{"group":{"id":1,"name":"Community","lockable":false,"created_at":"2012-01-18T18:02:15.000Z","updated_at":"2025-12-14T01:33:56.000Z","description":"Problems submitted by members of the MATLAB Central community.","is_default":true,"created_by":161519,"badge_id":null,"featured":false,"trending":false,"solution_count_in_trending_period":0,"trending_last_calculated":"2025-12-14T00:00:00.000Z","image_id":null,"published":true,"community_created":false,"status_id":2,"is_default_group_for_player":false,"deleted_by":null,"deleted_at":null,"restored_by":null,"restored_at":null,"description_opc":null,"description_html":null,"published_at":null},"problems":[{"id":61183,"title":"Estimate brake line pressure required for a given force.","description":"Hydraulic braking systems amplify pedal input to generate braking force. Given braking force and piston area, compute the hydraulic pressure required inside the brake lines.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eHydraulic braking systems amplify pedal input to generate braking force. Given braking force and piston area, compute the hydraulic pressure required inside the brake lines.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function P = brakePressure(F,A)\r\nP = 0;\r\nend\r\n","test_suite":"%%\r\nF = 4000; A = 0.004;\r\nP_correct = 1e6;\r\nassert(abs(brakePressure(F,A)-P_correct) \u003c 1)\r\n\r\n%%\r\nF = 3000; A = 0.003;\r\nP_correct = 1e6;\r\nassert(abs(brakePressure(F,A)-P_correct) \u003c 1)\r\n\r\n%%\r\nF = 0; A = 0.005;\r\nP_correct = 0;\r\nassert(isequal(brakePressure(F,A),P_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-02-02T06:25:47.000Z","deleted_by":null,"deleted_at":null,"solvers_count":39,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T06:25:43.000Z","updated_at":"2026-03-31T16:42:26.000Z","published_at":"2026-02-02T06:25:47.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHydraulic braking systems amplify pedal input to generate braking force. Given braking force and piston area, compute the hydraulic pressure required inside the brake lines.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":1875,"title":"GJam: 2013 China Event: Cannon Angle","description":"This Challenge is derived from \u003chttp://code.google.com/codejam/contest/2933486/dashboard#s=p1 GJam 2013 China Captain Hammer\u003e. The problem is modified to fit within Cody dimensions.\r\n\r\nThe Challenge is to return the lower angle of a cannon given a target distance and an initial cannonball velocity. Gravity is a constant at 9.8m/sec^2, A valid solution is assured. (Error tolerance 2e-6).\r\n\r\n*Input:* [v d]  Velocity and Distance in meters.\r\n\r\n*Output:* theta  in units of degrees with an accuracy of 2e-6\r\n\r\n\r\n*Competition Summary:*  Best Time of 8 minutes,  755/1070 completed\r\n\r\nThe winner completed all three GJam China Challenges in 26 minutes with second at 43 minutes.\r\n","description_html":"\u003cp\u003eThis Challenge is derived from \u003ca href = \"http://code.google.com/codejam/contest/2933486/dashboard#s=p1\"\u003eGJam 2013 China Captain Hammer\u003c/a\u003e. The problem is modified to fit within Cody dimensions.\u003c/p\u003e\u003cp\u003eThe Challenge is to return the lower angle of a cannon given a target distance and an initial cannonball velocity. Gravity is a constant at 9.8m/sec^2, A valid solution is assured. (Error tolerance 2e-6).\u003c/p\u003e\u003cp\u003e\u003cb\u003eInput:\u003c/b\u003e [v d]  Velocity and Distance in meters.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e theta  in units of degrees with an accuracy of 2e-6\u003c/p\u003e\u003cp\u003e\u003cb\u003eCompetition Summary:\u003c/b\u003e  Best Time of 8 minutes,  755/1070 completed\u003c/p\u003e\u003cp\u003eThe winner completed all three GJam China Challenges in 26 minutes with second at 43 minutes.\u003c/p\u003e","function_template":"function theta=Cannon(v,d)\r\n  theta=0;\r\nend","test_suite":"%%\r\ntic\r\nvd=[249 6326 ];\r\nexp=44.5948575;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[77 41 ];\r\nexp=1.9429163;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[28 11 ];\r\nexp=3.9516039;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[105 21 ];\r\nexp=0.5347917;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[147 51 ];\r\nexp=0.6626633;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3210 ];\r\nexp=10.2293872;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[219 61 ];\r\nexp=0.3570850;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[240 41 ];\r\nexp=0.1998405;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[179 3269 ];\r\nexp=44.5041154;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3480 ];\r\nexp=11.1338133;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[102 81 ];\r\nexp=2.1878908;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[121 51 ];\r\nexp=0.9781434;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[138 31 ];\r\nexp=0.4570257;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[210 4500 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[192 3761 ];\r\nexp=44.4745779;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[37 41 ];\r\nexp=8.5337735;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[32 41 ];\r\nexp=11.5514232;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[199 81 ];\r\nexp=0.5742839;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3360 ];\r\nexp=10.7304643;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[233 71 ];\r\nexp=0.3671784;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[266 81 ];\r\nexp=0.3214027;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[27 21 ];\r\nexp=8.1988972;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[279 21 ];\r\nexp=0.0757408;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5230 ];\r\nexp=17.3572961;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[279 51 ];\r\nexp=0.1839431;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[218 21 ];\r\nexp=0.1240585;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7690 ];\r\nexp=28.4309587;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[89 31 ];\r\nexp=1.0990234;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[141 2028 ];\r\nexp=44.2618026;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[178 81 ];\r\nexp=0.7178094;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[132 71 ];\r\nexp=1.1443126;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 690 ];\r\nexp=2.1544417;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6970 ];\r\nexp=24.6861041;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[41 1 ];\r\nexp=0.1670142;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[123 21 ];\r\nexp=0.3897097;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[48 61 ];\r\nexp=7.5190650;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[77 81 ];\r\nexp=3.8470546;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[152 71 ];\r\nexp=0.8628902;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[267 11 ];\r\nexp=0.0433201;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[164 21 ];\r\nexp=0.2192071;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4310 ];\r\nexp=13.9947943;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[256 71 ];\r\nexp=0.3041622;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[192 41 ];\r\nexp=0.3122545;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7110 ];\r\nexp=25.3662790;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[98 31 ];\r\nexp=0.9063600;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[286 21 ];\r\nexp=0.0720786;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[44 91 ];\r\nexp=13.7142226;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8360 ];\r\nexp=32.7741901;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5060 ];\r\nexp=16.7170592;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[194 81 ];\r\nexp=0.6042720;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[96 61 ];\r\nexp=1.8595639;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[190 1 ];\r\nexp=0.0077770;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[237 51 ];\r\nexp=0.2549165;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[52 31 ];\r\nexp=3.2254600;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[250 71 ];\r\nexp=0.3189378;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[29 61 ];\r\nexp=22.6508544;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4030 ];\r\nexp=13.0143792;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[39 31 ];\r\nexp=5.7607904;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[62 61 ];\r\nexp=4.4733355;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[246 61 ];\r\nexp=0.2829993;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[86 51 ];\r\nexp=1.9374169;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[252 91 ];\r\nexp=0.4023216;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[275 11 ];\r\nexp=0.0408363;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[49 81 ];\r\nexp=9.6529702;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[127 11 ];\r\nexp=0.1914728;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[223 61 ];\r\nexp=0.3443890;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[160 21 ];\r\nexp=0.2303047;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[196 31 ];\r\nexp=0.2265546;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[55 91 ];\r\nexp=8.5730698;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[110 1234 ];\r\nexp=44.0395169;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[274 61 ];\r\nexp=0.2281140;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6800 ];\r\nexp=23.8846446;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3310 ];\r\nexp=10.5630642;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[44 31 ];\r\nexp=4.5141266;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[295 1 ];\r\nexp=0.0032261;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[64 11 ];\r\nexp=0.7540525;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[240 21 ];\r\nexp=0.1023567;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[91 21 ];\r\nexp=0.7120327;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1870 ];\r\nexp=5.8744286;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1730 ];\r\nexp=5.4290641;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[259 51 ];\r\nexp=0.2134486;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[51 91 ];\r\nexp=10.0258563;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4200 ];\r\nexp=13.6075829;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[262 81 ];\r\nexp=0.3312919;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[74 81 ];\r\nexp=4.1674764;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[88 81 ];\r\nexp=2.9417237;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[255 91 ];\r\nexp=0.3929103;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[72 41 ];\r\nexp=2.2226617;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7900 ];\r\nexp=29.6707716;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1620 ];\r\nexp=5.0800699;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[253 71 ];\r\nexp=0.3114186;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[265 91 ];\r\nexp=0.3638145;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[248 1 ];\r\nexp=0.0045647;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6090 ];\r\nexp=20.7696393;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[158 71 ];\r\nexp=0.7985813;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2170 ];\r\nexp=6.8338053;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1500 ];\r\nexp=4.7002140;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[163 31 ];\r\nexp=0.3275780;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[139 31 ];\r\nexp=0.4504729;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[271 21 ];\r\nexp=0.0802786;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[113 41 ];\r\nexp=0.9016072;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[156 81 ];\r\nexp=0.9346125;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[100 61 ];\r\nexp=1.7135925;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[85 91 ];\r\nexp=3.5451226;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[43 61 ];\r\nexp=9.4316060;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[57 61 ];\r\nexp=5.3012744;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[136 61 ];\r\nexp=0.9260755;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5200 ];\r\nexp=17.2436039;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[159 71 ];\r\nexp=0.7885653;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[86 61 ];\r\nexp=2.3180653;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8140 ];\r\nexp=31.2094004;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5190 ];\r\nexp=17.2057754;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[259 6845 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6570 ];\r\nexp=22.8379951;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[285 71 ];\r\nexp=0.2454102;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6460 ];\r\nexp=22.3511092;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[75 573 ];\r\nexp=43.3260450;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[46 41 ];\r\nexp=5.4730826;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[52 21 ];\r\nexp=2.1824862;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5950 ];\r\nexp=20.1913108;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[68 91 ];\r\nexp=5.5599659;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[64 21 ];\r\nexp=1.4399949;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[36 11 ];\r\nexp=2.3856596;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[134 21 ];\r\nexp=0.3283507;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[9 1 ];\r\nexp=3.4745532;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[143 31 ];\r\nexp=0.4256222;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[116 91 ];\r\nexp=1.9000393;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[23 41 ];\r\nexp=24.7121091;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8390 ];\r\nexp=33.0022766;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[200 51 ];\r\nexp=0.3579647;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[66 91 ];\r\nexp=5.9068209;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[203 21 ];\r\nexp=0.1430697;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 230 ];\r\nexp=0.7175455;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7250 ];\r\nexp=26.0668121;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[81 71 ];\r\nexp=3.0438586;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[184 91 ];\r\nexp=0.7547006;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[273 41 ];\r\nexp=0.1544470;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[224 91 ];\r\nexp=0.5091983;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[25 1 ];\r\nexp=0.4492173;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[243 51 ];\r\nexp=0.2424831;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4920 ];\r\nexp=16.1968290;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 840 ];\r\nexp=2.6239945;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2740 ];\r\nexp=8.6794304;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[49 91 ];\r\nexp=10.9018740;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[244 81 ];\r\nexp=0.3819768;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[197 31 ];\r\nexp=0.2242603;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[186 31 ];\r\nexp=0.2515707;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[278 71 ];\r\nexp=0.2579249;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[258 1 ];\r\nexp=0.0042177;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2990 ];\r\nexp=9.5002916;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[10 1 ];\r\nexp=2.8120066;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7390 ];\r\nexp=26.7901102;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 430 ];\r\nexp=1.3418485;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[46 215 ];\r\nexp=42.3568299;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6250 ];\r\nexp=21.4435357;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[109 1 ];\r\nexp=0.0236301;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[152 31 ];\r\nexp=0.3767088;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[290 41 ];\r\nexp=0.1368700;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[277 21 ];\r\nexp=0.0768385;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[136 81 ];\r\nexp=1.2298703;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 910 ];\r\nexp=2.8433535;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[224 21 ];\r\nexp=0.1175014;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2440 ];\r\nexp=7.7039453;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[119 71 ];\r\nexp=1.4081796;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[20 31 ];\r\nexp=24.7100694;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5120 ];\r\nexp=16.9419243;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1940 ];\r\nexp=6.0976449;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[119 1445 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[255 6635 ];\r\nexp=44.7753101;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 280 ];\r\nexp=0.8735777;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[219 41 ];\r\nexp=0.2400045;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[262 61 ];\r\nexp=0.2494890;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 970 ];\r\nexp=3.0315083;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7720 ];\r\nexp=28.6029416;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[189 31 ];\r\nexp=0.2436475;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[110 51 ];\r\nexp=1.1836603;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[298 61 ];\r\nexp=0.1928498;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[231 5445 ];\r\nexp=44.9999996;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[69 81 ];\r\nexp=4.7988649;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[107 11 ];\r\nexp=0.2697430;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[114 21 ];\r\nexp=0.4536767;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[47 225 ];\r\nexp=43.2757298;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[17 1 ];\r\nexp=0.9716372;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[130 81 ];\r\nexp=1.3460985;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4630 ];\r\nexp=15.1376561;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[121 91 ];\r\nexp=1.7460565;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[82 41 ];\r\nexp=1.7129065;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[199 31 ];\r\nexp=0.2197751;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[93 71 ];\r\nexp=2.3071761;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5540 ];\r\nexp=18.5513095;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[126 41 ];\r\nexp=0.7251166;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4260 ];\r\nexp=13.8184496;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 440 ];\r\nexp=1.3730779;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3130 ];\r\nexp=9.9634881;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[145 61 ];\r\nexp=0.8146500;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1170 ];\r\nexp=3.6596870;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[200 4081 ];\r\nexp=44.4955953;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[271 41 ];\r\nexp=0.1567351;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1490 ];\r\nexp=4.6685979;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[291 21 ];\r\nexp=0.0696230;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[139 51 ];\r\nexp=0.7411528;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[53 51 ];\r\nexp=5.1245500;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[42 71 ];\r\nexp=11.6156650;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[243 91 ];\r\nexp=0.4326773;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4430 ];\r\nexp=14.4204070;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[210 11 ];\r\nexp=0.0700282;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[112 61 ];\r\nexp=1.3657683;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[219 31 ];\r\nexp=0.1814659;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4910 ];\r\nexp=16.1599009;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[44 11 ];\r\nexp=1.5959920;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[192 11 ];\r\nexp=0.0837741;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[276 71 ];\r\nexp=0.2616766;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[75 91 ];\r\nexp=4.5611459;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[166 21 ];\r\nexp=0.2139567;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[195 41 ];\r\nexp=0.3027202;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[116 81 ];\r\nexp=1.6909858;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[282 8114 ];\r\nexp=44.6253583;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[37 11 ];\r\nexp=2.2581760;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1910 ];\r\nexp=6.0019356;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[182 1 ];\r\nexp=0.0084757;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[176 21 ];\r\nexp=0.1903338;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[120 1 ];\r\nexp=0.0194965;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1320 ];\r\nexp=4.1319681;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[298 9061 ];\r\nexp=44.6614758;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7700 ];\r\nexp=28.4881098;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[79 636 ];\r\nexp=43.5312934;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5280 ];\r\nexp=17.5474818;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[227 31 ];\r\nexp=0.1689006;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[275 41 ];\r\nexp=0.1522086;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[171 1 ];\r\nexp=0.0096012;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[229 91 ];\r\nexp=0.4872031;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[200 1 ];\r\nexp=0.0070187;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[147 41 ];\r\nexp=0.5327126;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[169 31 ];\r\nexp=0.3047300;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[133 41 ];\r\nexp=0.6507837;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1150 ];\r\nexp=3.5967945;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[147 1 ];\r\nexp=0.0129922;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[144 51 ];\r\nexp=0.6905672;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[30 51 ];\r\nexp=16.8668385;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[217 4805 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[131 1 ];\r\nexp=0.0163597;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[58 41 ];\r\nexp=3.4299252;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[116 61 ];\r\nexp=1.2731382;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[43 1 ];\r\nexp=0.1518392;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[167 21 ];\r\nexp=0.2114020;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[295 31 ];\r\nexp=0.1000086;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[217 51 ];\r\nexp=0.3040728;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7220 ];\r\nexp=25.9148699;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[25 51 ];\r\nexp=26.5497777;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3620 ];\r\nexp=11.6073520;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[67 31 ];\r\nexp=1.9402732;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 31 ];\r\nexp=0.0967027;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8610 ];\r\nexp=34.8206771;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[81 91 ];\r\nexp=3.9060385;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[57 31 ];\r\nexp=2.6826598;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 180 ];\r\nexp=0.5615346;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[73 81 ];\r\nexp=4.2832883;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[201 21 ];\r\nexp=0.1459311;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[68 11 ];\r\nexp=0.6679330;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[159 51 ];\r\nexp=0.5663996;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[204 1 ];\r\nexp=0.0067462;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[189 81 ];\r\nexp=0.6366722;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 590 ];\r\nexp=1.8417362;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[149 61 ];\r\nexp=0.7714868;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8980 ];\r\nexp=38.9553303;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[216 11 ];\r\nexp=0.0661918;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[119 91 ];\r\nexp=1.8053178;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[125 81 ];\r\nexp=1.4560313;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6750 ];\r\nexp=23.6536081;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 790 ];\r\nexp=2.4674046;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4520 ];\r\nexp=14.7419107;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6830 ];\r\nexp=24.0242561;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[94 51 ];\r\nexp=1.6213062;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[75 21 ];\r\nexp=1.0483648;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5630 ];\r\nexp=18.9049816;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[86 71 ];\r\nexp=2.6991243;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[43 31 ];\r\nexp=4.7284323;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[193 31 ];\r\nexp=0.2336526;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[259 31 ];\r\nexp=0.1297425;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[287 21 ];\r\nexp=0.0715772;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6870 ];\r\nexp=24.2115915;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[57 41 ];\r\nexp=3.5519442;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[239 11 ];\r\nexp=0.0540650;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[192 71 ];\r\nexp=0.5407548;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8470 ];\r\nexp=33.6315148;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[77 61 ];\r\nexp=2.8933815;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[105 1125 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 9183 ];\r\nexp=44.6530547;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7170 ];\r\nexp=25.6638839;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5560 ];\r\nexp=18.6296154;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 980 ];\r\nexp=3.0628800;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[145 91 ];\r\nexp=1.2154985;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5820 ];\r\nexp=19.6630507;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[32 61 ];\r\nexp=17.8587444;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5270 ];\r\nexp=17.5093740;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[237 31 ];\r\nexp=0.1549479;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[168 1 ];\r\nexp=0.0099472;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[41 71 ];\r\nexp=12.2256701;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[207 11 ];\r\nexp=0.0720728;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[250 61 ];\r\nexp=0.2740155;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 51 ];\r\nexp=0.1590921;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[161 51 ];\r\nexp=0.5524132;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[265 1 ];\r\nexp=0.0039979;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[246 21 ];\r\nexp=0.0974246;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[195 61 ];\r\nexp=0.4503988;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[160 2612 ];\r\nexp=44.6077195;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6150 ];\r\nexp=21.0206716;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[83 21 ];\r\nexp=0.8559461;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[160 61 ];\r\nexp=0.6690338;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[156 61 ];\r\nexp=0.7037899;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[162 1 ];\r\nexp=0.0106977;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[166 61 ];\r\nexp=0.6215362;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[107 51 ];\r\nexp=1.2510059;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[215 41 ];\r\nexp=0.2490182;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[212 91 ];\r\nexp=0.5684822;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[84 61 ];\r\nexp=2.4300259;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6630 ];\r\nexp=23.1071658;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[119 61 ];\r\nexp=1.2097168;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[7 1 ];\r\nexp=5.7684795;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6730 ];\r\nexp=23.5617578;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2860 ];\r\nexp=9.0724806;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[274 21 ];\r\nexp=0.0785303;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1510 ];\r\nexp=4.7318359;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[42 21 ];\r\nexp=3.3498826;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5220 ];\r\nexp=17.3193640;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8670 ];\r\nexp=35.3730578;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[18 31 ];\r\nexp=34.8306447;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8540 ];\r\nexp=34.2104815;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[256 21 ];\r\nexp=0.0899619;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[91 71 ];\r\nexp=2.4099422;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[247 51 ];\r\nexp=0.2346928;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[56 21 ];\r\nexp=1.8813698;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[135 91 ];\r\nexp=1.4023810;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3930 ];\r\nexp=12.6682378;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[97 41 ];\r\nexp=1.2237457;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[280 8000 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[280 41 ];\r\nexp=0.1468211;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[147 21 ];\r\nexp=0.2728412;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[23 11 ];\r\nexp=5.8790664;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[139 1 ];\r\nexp=0.0145308;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[78 620 ];\r\nexp=43.5307164;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[250 41 ];\r\nexp=0.1841728;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[69 41 ];\r\nexp=2.4205902;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2730 ];\r\nexp=8.6467533;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[141 91 ];\r\nexp=1.2854868;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3800 ];\r\nexp=12.2211854;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[290 11 ];\r\nexp=0.0367211;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[276 21 ];\r\nexp=0.0773963;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[105 11 ];\r\nexp=0.2801172;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[238 81 ];\r\nexp=0.4014801;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[200 91 ];\r\nexp=0.6387576;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[293 41 ];\r\nexp=0.1340815;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[299 9122 ];\r\nexp=44.6851269;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[21 1 ];\r\nexp=0.6366722;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[36 91 ];\r\nexp=21.7406299;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[270 7438 ];\r\nexp=44.5863296;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5870 ];\r\nexp=19.8652679;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[125 21 ];\r\nexp=0.3773380;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[132 81 ];\r\nexp=1.3055882;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4510 ];\r\nexp=14.7060881;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[111 91 ];\r\nexp=2.0753631;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[176 11 ];\r\nexp=0.0996981;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[76 81 ];\r\nexp=3.9496009;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[183 51 ];\r\nexp=0.4275657;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[144 41 ];\r\nexp=0.5551429;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[111 11 ];\r\nexp=0.2506519;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[232 21 ];\r\nexp=0.1095376;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[153 2388 ];\r\nexp=44.3197033;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[264 41 ];\r\nexp=0.1651571;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[203 1 ];\r\nexp=0.0068128;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[206 1 ];\r\nexp=0.0066158;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[190 41 ];\r\nexp=0.3188632;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[67 51 ];\r\nexp=3.1962494;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[59 21 ];\r\nexp=1.6946784;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8380 ];\r\nexp=32.9257979;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[108 51 ];\r\nexp=1.2279321;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[267 7274 ];\r\nexp=44.7042055;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[298 21 ];\r\nexp=0.0663905;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 9070 ];\r\nexp=40.4879078;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[247 31 ];\r\nexp=0.1426554;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1580 ];\r\nexp=4.9533543;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 310 ];\r\nexp=0.9672092;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[246 91 ];\r\nexp=0.4221877;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[110 81 ];\r\nexp=1.8807470;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[189 1 ];\r\nexp=0.0078595;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[299 91 ];\r\nexp=0.2857755;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4820 ];\r\nexp=15.8288860;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[184 41 ];\r\nexp=0.3399986;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[173 81 ];\r\nexp=0.7599105;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[201 61 ];\r\nexp=0.4239087;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1820 ];\r\nexp=5.7152103;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[130 41 ];\r\nexp=0.6811720;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[65 71 ];\r\nexp=4.7395084;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[192 91 ];\r\nexp=0.6931066;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[136 1887 ];\r\nexp=44.4506934;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[171 51 ];\r\nexp=0.4896861;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[236 91 ];\r\nexp=0.4587274;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[173 31 ];\r\nexp=0.2908008;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[35 41 ];\r\nexp=9.5737143;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 9020 ];\r\nexp=39.5832887;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[296 91 ];\r\nexp=0.2915978;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[33 41 ];\r\nexp=10.8258185;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4110 ];\r\nexp=13.2927675;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[277 1 ];\r\nexp=0.0036590;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[254 31 ];\r\nexp=0.1349008;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[82 81 ];\r\nexp=3.3899244;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[54 21 ];\r\nexp=2.0235395;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[54 91 ];\r\nexp=8.9040499;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[85 71 ];\r\nexp=2.7632032;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[14 1 ];\r\nexp=1.4329920;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[170 81 ];\r\nexp=0.7869742;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[42 51 ];\r\nexp=8.2296248;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[35 125 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3390 ];\r\nexp=10.8310888;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[122 81 ];\r\nexp=1.5285870;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[74 31 ];\r\nexp=1.5901570;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8170 ];\r\nexp=31.4129069;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1660 ];\r\nexp=5.2068859;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[134 41 ];\r\nexp=0.6411051;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[184 3454 ];\r\nexp=44.4258154;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[143 81 ];\r\nexp=1.1123483;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[67 91 ];\r\nexp=5.7294046;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[208 41 ];\r\nexp=0.2660616;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[169 81 ];\r\nexp=0.7963175;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[213 11 ];\r\nexp=0.0680695;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[152 61 ];\r\nexp=0.7413270;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[259 21 ];\r\nexp=0.0878899;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[174 71 ];\r\nexp=0.6584409;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[242 41 ];\r\nexp=0.1965510;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[265 31 ];\r\nexp=0.1239339;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6930 ];\r\nexp=24.4952155;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[177 1 ];\r\nexp=0.0089613;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8630 ];\r\nexp=35.0015489;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[281 8057 ];\r\nexp=44.7766386;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4450 ];\r\nexp=14.4916789;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[257 51 ];\r\nexp=0.2167838;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7210 ];\r\nexp=25.8644501;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8110 ];\r\nexp=31.0086245;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[120 31 ];\r\nexp=0.6044357;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4010 ];\r\nexp=12.9449893;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[85 737 ];\r\nexp=44.2615751;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[287 1 ];\r\nexp=0.0034084;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6900 ];\r\nexp=24.3530039;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[107 81 ];\r\nexp=1.9878552;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[73 91 ];\r\nexp=4.8168446;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5830 ];\r\nexp=19.7034001;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[125 51 ];\r\nexp=0.9165221;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[174 31 ];\r\nexp=0.2874678;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[258 91 ];\r\nexp=0.3838254;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[88 51 ];\r\nexp=1.8502291;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 890 ];\r\nexp=2.7806630;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[131 71 ];\r\nexp=1.1618593;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5890 ];\r\nexp=19.9464871;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[275 81 ];\r\nexp=0.3007089;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[201 31 ];\r\nexp=0.2154232;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[103 61 ];\r\nexp=1.6151178;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[169 11 ];\r\nexp=0.1081282;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[234 81 ];\r\nexp=0.4153242;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[127 41 ];\r\nexp=0.7137400;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[45 61 ];\r\nexp=8.5850615;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[268 71 ];\r\nexp=0.2775328;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[120 81 ];\r\nexp=1.5800158;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2520 ];\r\nexp=7.9631306;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[39 91 ];\r\nexp=17.9483177;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[113 31 ];\r\nexp=0.6816548;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[152 91 ];\r\nexp=1.1060655;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1260 ];\r\nexp=3.9429273;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6980 ];\r\nexp=24.7340581;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[212 61 ];\r\nexp=0.3810567;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[8 1 ];\r\nexp=4.4040343;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[153 61 ];\r\nexp=0.7316660;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[55 1 ];\r\nexp=0.0928099;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3080 ];\r\nexp=9.7977560;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[108 81 ];\r\nexp=1.9511562;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[81 41 ];\r\nexp=1.7555143;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[242 71 ];\r\nexp=0.3403741;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[46 81 ];\r\nexp=11.0165379;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[221 1 ];\r\nexp=0.0057482;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[249 71 ];\r\nexp=0.3215048;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7440 ];\r\nexp=27.0544802;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[45 21 ];\r\nexp=2.9165098;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[289 21 ];\r\nexp=0.0705899;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7520 ];\r\nexp=27.4846425;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[235 1 ];\r\nexp=0.0050837;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[299 1234 ];\r\nexp=3.8870928;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[250 1 ];\r\nexp=0.0044920;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[176 51 ];\r\nexp=0.4622558;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8510 ];\r\nexp=33.9588221;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[151 31 ];\r\nexp=0.3817151;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[61 1 ];\r\nexp=0.0754501;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[132 31 ];\r\nexp=0.4995219;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[238 21 ];\r\nexp=0.1040843;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[238 91 ];\r\nexp=0.4510494;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[101 31 ];\r\nexp=0.8533003;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[252 1 ];\r\nexp=0.0044210;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[101 41 ];\r\nexp=1.1286835;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[152 51 ];\r\nexp=0.6197772;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8830 ];\r\nexp=37.0236469;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[240 31 ];\r\nexp=0.1510984;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[134 51 ];\r\nexp=0.7975086;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1020 ];\r\nexp=3.1884039;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[257 91 ];\r\nexp=0.3868183;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[128 11 ];\r\nexp=0.1884927;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6160 ];\r\nexp=21.0627029;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[213 31 ];\r\nexp=0.1918335;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[255 51 ];\r\nexp=0.2201977;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[126 11 ];\r\nexp=0.1945242;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[280 51 ];\r\nexp=0.1826315;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[150 41 ];\r\nexp=0.5116148;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7480 ];\r\nexp=27.2684278;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4140 ];\r\nexp=13.3975114;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[133 51 ];\r\nexp=0.8095495;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[168 41 ];\r\nexp=0.4078483;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[281 71 ];\r\nexp=0.2524469;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[147 2205 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[113 1 ];\r\nexp=0.0219868;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[242 61 ];\r\nexp=0.2924323;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[56 91 ];\r\nexp=8.2607465;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[260 21 ];\r\nexp=0.0872152;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[22 31 ];\r\nexp=19.4398009;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[165 71 ];\r\nexp=0.7322451;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2190 ];\r\nexp=6.8980297;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7570 ];\r\nexp=27.7582308;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[141 41 ];\r\nexp=0.5790205;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4840 ];\r\nexp=15.9022391;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[142 11 ];\r\nexp=0.1531570;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7750 ];\r\nexp=28.7765421;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[232 81 ];\r\nexp=0.4225163;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[53 21 ];\r\nexp=2.1007558;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[123 81 ];\r\nexp=1.5038100;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[210 51 ];\r\nexp=0.3246830;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[273 1 ];\r\nexp=0.0037670;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[50 81 ];\r\nexp=9.2565056;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[298 1 ];\r\nexp=0.0031614;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[166 11 ];\r\nexp=0.1120718;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6260 ];\r\nexp=21.4861399;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[253 81 ];\r\nexp=0.3552825;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[144 91 ];\r\nexp=1.2324494;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[288 8463 ];\r\nexp=44.6385985;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[268 7328 ];\r\nexp=44.5316039;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[297 61 ];\r\nexp=0.1941507;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[62 41 ];\r\nexp=2.9999445;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[223 5074 ];\r\nexp=44.6458418;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[248 91 ];\r\nexp=0.4154052;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[106 61 ];\r\nexp=1.5249020;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[211 41 ];\r\nexp=0.2585494;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[120 21 ];\r\nexp=0.4094400;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[210 1 ];\r\nexp=0.0063662;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4660 ];\r\nexp=15.2461386;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[172 71 ];\r\nexp=0.6738453;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[214 91 ];\r\nexp=0.5579047;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[131 11 ];\r\nexp=0.1799582;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[50 255 ];\r\nexp=44.1896883;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[227 51 ];\r\nexp=0.2778715;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4330 ];\r\nexp=14.0654935;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[115 1 ];\r\nexp=0.0212287;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[80 91 ];\r\nexp=4.0049368;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[228 21 ];\r\nexp=0.1134147;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[104 11 ];\r\nexp=0.2855301;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[260 61 ];\r\nexp=0.2533422;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[290 1 ];\r\nexp=0.0033383;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[105 81 ];\r\nexp=2.0644344;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[57 71 ];\r\nexp=6.1830728;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[43 188 ];\r\nexp=42.5787456;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[214 71 ];\r\nexp=0.4352775;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[284 11 ];\r\nexp=0.0382891;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[267 41 ];\r\nexp=0.1614665;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[270 31 ];\r\nexp=0.1193862;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[131 51 ];\r\nexp=0.8344642;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[70 71 ];\r\nexp=4.0817971;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[21 41 ];\r\nexp=32.8296766;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[282 91 ];\r\nexp=0.3212706;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[24 11 ];\r\nexp=5.3933350;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[226 21 ];\r\nexp=0.1154310;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[227 11 ];\r\nexp=0.0599322;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4800 ];\r\nexp=15.7556484;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[134 81 ];\r\nexp=1.2668806;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[256 61 ];\r\nexp=0.2613212;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8860 ];\r\nexp=37.3715407;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[230 81 ];\r\nexp=0.4298969;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[182 91 ];\r\nexp=0.7713825;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[142 2057 ];\r\nexp=44.3369812;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[32 71 ];\r\nexp=21.4019868;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[142 61 ];\r\nexp=0.8494455;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3170 ];\r\nexp=10.0963242;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[191 61 ];\r\nexp=0.4694629;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[190 71 ];\r\nexp=0.5522004;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[205 71 ];\r\nexp=0.4743394;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[248 71 ];\r\nexp=0.3241029;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[166 31 ];\r\nexp=0.3158443;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[145 51 ];\r\nexp=0.6810732;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6050 ];\r\nexp=20.6033628;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[254 71 ];\r\nexp=0.3089712;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[185 71 ];\r\nexp=0.5824565;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3380 ];\r\nexp=10.7975318;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[296 71 ];\r\nexp=0.2275088;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[38 81 ];\r\nexp=16.6740056;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[24 1 ];\r\nexp=0.4874355;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[280 31 ];\r\nexp=0.1110109;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8690 ];\r\nexp=35.5640799;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4160 ];\r\nexp=13.4674481;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[252 61 ];\r\nexp=0.2696832;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[98 71 ];\r\nexp=2.0773304;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[209 81 ];\r\nexp=0.5206370;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2710 ];\r\nexp=8.5814338;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[57 21 ];\r\nexp=1.8158465;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[102 51 ];\r\nexp=1.3767520;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1770 ];\r\nexp=5.5561708;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8160 ];\r\nexp=31.3447605;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[74 71 ];\r\nexp=3.6499694;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[51 41 ];\r\nexp=4.4432920;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[297 91 ];\r\nexp=0.2896374;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[48 71 ];\r\nexp=8.7887794;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[140 41 ];\r\nexp=0.5873229;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[284 61 ];\r\nexp=0.2123322;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[229 41 ];\r\nexp=0.2195007;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[294 81 ];\r\nexp=0.2630966;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[138 71 ];\r\nexp=1.0469250;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[84 11 ];\r\nexp=0.4376931;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[220 11 ];\r\nexp=0.0638067;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 650 ];\r\nexp=2.0293307;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[261 31 ];\r\nexp=0.1277617;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[259 11 ];\r\nexp=0.0460375;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[150 21 ];\r\nexp=0.2620364;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3580 ];\r\nexp=11.4717190;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[295 71 ];\r\nexp=0.2290539;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8330 ];\r\nexp=32.5500293;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[127 21 ];\r\nexp=0.3655463;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[196 91 ];\r\nexp=0.6651000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7230 ];\r\nexp=25.9654030;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[55 51 ];\r\nexp=4.7550987;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[118 61 ];\r\nexp=1.2303199;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[172 61 ];\r\nexp=0.5789235;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3990 ];\r\nexp=12.8756810;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[49 41 ];\r\nexp=4.8168001;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8400 ];\r\nexp=33.0792168;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[272 51 ];\r\nexp=0.1935327;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[246 51 ];\r\nexp=0.2366048;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[209 71 ];\r\nexp=0.4563550;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[113 51 ];\r\nexp=1.1216128;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[58 11 ];\r\nexp=0.9181841;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[90 21 ];\r\nexp=0.7279469;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5580 ];\r\nexp=18.7080845;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[26 1 ];\r\nexp=0.4153242;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6020 ];\r\nexp=20.4792082;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[153 71 ];\r\nexp=0.8516442;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[231 71 ];\r\nexp=0.3735643;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[296 41 ];\r\nexp=0.1313774;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[218 51 ];\r\nexp=0.3012894;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[156 71 ];\r\nexp=0.8191945;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[244 91 ];\r\nexp=0.4291377;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[97 61 ];\r\nexp=1.8213680;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[33 21 ];\r\nexp=5.4466530;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[48 21 ];\r\nexp=2.5623281;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5180 ];\r\nexp=17.1679811;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3630 ];\r\nexp=11.6413032;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[164 81 ];\r\nexp=0.8456275;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[180 3306 ];\r\nexp=44.7534375;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[49 61 ];\r\nexp=7.2085690;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[89 21 ];\r\nexp=0.7444009;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2110 ];\r\nexp=6.6413404;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[199 4040 ];\r\nexp=44.3892211;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[297 31 ];\r\nexp=0.0986662;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5920 ];\r\nexp=20.0686784;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7180 ];\r\nexp=25.7138602;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5210 ];\r\nexp=17.2814667;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[212 11 ];\r\nexp=0.0687132;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[246 1 ];\r\nexp=0.0046393;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[250 11 ];\r\nexp=0.0494119;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[47 1 ];\r\nexp=0.1270938;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[112 41 ];\r\nexp=0.9177847;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5110 ];\r\nexp=16.9043649;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6410 ];\r\nexp=22.1324926;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7030 ];\r\nexp=24.9752527;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7970 ];\r\nexp=30.1045540;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[255 1 ];\r\nexp=0.0043176;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[222 5028 ];\r\nexp=44.4345459;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[247 61 ];\r\nexp=0.2807124;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[40 163 ];\r\nexp=43.3665978;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[88 21 ];\r\nexp=0.7614192;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[91 51 ];\r\nexp=1.7300957;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[145 21 ];\r\nexp=0.2804200;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[170 61 ];\r\nexp=0.5926273;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[95 11 ];\r\nexp=0.3421957;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[137 1 ];\r\nexp=0.0149581;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[220 51 ];\r\nexp=0.2958362;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[132 51 ];\r\nexp=0.8218652;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6850 ];\r\nexp=24.1177523;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[271 61 ];\r\nexp=0.2331926;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[184 31 ];\r\nexp=0.2570695;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3250 ];\r\nexp=10.3626812;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[11 1 ];\r\nexp=2.3227865;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[148 81 ];\r\nexp=1.0384257;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5400 ];\r\nexp=18.0076051;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[287 31 ];\r\nexp=0.1056617;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[183 11 ];\r\nexp=0.0922168;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[278 81 ];\r\nexp=0.2942536;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[291 1 ];\r\nexp=0.0033154;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[64 71 ];\r\nexp=4.8902189;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[290 61 ];\r\nexp=0.2036368;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[124 51 ];\r\nexp=0.9313695;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[230 21 ];\r\nexp=0.1114509;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[109 51 ];\r\nexp=1.2054913;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[84 91 ];\r\nexp=3.6304847;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[289 81 ];\r\nexp=0.2722793;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[138 1 ];\r\nexp=0.0147421;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[130 91 ];\r\nexp=1.5124296;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[182 21 ];\r\nexp=0.1779910;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8780 ];\r\nexp=36.4745305","published":true,"deleted":false,"likes_count":7,"comments_count":4,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":58,"test_suite_updated_at":"2014-02-10T18:16:06.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-09-15T23:22:36.000Z","updated_at":"2026-03-31T20:37:05.000Z","published_at":"2013-09-15T23:34:41.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is derived from\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://code.google.com/codejam/contest/2933486/dashboard#s=p1\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eGJam 2013 China Captain Hammer\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. The problem is modified to fit within Cody dimensions.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Challenge is to return the lower angle of a cannon given a target distance and an initial cannonball velocity. Gravity is a constant at 9.8m/sec^2, A valid solution is assured. (Error tolerance 2e-6).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e [v d] Velocity and Distance in meters.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e theta in units of degrees with an accuracy of 2e-6\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCompetition Summary:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Best Time of 8 minutes, 755/1070 completed\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe winner completed all three GJam China Challenges in 26 minutes with second at 43 minutes.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":49723,"title":"Find the efficiency","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 10.5px; transform-origin: 407.5px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 172.958px 7.7px; transform-origin: 172.958px 7.7px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFind the efficiency of engine from Temperature tc and th\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = ef(tc,th)\r\n  y = x;\r\nend","test_suite":"%%\r\ntc = 50;th=60;\r\ny_correct =    16.6667;\r\nassert(isequal(ef(tc,th),y_correct))\r\n%%\r\ntc = 20;th=60;\r\ny_correct = 66.6667;\r\nassert(isequal(ef(tc,th),y_correct))\r\n%%\r\ntc = 50;th=90;\r\ny_correct = 44.4444;\r\nassert(isequal(ef(tc,th),y_correct))\r\n%%\r\ntc =20;th=80;\r\ny_correct = 75;\r\nassert(isequal(ef(tc,th),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":610936,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":36,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-31T03:31:17.000Z","updated_at":"2026-04-02T13:44:01.000Z","published_at":"2020-12-31T03:45:14.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind the efficiency of engine from Temperature tc and th\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":55160,"title":"Find distance travelled by an object starting from rest in time 't' and linear acceleration 'a' = 3t","description":"Find distance travelled by an object starting from rest in time 't' with linear acceleration a = 3t. You are given time t as an input to the function.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind distance travelled by an object starting from rest in time 't' with linear acceleration a = 3t. You are given time t as an input to the function.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s = your_fcn_name(t)\r\n  s = a;\r\nend","test_suite":"%%\r\nt = 2;\r\ny_correct = 4;\r\nassert(isequal(your_fcn_name(t),y_correct))\r\n\r\n%%\r\nt = 0;\r\ny_correct = 0;\r\nassert(isequal(your_fcn_name(t),y_correct))\r\n\r\n%%\r\nt = 1;\r\ny_correct = 0.5;\r\nassert(isequal(your_fcn_name(t),y_correct))\r\n\r\n%%\r\nt = 12;\r\ny_correct = 864;\r\nassert(isequal(your_fcn_name(t),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":2439180,"edited_by":2439180,"edited_at":"2022-07-13T19:07:25.000Z","deleted_by":null,"deleted_at":null,"solvers_count":37,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-07-13T19:07:08.000Z","updated_at":"2026-02-08T05:29:58.000Z","published_at":"2022-07-13T19:07:25.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind distance travelled by an object starting from rest in time 't' with linear acceleration a = 3t. You are given time t as an input to the function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61181,"title":"Compute braking force using vehicle mass and acceleration.","description":"Compute braking force required to stop a vehicle of mass 'm' and with acceleration 'a' \r\nRemember:  F = m × a.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 25.5px; transform-origin: 407px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCompute braking force required to stop a vehicle of mass 'm' and with acceleration 'a' \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eRemember:  F = m × a.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function F = brakingForce(m,a)\r\nF = 0;\r\nend\r\n","test_suite":"%%\r\nassert(isequal(brakingForce(1000,5),5000))\r\n\r\n%%\r\nassert(isequal(brakingForce(0,10),0))\r\n\r\n%%\r\nassert(isequal(brakingForce(1500,3),4500))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-02-02T05:31:40.000Z","deleted_by":null,"deleted_at":null,"solvers_count":43,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T05:09:13.000Z","updated_at":"2026-04-02T00:32:17.000Z","published_at":"2026-02-02T05:25:08.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCompute braking force required to stop a vehicle of mass 'm' and with acceleration 'a' \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember:  F = m × a.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":47113,"title":"Distance Travelled by Vehicle","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 101.2px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 50.6px; transform-origin: 407px 50.6px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 41.6px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 20.8px; text-align: left; transform-origin: 384px 20.8px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven a vehicle travelling at a velocity of 10m/s and having a constant acceleration of 5m/s^2, write a function that gives the distance travelled by the vehicle in time t.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.8px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.4px; text-align: left; transform-origin: 384px 10.4px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eUnits of distance is m and time sec.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.8px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.4px; text-align: left; transform-origin: 384px 10.4px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eHint:  Remember Newton\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function dist = d_in_t(t)\r\n  dist = t;\r\nend","test_suite":"%%\r\nt = 1;\r\ny_correct = 12.5;\r\nassert(isequal(d_in_t(t),y_correct))\r\n%%\r\nt = 5;\r\ny_correct = 112.5;\r\nassert(isequal(d_in_t(t),y_correct))\r\n%%\r\nt = 10;\r\ny_correct = 350;\r\nassert(isequal(d_in_t(t),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":511890,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":89,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-28T08:21:47.000Z","updated_at":"2026-02-05T15:52:02.000Z","published_at":"2020-10-28T08:21:47.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a vehicle travelling at a velocity of 10m/s and having a constant acceleration of 5m/s^2, write a function that gives the distance travelled by the vehicle in time t.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eUnits of distance is m and time sec.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHint:  Remember Newton\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":45909,"title":"Convert Angstrom to Meters","description":"Write a code that converts the angstrom unit to meters.(A is angstrom and m is meters.)","description_html":"\u003cp\u003eWrite a code that converts the angstrom unit to meters.(A is angstrom and m is meters.)\u003c/p\u003e","function_template":"function m = conv_fcn_met(A)\r\n  m = ;\r\nend","test_suite":"%%\r\nA = 1;\r\nm_correct = 10^-10;\r\nassert(isequal(conv_fcn_met(A),m_correct))\r\n\r\n%%\r\nA = 0;\r\nm_correct = 0;\r\nassert(isequal(conv_fcn_met(A),m_correct))\r\n\r\n%%\r\nA = 10;\r\nm_correct = 10^-9;\r\nassert(isequal(conv_fcn_met(A),m_correct))\r\n\r\n%%\r\nA = 400;\r\nm_correct = 4*10^-8 ;\r\nassert(isequal(conv_fcn_met(A),m_correct))\r\n\r\n%%\r\nA = 30000;\r\nm_correct = 3*10^-6;\r\nassert(isequal(conv_fcn_met(A),m_correct))\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":444624,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":102,"test_suite_updated_at":"2020-06-13T17:36:05.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-06-13T17:27:41.000Z","updated_at":"2026-02-06T10:07:54.000Z","published_at":"2020-06-13T17:27:39.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a code that converts the angstrom unit to meters.(A is angstrom and m is meters.)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1360,"title":"Special Relativity 101.","description":"Special relativity states that the effective mass of an object varies as a function of its velocity. If *c* is the speed of light (c approx. = 300,000 km/s) and *v* is the velocity of the object (in km/s), find the effective mass m' of an object traveling at a velocity v. Assume that at v = 0 m/s, m = 1 kg.","description_html":"\u003cp\u003eSpecial relativity states that the effective mass of an object varies as a function of its velocity. If \u003cb\u003ec\u003c/b\u003e is the speed of light (c approx. = 300,000 km/s) and \u003cb\u003ev\u003c/b\u003e is the velocity of the object (in km/s), find the effective mass m' of an object traveling at a velocity v. Assume that at v = 0 m/s, m = 1 kg.\u003c/p\u003e","function_template":"function mprime = specialRelativity(v)\r\n  mprime = v;\r\nend","test_suite":"%%\r\nv = 0;\r\ny_correct = 1;\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 1000;      % km/s\r\ny_correct = 1; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 10000;          % km/s\r\ny_correct = 1.0006; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 50000;          % km/s\r\ny_correct = 1.0142; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 100000;         % km/s\r\ny_correct = 1.0607; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 200000;         % km/s\r\ny_correct = 1.3416; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 250000;         % km/s\r\ny_correct = 1.8091; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 290000;         % km/s\r\ny_correct = 3.9057; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 299000;          % km/s\r\ny_correct = 12.2577; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 299900;          % km/s\r\ny_correct = 38.7331; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 299999;           % km/s\r\ny_correct = 387.2987; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":810,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":112,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-03-19T00:59:56.000Z","updated_at":"2026-02-06T11:57:49.000Z","published_at":"2013-03-19T01:00:25.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSpecial relativity states that the effective mass of an object varies as a function of its velocity. If\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ec\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is the speed of light (c approx. = 300,000 km/s) and\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ev\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is the velocity of the object (in km/s), find the effective mass m' of an object traveling at a velocity v. Assume that at v = 0 m/s, m = 1 kg.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":53059,"title":"Siren frequency and Doppler effect.","description":"The Doppler effect is described on OpenStax University Physics at https://openstax.org/books/university-physics-volume-1/pages/17-7-the-doppler-effect and in other sources.  \r\nConsider the  Doppler effect for sound waves travelling in air.  Use the equations in the OpenStax source (or equivalent information ) to model the Doppler effect. \r\nA moving vehicle with a speed u, having a siren frequency, fs, approaches a static (fixed)  observer and then passes the static observer.   A siren , in this context,  is also called a horn.  The vehicle motion is modelled as straight-line motion. \r\nOne way of summarising the effect to the formula for two frequencies\r\n  \r\nor written in MATLAB syntax as\r\nfh = fs *(c/(c-u)) \r\nfl = fs *(c/(c+u)) \r\nwhere fs is the frequency of a siren in Hz,  c is the  speed of sound in m/s , u is the speed of the moving vehicle in m/s,  fh is the higher frequency in Hz as the vehicle approaches the  stationary observer and the fl the lower frequency  in Hz as the vehicle recedes from (passes) the observer. \r\nCalculate the siren frequency, fs, to the nearest Hz.  The function definition is \r\nfs = findSirenFrequency ( c, u, fh, fl )\r\nFor example, if  c = 345  m/s  ; u= 30.5556 m/s ;  fh = 877  Hz and fl =734 Hz   then fs= 799 Hz.   Assume  fh ≥ fl and c \u003e u.\r\n ","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 502.667px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 251.333px; transform-origin: 406.5px 251.333px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 41.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 20.6667px; text-align: left; transform-origin: 383.5px 20.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThe Doppler effect is described on OpenStax University Physics at \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://openstax.org/books/university-physics-volume-1/pages/17-7-the-doppler-effect\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ehttps://openstax.org/books/university-physics-volume-1/pages/17-7-the-doppler-effect\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e and in other sources.  \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 41.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 20.6667px; text-align: left; transform-origin: 383.5px 20.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eConsider the  Doppler effect for sound waves travelling in air.  Use the equations in the OpenStax source (or equivalent information ) to model the Doppler effect. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 41.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 20.6667px; text-align: left; transform-origin: 383.5px 20.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eA moving vehicle with a speed \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eu\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e, having a siren frequency, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efs,\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e approaches a static (fixed)  observer and then passes the static observer.   A siren , in this context,  is also called a horn.  The vehicle motion is modelled as straight-line motion. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.3333px; text-align: left; transform-origin: 383.5px 10.3333px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eOne way of summarising the effect to the formula for two frequencies\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.3333px; text-align: center; transform-origin: 383.5px 10.3333px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e  \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.3333px; text-align: left; transform-origin: 383.5px 10.3333px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eor written in MATLAB syntax as\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.6667px; text-align: left; transform-origin: 383.5px 10.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003efh = fs *(c/(c-u)) \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.6667px; text-align: left; transform-origin: 383.5px 10.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003efl = fs *(c/(c+u)) \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 62px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 31px; text-align: left; transform-origin: 383.5px 31px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ewhere \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efs \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eis the frequency of a siren in Hz,  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ec \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eis the  speed of sound in m/s , \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eu \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eis the speed of the moving vehicle in m/s,  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efh\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e is the higher frequency in Hz as the vehicle approaches the  stationary observer and the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efl\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e the lower frequency  in Hz as the vehicle recedes from (passes) the observer. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.3333px; text-align: left; transform-origin: 383.5px 10.3333px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eCalculate the siren frequency, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efs\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"text-decoration: underline; text-decoration-line: underline; \"\u003eto the nearest Hz.\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e  The function definition is \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.6667px; text-align: left; transform-origin: 383.5px 10.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003efs = findSirenFrequency ( c, u, fh, fl )\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 41.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 20.6667px; text-align: left; transform-origin: 383.5px 20.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor example, if  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ec\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e = 345  m/s  ; \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eu\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e= 30.5556 m/s ;  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efh\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e = 877  Hz and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efl \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e=734 Hz   then \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efs\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e= 799 Hz.   Assume  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efh\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e ≥ \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efl\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ec\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e \u0026gt; \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eu\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.3333px; text-align: left; transform-origin: 383.5px 10.3333px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function  fs = findSirenFrequency ( c, u, fh, fl )\r\n \r\n  fs=1;\r\n  \r\nend\r\n\r\n\r\n","test_suite":"%testdopp2\r\n \r\n%%\r\n%T1\r\nc = 345 ; u = 30.5556    ; fh  = 877 ;   fl =  734;\r\nfs=findSirenFrequency ( c, u, fh, fl );\r\nfs_correct = 799;\r\n%fs_correct = 801; %incorrect value should cause assert to fail.\r\ndelta=1 ; % One Hz plus or minus tolerance on answer \r\nassert(and( ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003e= fs_correct-delta , ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003c= fs_correct+delta   ...\r\n          ) == 1 ) \r\n      \r\n \r\n%%\r\n%T2      \r\nc = 335 ; u = 12.8846    ; fh  = 208 ;   fl =  193;\r\nfs=findSirenFrequency ( c, u, fh, fl );\r\nfs_correct= 200 ;\r\n%fs_correct= 322 ;\r\ndelta=1;  % One Hz plus or minus tolerance on answer \r\nassert(and( ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003e= fs_correct-delta , ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003c= fs_correct+delta   ...\r\n          ) == 1 ) \r\n \r\n%%      \r\n%T3\r\n%Test 3\r\nc = 228.9596 ; u = 111    ; fh  = 1941 ;   fl =  674;\r\nfs_correct= 1000 ;\r\n%fs_correct= 2000; %incorrect value should cause assert to fail.\r\nfs=findSirenFrequency ( c, u, fh, fl );\r\ndelta=1 ; % One Hz plus or minus tolerance on answer \r\nassert(and( ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003e= fs_correct-delta , ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003c= fs_correct+delta   ...\r\n          ) == 1 ) \r\n \r\n%%\r\n%T4   \r\nc = 335 ; u = 0    ; fh  = 333 ;   fl =  333;\r\nfs_correct= 333 ;\r\n% fs_correct= 444 ; %incorrect value should cause assert to fail.\r\nfs=findSirenFrequency ( c, u, fh, fl );\r\ndelta=1 ;% One Hz plus or minus tolerance on answer \r\nassert(and( ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003e= fs_correct-delta , ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003c= fs_correct+delta   ...\r\n          ) == 1 ) \r\n      \r\n%%\r\n%T5\r\nc = 339.0047 ; u = 200    ; fh  = 6097 ;   fl =  1572;\r\nfs_correct= 2500; \r\n%fs_correct= 232 ; %incorrect value should cause assert to fail.\r\nfs=findSirenFrequency ( c, u, fh, fl );\r\ndelta=1;  % One Hz plus or minus tolerance on answer \r\nassert(and( ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003e= fs_correct-delta , ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003c= fs_correct+delta   ...\r\n          ) == 1 ) \r\n      \r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":1330792,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":30,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-11-14T02:51:12.000Z","updated_at":"2026-02-24T10:07:29.000Z","published_at":"2021-11-14T02:56:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Doppler effect is described on OpenStax University Physics at \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://openstax.org/books/university-physics-volume-1/pages/17-7-the-doppler-effect\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ehttps://openstax.org/books/university-physics-volume-1/pages/17-7-the-doppler-effect\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e and in other sources.  \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eConsider the  Doppler effect for sound waves travelling in air.  Use the equations in the OpenStax source (or equivalent information ) to model the Doppler effect. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA moving vehicle with a speed \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eu\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, having a siren frequency, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efs,\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e approaches a static (fixed)  observer and then passes the static observer.   A siren , in this context,  is also called a horn.  The vehicle motion is modelled as straight-line motion. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOne way of summarising the effect to the formula for two frequencies\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"center\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e  \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eor written in MATLAB syntax as\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efh = fs *(c/(c-u)) \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efl = fs *(c/(c+u)) \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ewhere \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efs \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eis the frequency of a siren in Hz,  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ec \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eis the  speed of sound in m/s , \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eu \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eis the speed of the moving vehicle in m/s,  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efh\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is the higher frequency in Hz as the vehicle approaches the  stationary observer and the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efl\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e the lower frequency  in Hz as the vehicle recedes from (passes) the observer. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the siren frequency, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efs\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:u/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eto the nearest Hz.\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e  The function definition is \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efs = findSirenFrequency ( c, u, fh, fl )\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example, if  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ec\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 345  m/s  ; \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eu\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e= 30.5556 m/s ;  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efh\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 877  Hz and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efl \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e=734 Hz   then \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efs\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e= 799 Hz.   Assume  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efh\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e ≥ \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efl\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ec\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u0026gt; \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eu\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61188,"title":"Compute optimal regenerative and friction brake torque blending.","description":"Electric and hybrid vehicles combine regenerative braking with traditional friction braking to maximize energy recovery while ensuring safety.\r\nGiven total braking torque demand and maximum regenerative torque capability, compute how braking effort should be split between regenerative and friction braking.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 93px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 46.5px; transform-origin: 407px 46.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eElectric and hybrid vehicles combine regenerative braking with traditional friction braking to maximize energy recovery while ensuring safety.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven total braking torque demand and maximum regenerative torque capability, compute how braking effort should be split between regenerative and friction braking.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [Tregen, Tfric] = brakeBlending(T_total, Tregen_max)\r\nTregen = 0; Tfric = 0;\r\nend\r\n","test_suite":"%%\r\nT_total = 300; Tregen_max = 200;\r\n[Tregen,Tfric] = brakeBlending(T_total,Tregen_max);\r\nassert(isequal([Tregen Tfric],[200 100]))\r\n\r\n%%\r\nT_total = 150; Tregen_max = 200;\r\n[Tregen,Tfric] = brakeBlending(T_total,Tregen_max);\r\nassert(isequal([Tregen Tfric],[150 0]))\r\n\r\n%%\r\nT_total = 0; Tregen_max = 200;\r\n[Tregen,Tfric] = brakeBlending(T_total,Tregen_max);\r\nassert(isequal([Tregen Tfric],[0 0]))\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2305225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":32,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T07:28:49.000Z","updated_at":"2026-03-31T16:49:25.000Z","published_at":"2026-02-02T07:28:49.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eElectric and hybrid vehicles combine regenerative braking with traditional friction braking to maximize energy recovery while ensuring safety.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven total braking torque demand and maximum regenerative torque capability, compute how braking effort should be split between regenerative and friction braking.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":47420,"title":"Falling on the Moon.","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 41.6px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 331.5px 20.8px; transform-origin: 331.5px 20.8px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 308.5px 20.8px; text-align: left; transform-origin: 308.5px 20.8px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eA stone of mass \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"53.5\" height=\"18\" style=\"width: 53.5px; height: 18px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e is dropped on the moon from a height \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral, STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003eh\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e. Given a gravity force \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"84.5\" height=\"18.5\" style=\"width: 84.5px; height: 18.5px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e , find the time \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral, STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003et\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e it takes to reach the ground.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function t = your_fcn_name(h)\r\n  t = [];\r\nend","test_suite":"%%\r\nh = 1.5;\r\ny_correct = 1.3608;\r\nassert(isequal(round(your_fcn_name(h),4), y_correct))\r\n%%\r\nh = 2.0;\r\ny_correct = 1.5713;\r\nassert(isequal(round(your_fcn_name(h),4), y_correct))","published":true,"deleted":false,"likes_count":3,"comments_count":5,"created_by":514092,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":52,"test_suite_updated_at":"2020-11-08T12:08:05.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-11-07T18:58:53.000Z","updated_at":"2026-02-13T18:26:21.000Z","published_at":"2020-11-07T18:58:53.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA stone of mass \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003em = 1kg\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is dropped on the moon from a height \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eh\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e. Given a gravity force \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eg = 1.62 m/s^2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e , find the time \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003et\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e it takes to reach the ground.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":49825,"title":"Angular Velocity","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven a value of velocity or a set of velocities (in a vector or matrix form) and the radius, determine the corresponding angular velocity in a circular motion.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function omega = ang_vel(v,r)\r\n  omega = alpha*v + pi*r^2;\r\nend","test_suite":"%%\r\nv=2728;\r\nr=17;\r\nv_cor=160.4706;\r\nassert(isequal(ang_vel(v,r),v_cor))\r\n%%\r\nv=[1 2 4;3 7 8];\r\nr=pi;\r\nv_cor=[0.3183 0.6366 1.2732; 0.9549 2.2282 2.5465];\r\nassert(isequal(ang_vel(v,r),v_cor))\r\n%%\r\nv=primes(19);\r\nr=sqrt(3);\r\nv_cor=[1.1547 1.7321 2.8868 4.0415 6.3509 7.5056 9.8150 10.9697];\r\nassert(isequal(ang_vel(v,r),v_cor))\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":180632,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":52,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-01-15T15:29:09.000Z","updated_at":"2026-02-19T14:19:41.000Z","published_at":"2021-01-15T15:29:09.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a value of velocity or a set of velocities (in a vector or matrix form) and the radius, determine the corresponding angular velocity in a circular motion.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":55190,"title":"Momentum Calculation","description":"A shopping cart of mass 'm1' is traveling with velocity 'u' and collides with a second shopping cart of mass 'm2.' The two shopping carts move together after the collision. Find their final velocity.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(232, 230, 227); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(232, 230, 227); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eA shopping cart of mass 'm1' is traveling with velocity 'u' and collides with a second shopping cart of mass 'm2.' The two shopping carts move together after the collision. Find their final velocity.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function v = your_fcn_name(m1, m2, u)\r\n  v = u;\r\nend","test_suite":"%%\r\nm1 = 1; m2 = 1; u = 1\r\ny_correct = 0.5;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 2; m2 = 1; u = 2\r\ny_correct = 4/3;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 2; m2 = 3; u = 4\r\ny_correct = 8/5;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 3; m2 = 5; u = 4\r\ny_correct = 1.5;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 7; m2 = 2; u = 2\r\ny_correct = 14/9;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 24; m2 = 3; u = 2\r\ny_correct = 48/27;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 5; m2 = 4; u = 4\r\ny_correct = 20/9;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 6; m2 = 3; u = 1\r\ny_correct = 2/3;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2453225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":76,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-07-13T20:36:34.000Z","updated_at":"2026-02-17T08:20:35.000Z","published_at":"2022-07-13T20:36:34.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA shopping cart of mass 'm1' is traveling with velocity 'u' and collides with a second shopping cart of mass 'm2.' The two shopping carts move together after the collision. Find their final velocity.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":45522,"title":"Electric Flux","description":"Calculate the flux passing through a surface.\r\nE is electric field, A is area.","description_html":"\u003cp\u003eCalculate the flux passing through a surface.\r\nE is electric field, A is area.\u003c/p\u003e","function_template":"function Flux = electric_fcn_flux(E,A)\r\n  Flux = ;\r\nend","test_suite":"%%\r\nE = 0;\r\nA = 10;\r\nFlux_correct = 0;\r\nassert(isequal(electric_fcn_flux(E,A),Flux_correct))\r\n\r\n%%\r\nE = 2;\r\nA = 10;\r\nFlux_correct = 20;\r\nassert(isequal(electric_fcn_flux(E,A),Flux_correct))\r\n\r\n%%\r\nE = 5;\r\nA = 10;\r\nFlux_correct = 50;\r\nassert(isequal(electric_fcn_flux(E,A),Flux_correct))\r\n\r\n%%\r\nE = 10;\r\nA = 10;\r\nFlux_correct = 100;\r\nassert(isequal(electric_fcn_flux(E,A),Flux_correct))\r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":444624,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":78,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-05-17T13:38:58.000Z","updated_at":"2026-02-10T08:26:09.000Z","published_at":"2020-05-17T13:38:58.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the flux passing through a surface. E is electric field, A is area.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":49713,"title":"Ohmic Heating","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 25.5px; transform-origin: 407.5px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 42.0083px 7.7px; transform-origin: 42.0083px 7.7px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFind Power P\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 103.475px 7.7px; transform-origin: 103.475px 7.7px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ewith Voltage V and resistance (R)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = H(V,R)\r\n  y = x;\r\nend","test_suite":"%%\r\nV= 1;R=5;\r\ny_correct = 0.2000;\r\nassert(isequal(H(V,R),y_correct))\r\n%%\r\nV= 50;R=45;\r\ny_correct =  55.5556;\r\nassert(isequal(H(V,R),y_correct))\r\n%%\r\nV= 1100;R=55;\r\ny_correct = 22000;\r\nassert(isequal(H(V,R),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":610936,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-31T03:20:57.000Z","updated_at":"2026-02-10T08:46:34.000Z","published_at":"2020-12-31T03:46:00.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind Power P\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ewith Voltage V and resistance (R)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":49830,"title":"Period of a pendulum","description":"Consider a small object hanging on a massless thread and pulled back from equilibrium at a small angle. Assuming that the pivot point is frictionless as well as no drag, determine the period of the movement of the pendulum given the length of the thread. Please use a gravitational constant of 9.8067 m/s^2.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 63px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 31.5px; transform-origin: 407px 31.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 376.5px 8px; transform-origin: 376.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eConsider a small object hanging on a massless thread and pulled back from equilibrium at a small angle. Assuming that the pivot point is frictionless as well as no drag, determine the period of the movement of the pendulum given the length of the thread. Please use a gravitational constant of 9.8067 m/s^2.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function T = pendulum(L)\r\n  T = L^(1/3)*g;\r\nend","test_suite":"%%\r\nL=10;\r\nT_corr=6.3448;\r\nassert(isequal(pendulum(L),T_corr))\r\n%%\r\nL=primes(10);\r\nT_corr=[2.8375 3.4752 4.4865 5.3084];\r\nassert(isequal(pendulum(L),T_corr))\r\n%%\r\nL=pi;\r\nT_corr=3.5563;\r\nassert(isequal(pendulum(L),T_corr))\r\n%%\r\nL=9.8067/pi^2;\r\nT_corr=2;\r\nassert(isequal(pendulum(L),T_corr))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":180632,"edited_by":223089,"edited_at":"2022-06-02T19:39:27.000Z","deleted_by":null,"deleted_at":null,"solvers_count":40,"test_suite_updated_at":"2022-06-02T19:39:27.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2021-01-15T16:08:56.000Z","updated_at":"2026-02-12T12:15:02.000Z","published_at":"2021-01-15T16:08:56.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eConsider a small object hanging on a massless thread and pulled back from equilibrium at a small angle. Assuming that the pivot point is frictionless as well as no drag, determine the period of the movement of the pendulum given the length of the thread. Please use a gravitational constant of 9.8067 m/s^2.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":8058,"title":"Kinetic Energy","description":"Given the mass m and velocity v of an object, determine its \u003chttp://en.wikipedia.org/wiki/Kinetic_energy kinetic energy\u003e.","description_html":"\u003cp\u003eGiven the mass m and velocity v of an object, determine its \u003ca href = \"http://en.wikipedia.org/wiki/Kinetic_energy\"\u003ekinetic energy\u003c/a\u003e.\u003c/p\u003e","function_template":"function y = kinetic_energy(m,v)\r\n  y = x;\r\nend","test_suite":"%%\r\nm = 20;\r\nv = 25\r\ny_correct = 6250;\r\nassert(isequal(kinetic_energy(m,v),y_correct))\r\n\r\n%%\r\nm = 1;\r\nv = 4;\r\ny_correct = 8;\r\nassert(isequal(kinetic_energy(m,v),y_correct))\r\n\r\n%%\r\nm = 6;\r\nv = 9;\r\ny_correct = 243;\r\nassert(isequal(kinetic_energy(m,v),y_correct))","published":true,"deleted":false,"likes_count":6,"comments_count":2,"created_by":33703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":388,"test_suite_updated_at":"2015-04-09T15:52:31.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2015-04-02T15:31:28.000Z","updated_at":"2026-02-11T11:51:30.000Z","published_at":"2015-04-02T15:31:27.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven the mass m and velocity v of an object, determine its\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Kinetic_energy\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ekinetic energy\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":54895,"title":"determine skid distance of car","description":"Determine the distance a car skids to a stop given initial velocity (v) and time (t).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eDetermine the distance a car skids to a stop given initial velocity (v) and time (t).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function d = skid_distance(v,t)\r\n  d = v;\r\nend","test_suite":"%%\r\nv = 22.4;\r\nt = 2.55;\r\ny_correct = 28.56;\r\ntolerance = 1e-12;\r\nassert(abs(skid_distance(v,t)-y_correct)\u003ctolerance)\r\n%%\r\nv = 26.8;\r\nt = 5.1;\r\ny_correct = 68.34;\r\ntolerance = 1e-12;\r\nassert(abs(skid_distance(v,t)-y_correct)\u003ctolerance)","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2457130,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":39,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-07-12T15:13:33.000Z","updated_at":"2026-02-12T12:28:20.000Z","published_at":"2022-07-12T15:13:33.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDetermine the distance a car skids to a stop given initial velocity (v) and time (t).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":58319,"title":"Calculate the Voltage Through a Step-Up Transformer","description":"Given a step-up transformer has a primary coil with A number loops, a secondary coil with B number loops, and a primary voltage of 12 volts. What is the secondary voltage in each transformer?","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 21px; transform-origin: 407.5px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 21px; text-align: left; transform-origin: 384.5px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven a step-up transformer has a primary coil with A number loops, a secondary coil with B number loops, and a primary voltage of 12 volts. What is the secondary voltage in each transformer?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function V_s = SecVolt(A,B)\r\n  V_s = ;\r\nend","test_suite":"%%\r\nA = 30;\r\nB = 75;\r\nassert(isequal(SecVolt(A,B),30))\r\n%%\r\nA = 20;\r\nB = 40;\r\nassert(isequal(SecVolt(A,B),24))\r\n%%\r\nA = 40;\r\nB = 90;\r\nassert(isequal(SecVolt(A,B),27))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":3227359,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":72,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-05-17T17:08:40.000Z","updated_at":"2026-02-16T11:59:58.000Z","published_at":"2023-05-17T17:08:40.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a step-up transformer has a primary coil with A number loops, a secondary coil with B number loops, and a primary voltage of 12 volts. What is the secondary voltage in each transformer?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":43065,"title":"Energy of an object","description":"Calculate the total mechanical energy of an object.\r\n\r\nTotal Energy= Potential energy + Kinetic energy\r\n\r\nP.E.=m*g*h\r\n\r\nK.E.=1/2*m*v^2\r\n\r\ng=9.8m/s^2","description_html":"\u003cp\u003eCalculate the total mechanical energy of an object.\u003c/p\u003e\u003cp\u003eTotal Energy= Potential energy + Kinetic energy\u003c/p\u003e\u003cp\u003eP.E.=m*g*h\u003c/p\u003e\u003cp\u003eK.E.=1/2*m*v^2\u003c/p\u003e\u003cp\u003eg=9.8m/s^2\u003c/p\u003e","function_template":"function y = te(m,h,v)\r\n  y = x;\r\nend","test_suite":"%%\r\nm=1;\r\nh=10;\r\nv=2;\r\ny_correct = 100;\r\nassert(isequal(te(m,h,v),y_correct))\r\n\r\n%%\r\nm=10;\r\nh=10;\r\nv=2;\r\ny_correct = 1000;\r\nassert(isequal(te(m,h,v),y_correct))\r\n\r\n%%\r\nm=1;\r\nh=10;\r\nv=20;\r\ny_correct = 298;\r\nassert(isequal(te(m,h,v),y_correct))\r\n","published":true,"deleted":false,"likes_count":8,"comments_count":0,"created_by":91311,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":458,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-05T15:51:12.000Z","updated_at":"2026-04-03T16:21:54.000Z","published_at":"2016-10-05T15:51:12.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the total mechanical energy of an object.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTotal Energy= Potential energy + Kinetic energy\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eP.E.=m*g*h\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eK.E.=1/2*m*v^2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eg=9.8m/s^2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2311,"title":"Vector Magnitude Calculator","description":"'a' is a vector that starts at the origin and ends at (x, y). Find ||a||.\r\n\r\nHint: It is as simple as \"ABC\".","description_html":"\u003cp\u003e'a' is a vector that starts at the origin and ends at (x, y). Find \u003ctt\u003e|a|\u003c/tt\u003e.\u003c/p\u003e\u003cp\u003eHint: It is as simple as \"ABC\".\u003c/p\u003e","function_template":"function m = vector_magnitude(x, y)\r\n  m = x;\r\nend","test_suite":"%%\r\nx = 5;\r\ny = 12;\r\nmm = 13;\r\nassert(isequal(vector_magnitude(x, y),mm))\r\n\r\n%%\r\nx = 3;\r\ny = 4;\r\nmm = 5;\r\nassert(isequal(vector_magnitude(x, y),mm))\r\n\r\n%%\r\nx = 12;\r\ny = 35;\r\nmm = 37;\r\nassert(isequal(vector_magnitude(x, y),mm))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":26349,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":167,"test_suite_updated_at":"2014-06-05T15:55:43.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-05-07T19:54:35.000Z","updated_at":"2026-02-18T09:28:19.000Z","published_at":"2014-05-07T19:54:35.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'a' is a vector that starts at the origin and ends at (x, y). Find\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e|a\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e|.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHint: It is as simple as \\\"ABC\\\".\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61187,"title":"Estimate brake disc temperature rise during braking.","description":"During braking, kinetic energy is converted into thermal energy, causing brake discs to heat up. Excessive temperature rise can lead to brake fade and reduced braking effectiveness.\r\nGiven braking energy absorbed by the disc, disc mass, and material heat capacity, estimate the resulting temperature increase.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 93px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 46.5px; transform-origin: 407px 46.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eDuring braking, kinetic energy is converted into thermal energy, causing brake discs to heat up. Excessive temperature rise can lead to brake fade and reduced braking effectiveness.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven braking energy absorbed by the disc, disc mass, and material heat capacity, estimate the resulting temperature increase.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function dT = brakeDiscTempRise(E, m, Cp)\r\ndT = 0;\r\nend\r\n","test_suite":"%%\r\nE = 150000; m = 7; Cp = 500;\r\ndT_correct = 42.8571;\r\nassert(abs(brakeDiscTempRise(E,m,Cp)-dT_correct) \u003c 1e-3)\r\n\r\n%%\r\nE = 100000; m = 5; Cp = 450;\r\ndT_correct = 44.4444;\r\nassert(abs(brakeDiscTempRise(E,m,Cp)-dT_correct) \u003c 1e-3)\r\n\r\n%%\r\nE = 0; m = 6; Cp = 500;\r\ndT_correct = 0;\r\nassert(isequal(brakeDiscTempRise(E,m,Cp),dT_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":37,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T07:26:30.000Z","updated_at":"2026-03-31T16:47:57.000Z","published_at":"2026-02-02T07:26:30.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDuring braking, kinetic energy is converted into thermal energy, causing brake discs to heat up. Excessive temperature rise can lead to brake fade and reduced braking effectiveness.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven braking energy absorbed by the disc, disc mass, and material heat capacity, estimate the resulting temperature increase.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":58832,"title":"Find the Peak Particle Velocity on a ETL structure","description":"PPV is a vibration parameter that can connect stress to a structure, it is measured in mm/s or mm/s-1. The higher the PPV the more stress to the structure. Common practices in power industries are to limit ground motion by specifying the maximum peak particle velocity (PPV). Electrical Tranmission Line (ETL) Structure's maximum PPV without having any damage to the structure is around 50.8mm/s.\r\nThere are many different equations for PPV, but all generally have the same variables. 2 site constants and 2 unknowns.\r\nUse this equation to calculate PPV with k \u0026 e being the default site constants:\r\nPPV = k(D/sqrt(Q) )^(-e)\r\nk = 185\r\ne = 1.2\r\nD = distance from blast to structure (m)\r\nQ = Charge of mass per delay (kg)\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 324px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 162px; transform-origin: 407.5px 162px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 42px; text-align: left; transform-origin: 384.5px 42px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ePPV is a vibration parameter that can connect stress to a structure, it is measured in mm/s or mm/s-1. The higher the PPV the more stress to the structure. Common practices in power industries are to limit ground motion by specifying the maximum peak particle velocity (PPV). Electrical Tranmission Line (ETL) Structure's maximum PPV without having any damage to the structure is around 50.8mm/s.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThere are many different equations for PPV, but all generally have the same variables. 2 site constants and 2 unknowns.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eUse this equation to calculate PPV with k \u0026amp; e being the default site constants:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ePPV = k(D/sqrt(Q) )^(-e)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ek = 185\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ee = 1.2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eD = distance from blast to structure (m)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eQ = Charge of mass per delay (kg)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = PPV(D,Q)\r\ny = ...\r\nend","test_suite":"%%\r\nD = 60\r\nQ = 500\r\ny_correct = 56.6;\r\nassert(isequal(PPV(D,Q),y_correct))\r\n%%\r\nD = 100\r\nQ = 1000\r\ny_correct = 46.5;\r\nassert(isequal(PPV(D,Q),y_correct))\r\n%%\r\nD = 200\r\nQ = 3000\r\ny_correct = 39.1;\r\nassert(isequal(PPV(D,Q),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":3,"created_by":3227359,"edited_by":3227359,"edited_at":"2023-08-09T12:12:17.000Z","deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-08-08T16:17:14.000Z","updated_at":"2026-03-02T09:14:51.000Z","published_at":"2023-08-08T16:19:19.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePPV is a vibration parameter that can connect stress to a structure, it is measured in mm/s or mm/s-1. The higher the PPV the more stress to the structure. Common practices in power industries are to limit ground motion by specifying the maximum peak particle velocity (PPV). Electrical Tranmission Line (ETL) Structure's maximum PPV without having any damage to the structure is around 50.8mm/s.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere are many different equations for PPV, but all generally have the same variables. 2 site constants and 2 unknowns.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eUse this equation to calculate PPV with k \u0026amp; e being the default site constants:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePPV = k(D/sqrt(Q) )^(-e)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ek = 185\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ee = 1.2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eD = distance from blast to structure (m)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eQ = Charge of mass per delay (kg)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":49698,"title":"Find the magnetic field around the wire","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 79.44px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 39.72px; transform-origin: 406.5px 39.72px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.48px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.24px; text-align: left; transform-origin: 383.5px 10.24px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind the magnetic field around the wire\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.48px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.24px; text-align: left; transform-origin: 383.5px 10.24px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003er=radius\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.48px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.24px; text-align: left; transform-origin: 383.5px 10.24px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eI=current\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = EF(I,r)\r\n  y = x;\r\nend","test_suite":"%%\r\nI=3;r=3\r\ny_correct =  2e-07;\r\nassert(abs(EF(I,r)-y_correct)\u003c0.00000001)\r\n%%\r\nI=2;r=5;\r\ny_correct =   8e-08;\r\nassert(abs(EF(I,r)-y_correct)\u003c0.0000001)\r\n%%\r\nI=5;r=6;\r\ny_correct =  1.66666e-07;\r\nassert(abs(EF(I,r)-y_correct)\u003c0.0000001)","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":610936,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":26,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-31T03:15:27.000Z","updated_at":"2026-02-17T09:16:02.000Z","published_at":"2020-12-31T03:43:39.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind the magnetic field around the wire\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003er=radius\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eI=current\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":2215,"title":"Power supply: 230V to 115V","description":"The problem is simple: we have a wall outlet which supplies 230V and an apparatus that requires 115V.\r\n\r\nSoftware is always cheaper than hardware (well, most of the time), so we solve this with a program, a Matlab function, to be precise.\r\n\r\nWrite a program that converts the supplied input voltage to the required output voltage.\r\n\r\n*If you like this problem, please like it (after solving).*","description_html":"\u003cp\u003eThe problem is simple: we have a wall outlet which supplies 230V and an apparatus that requires 115V.\u003c/p\u003e\u003cp\u003eSoftware is always cheaper than hardware (well, most of the time), so we solve this with a program, a Matlab function, to be precise.\u003c/p\u003e\u003cp\u003eWrite a program that converts the supplied input voltage to the required output voltage.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIf you like this problem, please like it (after solving).\u003c/b\u003e\u003c/p\u003e","function_template":"function V_out = transformer(V_in)\r\n  N_primary = 5432; % Number of windings on primary coil.\r\n  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vÊÔÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÆÆÆÆÆÆÆÆÆÆÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÖ¿  ·;¬÷²¸   ¦ÊÅÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÆÆÆÆÆÆÆÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ·  ·*42/\u0026bî^:¿ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÆÆÆÆÆÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ:´-ÊÊÊÊÊÊÖÔ^  ½ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÆÆËÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ· :ëÊÊÊÊÊʬ  PÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ   ²ÞÊÊÊÊÝ  WÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÉ    {ÊÊÊʲ ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÅ   ¹ÊÊÊÊÊ:ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊg  µÊÊÊÊËÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ8·gÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('Is this problem a hair-raiser?');\r\nend\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\n% On request of Ned Gulley, some extra testcases (for the, hopefully, stable voltage regulator within the input voltage range specified on the box).\r\nassert(isequal(transformer(173),115))\r\nassert(isequal(transformer(225),115))\r\nassert(isequal(transformer(145),115))\r\nassert(isequal(transformer(238),115))\r\nassert(isequal(transformer(163),115))\r\nassert(isequal(transformer(128),115))\r\nassert(isequal(transformer(216),115))\r\nassert(isequal(transformer(164),115))\r\nassert(isequal(transformer(136),115))\r\nassert(isequal(transformer(156),115))\r\nassert(isequal(transformer(166),115))\r\nassert(isequal(transformer(132),115))\r\nassert(isequal(transformer(162),115))\r\nassert(isequal(transformer(227),115))\r\nassert(isequal(transformer(203),115))\r\nassert(isequal(transformer(168),115))\r\nassert(isequal(transformer(174),115))\r\nassert(isequal(transformer(170),115))\r\nassert(isequal(transformer(161),115))\r\nassert(isequal(transformer(226),115))\r\nassert(isequal(transformer(232),115))\r\nassert(isequal(transformer(146),115))\r\nassert(isequal(transformer(151),115))\r\nassert(isequal(transformer(152),115))\r\nassert(isequal(transformer(193),115))\r\nassert(isequal(transformer(201),115))\r\nassert(isequal(transformer(192),115))\r\nassert(isequal(transformer(133),115))\r\nassert(isequal(transformer(137),115))\r\nassert(isequal(transformer(224),115))\r\nassert(isequal(transformer(200),115))\r\nassert(isequal(transformer(221),115))\r\nassert(isequal(transformer(160),115))\r\nassert(isequal(transformer(230),115))\r\nassert(isequal(transformer(176),115))\r\nassert(isequal(transformer(210),115))\r\nassert(isequal(transformer(159),115))\r\nassert(isequal(transformer(177),115))\r\nassert(isequal(transformer(126),115))\r\nassert(isequal(transformer(197),115))\r\nassert(isequal(transformer(141),115))\r\nassert(isequal(transformer(222),115))\r\nassert(isequal(transformer(189),115))\r\nassert(isequal(transformer(223),115))\r\nassert(isequal(transformer(140),115))\r\nassert(isequal(transformer(231),115))\r\nassert(isequal(transformer(236),115))\r\nassert(isequal(transformer(180),115))\r\nassert(isequal(transformer(191),115))\r\nassert(isequal(transformer(149),115))\r\nassert(isequal(transformer(172),115))\r\nassert(isequal(transformer(196),115))\r\nassert(isequal(transformer(135),115))\r\nassert(isequal(transformer(209),115))\r\nassert(isequal(transformer(144),115))\r\nassert(isequal(transformer(233),115))\r\nassert(isequal(transformer(215),115))\r\nassert(isequal(transformer(204),115))\r\nassert(isequal(transformer(187),115))\r\nassert(isequal(transformer(202),115))\r\nassert(isequal(transformer(217),115))\r\nassert(isequal(transformer(171),115))\r\nassert(isequal(transformer(153),115))\r\nassert(isequal(transformer(139),115))\r\nassert(isequal(transformer(148),115))\r\nassert(isequal(transformer(169),115))\r\nassert(isequal(transformer(130),115))\r\nassert(isequal(transformer(219),115))\r\nassert(isequal(transformer(206),115))\r\nassert(isequal(transformer(127),115))\r\nassert(isequal(transformer(129),115))\r\nassert(isequal(transformer(218),115))\r\nassert(isequal(transformer(220),115))\r\nassert(isequal(transformer(213),115))\r\nassert(isequal(transformer(207),115))\r\nassert(isequal(transformer(188),115))\r\nassert(isequal(transformer(179),115))\r\nassert(isequal(transformer(185),115))\r\nassert(isequal(transformer(131),115))\r\nassert(isequal(transformer(157),115))\r\nassert(isequal(transformer(143),115))\r\nassert(isequal(transformer(147),115))\r\nassert(isequal(transformer(138),115))\r\nassert(isequal(transformer(214),115))\r\nassert(isequal(transformer(178),115))\r\nassert(isequal(transformer(182),115))\r\nassert(isequal(transformer(195),115))\r\nassert(isequal(transformer(237),115))\r\nassert(isequal(transformer(155),115))\r\nassert(isequal(transformer(158),115))\r\nassert(isequal(transformer(199),115))\r\nassert(isequal(transformer(211),115))\r\nassert(isequal(transformer(228),115))\r\nassert(isequal(transformer(175),115))\r\nassert(isequal(transformer(150),115))\r\nassert(isequal(transformer(194),115))\r\nassert(isequal(transformer(134),115))\r\nassert(isequal(transformer(229),115))\r\nassert(isequal(transformer(181),115))\r\nassert(isequal(transformer(190),115))\r\nassert(isequal(transformer(165),115))\r\nassert(isequal(transformer(235),115))\r\nassert(isequal(transformer(239),115))\r\nassert(isequal(transformer(212),115))\r\nassert(isequal(transformer(208),115))\r\nassert(isequal(transformer(142),115))\r\nassert(isequal(transformer(198),115))\r\nassert(isequal(transformer(184),115))\r\nassert(isequal(transformer(240),115))\r\nassert(isequal(transformer(205),115))\r\nassert(isequal(transformer(234),115))\r\nassert(isequal(transformer(186),115))\r\nassert(isequal(transformer(183),115))\r\nassert(isequal(transformer(167),115))\r\nassert(isequal(transformer(154),115))\r\n\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":6556,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":108,"test_suite_updated_at":"2014-02-26T08:04:49.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-02-24T15:36:09.000Z","updated_at":"2026-02-18T14:03:38.000Z","published_at":"2014-02-24T15:36:09.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe problem is simple: we have a wall outlet which supplies 230V and an apparatus that requires 115V.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSoftware is always cheaper than hardware (well, most of the time), so we solve this with a program, a Matlab function, to be precise.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a program that converts the supplied input voltage to the required output voltage.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eIf you like this problem, please like it (after solving).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":56563,"title":"Compute the drag on a moving vehicle ","description":"We assume no rolling resistance, and the simple rule for Drag : , where  is the density of the fluid (assumed at 1.2 ),  is the surface of the vehicle,  is the drag coefficient and  is the velocity.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 56.8px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 28.4px; transform-origin: 407px 28.4px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 28.4px; text-align: left; transform-origin: 384px 28.4px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 197.083px 8px; transform-origin: 197.083px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWe assume no rolling resistance, and the simple rule for Drag : \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-15px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 90px; height: 35px;\" width=\"90\" height=\"35\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 24.8917px 8px; transform-origin: 24.8917px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, where \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003eρ\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 111.358px 8px; transform-origin: 111.358px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the density of the fluid (assumed at 1.2 \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 40px; height: 19.5px;\" width=\"40\" height=\"19.5\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 6.21667px 8px; transform-origin: 6.21667px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e), \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 37.5px; height: 19.5px;\" width=\"37.5\" height=\"19.5\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 90.6167px 8px; transform-origin: 90.6167px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the surface of the vehicle, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-6px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 18.5px; height: 20px;\" width=\"18.5\" height=\"20\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 83.5px 8px; transform-origin: 83.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the drag coefficient and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 44.5px; height: 18.5px;\" width=\"44.5\" height=\"18.5\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 45.375px 8px; transform-origin: 45.375px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the velocity.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function F_d = drag(S, C_d, v)\r\nrho = 0;\r\nF_d = 0;\r\nend","test_suite":"%%\r\nS = 1;\r\nC_d = 0.21;\r\nv = 10;\r\nF_correct = 12.6;\r\nassert(isequal(drag(S, C_d, v), F_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":2763543,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":44,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-11-09T21:14:22.000Z","updated_at":"2026-02-17T14:32:03.000Z","published_at":"2022-11-09T21:14:22.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWe assume no rolling resistance, and the simple rule for Drag : \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eF_d=\\\\frac{1}{2}\\\\rho S C_d v^2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e, where \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e\\\\rho\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the density of the fluid (assumed at 1.2 \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ekg/m^3\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e), \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eS [m^2]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the surface of the vehicle, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eC_d\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the drag coefficient and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ev [m/s]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the velocity.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":49850,"title":"Simple Circuit of Resistors","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 345px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 172.5px; transform-origin: 407px 172.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThe configuration of a group of resistors is described in a matrix with two rows. The first row provides the information regarding the number of resistors at each junction and the second row provides the resistance of each detector at each junction. Consider the following configuration:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 222px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 111px; text-align: left; transform-origin: 384px 111px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThe circuit_def (i.e., the matrix defining the problem) for this configuration is [1 3 2; R1 R2 R3]. Find the resultant resistance for any given configuration.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = tot_res(circuit_def)\r\n  y = circuit_def(1,:)./circuit_def(2,:);\r\nend","test_suite":"%%\r\ncircuit_def=[3 3 3 3;1 2 3 4];\r\ntot_corr=3.3333;\r\nassert(abs(tot_res(circuit_def)-tot_corr)\u003c1e-3)\r\n%%\r\ncircuit_def=[1 2 3 4;1 2 3 4];\r\ntot_corr=4;\r\nassert(abs(tot_res(circuit_def)-tot_corr)\u003c1e-3)\r\n%%\r\ncircuit_def=[11 12 3 7;4 5 3 8];\r\ntot_corr=2.92316;\r\nassert(abs(tot_res(circuit_def)-tot_corr)\u003c1e-3)\r\n%%\r\ncircuit_def=[3 3 4 4 6 7 8;3 1 1 5 9 10 11];\r\ntot_corr=7.136905;\r\nassert(abs(tot_res(circuit_def)-tot_corr)\u003c1e-3)\r\n%%\r\ncircuit_def=[2 5 3;11 2 20];\r\ntot_corr=12.56667;\r\nassert(abs(tot_res(circuit_def)-tot_corr)\u003c1e-3)\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":180632,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":25,"test_suite_updated_at":"2021-01-17T21:52:11.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2021-01-17T21:37:24.000Z","updated_at":"2026-02-26T11:54:37.000Z","published_at":"2021-01-17T21:52:11.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe configuration of a group of resistors is described in a matrix with two rows. The first row provides the information regarding the number of resistors at each junction and the second row provides the resistance of each detector at each junction. Consider the following configuration:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe circuit_def (i.e., the matrix defining the problem) for this configuration is [1 3 2; R1 R2 R3]. Find the resultant resistance for any given 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dynamic load transfer to front axle during braking.","description":"During braking, load shifts from the rear axle to the front axle. Given mass, deceleration, center of gravity height, and wheelbase, compute this dynamic load transfer ,a key factor in vehicle stability and brake force distribution.\r\n\r\nUse: g = 9.81;","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 102px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 51px; transform-origin: 407px 51px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eDuring braking, load shifts from the rear axle to the front axle. Given mass, deceleration, center of gravity height, and wheelbase, compute this dynamic load transfer ,a key factor in vehicle stability and brake force distribution.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eUse: g = 9.81;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function dW = loadTransfer(m,a,h,L)\r\ndW = 0;\r\nend\r\n","test_suite":"%%\r\nm = 1200; a = 5; h = 0.5; L = 2.5;\r\ndW_correct = 1200;\r\nassert(abs(loadTransfer(m,a,h,L)-dW_correct) \u003c 1)\r\n\r\n%%\r\nm = 1000; a = 4; h = 0.45; L = 2.6;\r\ndW_correct = 692.3;\r\nassert(abs(loadTransfer(m,a,h,L)-dW_correct) \u003c 2)\r\n\r\n%%\r\nm = 0; a = 5; h = 0.5; L = 2.5;\r\ndW_correct = 0;\r\nassert(isequal(loadTransfer(m,a,h,L),dW_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-02-02T06:29:05.000Z","deleted_by":null,"deleted_at":null,"solvers_count":34,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T06:29:00.000Z","updated_at":"2026-03-31T16:44:16.000Z","published_at":"2026-02-02T06:29:05.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDuring braking, load shifts from the rear axle to the front axle. Given mass, deceleration, center of gravity height, and wheelbase, compute this dynamic load transfer ,a key factor in vehicle stability and brake force distribution.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eUse: g = 9.81;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61119,"title":"Escape from Planet ....","description":"Given a  Planets mass M, and raduis r. Calculate the surface escape velocity and the escape velocity at height h. \r\nand the difference between the Escape velocities to 5 decimal places. \r\nG ≈ 6.67×10−11 m3⋅kg−1⋅s−2","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 81px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 408px 40.5px; transform-origin: 408px 40.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven a  Planets mass M, and raduis r. Calculate the surface escape velocity and the escape velocity at height h. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eand the difference between the Escape velocities to 5 decimal places. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003eG\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e ≈ 6.67×10−11 m3⋅kg−1⋅s−2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [ve,veh,difference] = Escape(M,r,h)\r\nve  = \r\nveh  = \r\ndifference  = \r\nend","test_suite":"%% Earth at 100km \r\nM = 5.97* 10^27 ;\r\nr =  6378000; \r\nh = 100000; \r\ny_correct = [3.53364e+05,3.50626e+05, 2.73802e+03] ;\r\ntol  = 0.00002 \r\nassert(isequal(Escape(M,r,h),y_correct) \u003c tol)\r\n\r\n%%\r\nM = 20.97* 10^27 ;\r\nr =  252378000; \r\nh = 100000000; \r\ny_correct = [1.05281e+05, 8.90989e+04,1.61823e+04]\r\ntol  = 0.00002 \r\nassert(isequal(Escape(M,r,h),y_correct) \u003c tol)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5017232,"edited_by":5017232,"edited_at":"2025-12-08T04:56:12.000Z","deleted_by":null,"deleted_at":null,"solvers_count":11,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-12-07T23:58:16.000Z","updated_at":"2026-03-04T21:20:55.000Z","published_at":"2025-12-07T23:58:16.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a  Planets mass M, and raduis r. Calculate the surface escape velocity and the escape velocity at height h. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand the difference between the Escape velocities to 5 decimal places. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eG\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e ≈ 6.67×10−11 m3⋅kg−1⋅s−2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61189,"title":"Simulate full-stop emergency braking scenario.","description":"Emergency braking events demand rapid deceleration to bring the vehicle safely to rest. Given initial vehicle speed and constant deceleration, simulate the braking process and determine the time required to reach zero velocity.\r\nYour solution should correctly handle typical braking cases and extreme boundary conditions.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 72px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 36px; transform-origin: 407px 36px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eEmergency braking events demand rapid deceleration to bring the vehicle safely to rest. Given initial vehicle speed and constant deceleration, simulate the braking process and determine the time required to reach zero velocity.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYour solution should correctly handle typical braking cases and extreme boundary conditions.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function t_stop = emergencyBrakingTime(v0,a)\r\nt_stop = 0;\r\nend\r\n","test_suite":"%%\r\nv0 = 25; a = 5;\r\nt_correct = 5;\r\nassert(abs(emergencyBrakingTime(v0,a)-t_correct) \u003c 1e-6)\r\n\r\n%%\r\nv0 = 30; a = 6;\r\nt_correct = 5;\r\nassert(abs(emergencyBrakingTime(v0,a)-t_correct) \u003c 1e-6)\r\n\r\n%%\r\nv0 = 0; a = 5;\r\nt_correct = 0;\r\nassert(isequal(emergencyBrakingTime(v0,a),t_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2305225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":32,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T07:31:11.000Z","updated_at":"2026-04-02T00:33:36.000Z","published_at":"2026-02-02T07:31:11.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEmergency braking events demand rapid deceleration to bring the vehicle safely to rest. Given initial vehicle speed and constant deceleration, simulate the braking process and determine the time required to reach zero velocity.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYour solution should correctly handle typical braking cases and extreme boundary conditions.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61180,"title":"Compute vehicle stopping distance using initial speed and constant deceleration.","description":"Given vehicle speed v (m/s) and constant deceleration a (m/s²), compute stopping distance\r\nRemember: d = v² / (2a)","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 25.5px; transform-origin: 407px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven vehicle speed \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ev\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (m/s) and constant deceleration \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ea\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (m/s²), compute stopping distance\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eRemember: d = v² / (2a)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function d = stoppingDistance(v,a)\r\nd = 0;\r\nend","test_suite":"%%\r\nv = 20; a = 5;\r\nd_correct = 40;\r\nassert(abs(stoppingDistance(v,a)-d_correct) \u003c 1e-6)\r\n\r\n%%\r\nv = 30; a = 10;\r\nd_correct = 45;\r\nassert(abs(stoppingDistance(v,a)-d_correct) \u003c 1e-6)\r\n\r\n%%\r\nv = 0; a = 5;\r\nd_correct = 0;\r\nassert(abs(stoppingDistance(v,a)-d_correct) \u003c 1e-6)\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-02-02T05:29:31.000Z","deleted_by":null,"deleted_at":null,"solvers_count":49,"test_suite_updated_at":"2026-02-02T05:29:31.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T04:56:51.000Z","updated_at":"2026-04-02T00:31:02.000Z","published_at":"2026-02-02T05:05:46.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven vehicle speed \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ev\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (m/s) and constant deceleration \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ea\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (m/s²), compute stopping distance\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember: d = v² / (2a)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48695,"title":"Laws of motion 5","description":"Calculate the force is u are given mass and acceleration.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 10.5px; transform-origin: 406.5px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.5px; text-align: left; transform-origin: 383.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 182.575px 7.81667px; transform-origin: 182.575px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCalculate the force is u are given mass and acceleration.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function F = your_fcn_name(m,a)\r\n  y = x;\r\nend","test_suite":"%%\r\nfiletext = fileread('your_fcn_name.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'regexp');\r\nassert(~illegal)\r\n\r\n%%\r\nm=1;\r\na=1;\r\ny_correct = 1;\r\nassert(isequal(your_fcn_name(m,a),y_correct))\r\n%%\r\nm=1;\r\na=10;\r\ny_correct = 10;\r\nassert(isequal(your_fcn_name(m,a),y_correct))\r\n%%\r\nm=10;\r\na=10;\r\ny_correct = 100;\r\nassert(isequal(your_fcn_name(m,a),y_correct))\r\n%%\r\nm=randi(10)*2;\r\na=1/m;\r\ny_correct = 1;\r\nassert(isequal(your_fcn_name(m,a),y_correct))\r\n","published":true,"deleted":false,"likes_count":13,"comments_count":1,"created_by":644918,"edited_by":223089,"edited_at":"2024-06-30T13:46:26.000Z","deleted_by":null,"deleted_at":null,"solvers_count":2565,"test_suite_updated_at":"2024-06-30T13:46:26.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T17:09:46.000Z","updated_at":"2026-04-03T14:12:21.000Z","published_at":"2020-12-21T17:09:46.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the force is u are given mass and acceleration.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48675,"title":"Laws of motion 1","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven initial velocity 'u', acceleration 'a' , find the final velocity of an object after time 't'.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function v = your_fcn_name(u,a,t)\r\n  v = x;\r\nend","test_suite":"%%\r\nu=1;\r\na=1;\r\nt=1;\r\n\r\ny_correct = 2;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n\r\n\r\n%%\r\n\r\nu=2;\r\na=2;\r\nt=2;\r\n\r\ny_correct = 6;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n\r\n%%%%%%\r\nu=0;\r\na=1;\r\nt=2;\r\n\r\ny_correct = 2;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n\r\n\r\n%%%\r\n\r\nu=0;\r\na=10;\r\nt=6;\r\n\r\ny_correct = 60;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":14,"comments_count":2,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2752,"test_suite_updated_at":"2020-12-21T16:34:02.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T16:28:05.000Z","updated_at":"2026-04-03T14:05:03.000Z","published_at":"2020-12-21T16:29:26.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven initial velocity 'u', acceleration 'a' , find the final velocity of an object after time 't'.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48900,"title":"Kinetic energy calculation","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eAn object with mass m moves with velocity v. Find its kinetic energy.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function KE = your_fcn_name(m,v)\r\n  y = x;\r\nend","test_suite":"%%\r\nm = 1;\r\nv=2\r\ny_correct = 2;\r\nassert(isequal(your_fcn_name(m,v),y_correct))\r\n%%\r\nm = 5;\r\nv=200\r\ny_correct = 100000;\r\nassert(isequal(your_fcn_name(m,v),y_correct))\r\n%%\r\nm = 10;\r\nv=28\r\ny_correct = 3920;\r\nassert(isequal(your_fcn_name(m,v),y_correct))\r\n%%\r\nm = 25;\r\nv=26\r\ny_correct = 8450;\r\nassert(isequal(your_fcn_name(m,v),y_correct))\r\n","published":true,"deleted":false,"likes_count":12,"comments_count":0,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2446,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T20:21:04.000Z","updated_at":"2026-04-03T13:57:10.000Z","published_at":"2020-12-21T20:21:04.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAn object with mass m moves with velocity v. Find its kinetic energy.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":49693,"title":"Find the magnetic field in sollinoid","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 10.5px; transform-origin: 407.5px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 84.425px 7.7px; transform-origin: 84.425px 7.7px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMagnetic field in sollinoid B\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = MF(N,l,I)\r\n  y = x;\r\nend","test_suite":"%%\r\nN=5;l=200;I=3;\r\ny_correct =  9.42477796076938e-08;\r\nassert(abs(MF(N,l,I)-y_correct)\u003c0.00000001)\r\n%%\r\nN=6;l=50;I=3;\r\ny_correct =    4.5238934211693e-07;\r\nassert(abs(MF(N,l,I)-y_correct)\u003c0.0000001)\r\n%%\r\nN=9;l=50;I=2;\r\ny_correct =  4.5238934211693e-07;\r\nassert(abs(MF(N,l,I)-y_correct)\u003c0.0000001)","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":610936,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":18,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-31T03:05:45.000Z","updated_at":"2026-02-17T08:28:07.000Z","published_at":"2020-12-31T03:41:31.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMagnetic field in sollinoid B\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48905,"title":"Potential energy calculation","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind the potential energy of an object with mass 'm' and height 'h'. Consider g=10 m/s^2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function PE = your_fcn_name(m,h)\r\n  y = x;\r\nend","test_suite":"%%\r\nm=10;\r\nh=10;\r\ny_correct = 1000;\r\nassert(isequal(your_fcn_name(m,h),y_correct))\r\n\r\n%%\r\nm=1;\r\nh=12;\r\ny_correct = 120;\r\nassert(isequal(your_fcn_name(m,h),y_correct))\r\n%%\r\nm=85;\r\nh=10;\r\ny_correct = 8500;\r\nassert(isequal(your_fcn_name(m,h),y_correct))\r\n","published":true,"deleted":false,"likes_count":15,"comments_count":0,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":3014,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T20:24:12.000Z","updated_at":"2026-04-03T13:57:53.000Z","published_at":"2020-12-21T20:24:12.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind the potential energy of an object with mass 'm' and height 'h'. Consider g=10 m/s^2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":360,"title":"peta to nano (x-ray)","description":"for certain x-ray radiation, given frequency in petahertz, give wavelength in nanometer, must be accurate +/- 25% ","description_html":"\u003cp\u003efor certain x-ray radiation, given frequency in petahertz, give wavelength in nanometer, must be accurate +/- 25%\u003c/p\u003e","function_template":"function nano = peta_to_nano(peta)\r\n  nano = NaN;\r\nend","test_suite":"%%\r\npeta = 40;\r\nnano_correct = 7.5;\r\nassert(isequal(round(peta_to_nano(peta)*1000)/1000,nano_correct))\r\n%%\r\npeta = 250;\r\nnano_correct = 1.2;\r\nassert(isequal(round(peta_to_nano(peta)*10)/10,nano_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":5,"created_by":166,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":189,"test_suite_updated_at":"2012-02-19T23:42:51.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-02-19T21:52:34.000Z","updated_at":"2026-03-05T15:59:58.000Z","published_at":"2012-02-19T23:50:23.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003efor certain x-ray radiation, given frequency in petahertz, give wavelength in nanometer, must be accurate +/- 25%\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61186,"title":"Compute optimal front–rear brake force distribution.","description":"Modern braking systems dynamically distribute braking forces between front and rear axles to maintain stability, reduce stopping distance, and prevent wheel lock.\r\nGiven total braking demand and axle load distribution, compute the optimal front and rear brake force allocation that preserves balance and traction.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 93px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 46.5px; transform-origin: 407px 46.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eModern braking systems dynamically distribute braking forces between front and rear axles to maintain stability, reduce stopping distance, and prevent wheel lock.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven total braking demand and axle load distribution, compute the optimal front and rear brake force allocation that preserves balance and traction.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [Ff, Fr] = brakeDistribution(F_total, front_ratio)\r\nFf = 0; Fr = 0;\r\nend\r\n","test_suite":"%%\r\nF_total = 6000; front_ratio = 0.6;\r\n[Ff,Fr] = brakeDistribution(F_total,front_ratio);\r\nassert(isequal([Ff Fr],[3600 2400]))\r\n\r\n%%\r\nF_total = 8000; front_ratio = 0.7;\r\n[Ff,Fr] = brakeDistribution(F_total,front_ratio);\r\nassert(isequal([Ff Fr],[5600 2400]))\r\n\r\n%%\r\nF_total = 0; front_ratio = 0.6;\r\n[Ff,Fr] = brakeDistribution(F_total,front_ratio);\r\nassert(isequal([Ff Fr],[0 0]))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-02-02T06:39:17.000Z","deleted_by":null,"deleted_at":null,"solvers_count":30,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T06:39:14.000Z","updated_at":"2026-03-31T16:46:35.000Z","published_at":"2026-02-02T06:39:17.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eModern braking systems dynamically distribute braking forces between front and rear axles to maintain stability, reduce stopping distance, and prevent wheel lock.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven total braking demand and axle load distribution, compute the optimal front and rear brake force allocation that preserves balance and traction.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48680,"title":"Laws of motion 2","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eWith the initial speed 'u', acceleration 'a', find the distance travelled by an object in 't' secods.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s = your_fcn_name(u,a,t)\r\n  y = x;\r\nend","test_suite":"%%\r\nu=1;\r\na=1;\r\nt=2\r\ny_correct = 4;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n%%\r\nu=0;\r\na=2;\r\nt=2\r\ny_correct = 4;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n%%\r\nu=54;\r\na=1;\r\nt=20\r\ny_correct = 1280;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n%%\r\nu=1;\r\na=2;\r\nt=1\r\ny_correct = 2;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))","published":true,"deleted":false,"likes_count":12,"comments_count":1,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2533,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T16:47:29.000Z","updated_at":"2026-04-03T14:06:20.000Z","published_at":"2020-12-21T16:47:29.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWith the initial speed 'u', acceleration 'a', find the distance travelled by an object in 't' secods.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48910,"title":"Total energy ","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eA bird of mass 'm' is flying with a velocity 'v' at an height 'h'. FInd it's total energy. (g=10)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function E = your_fcn_name(m,v,h)\r\n  y = x;\r\nend","test_suite":"%%\r\nm=2;\r\nv=2;\r\nh=2;\r\ny_correct = 44;\r\nassert(isequal(your_fcn_name(m,v,h),y_correct))\r\n%%\r\nm=2;\r\nv=4;\r\nh=6;\r\ny_correct = 136;\r\nassert(isequal(your_fcn_name(m,v,h),y_correct))\r\n%%\r\nm=2;\r\nv=4;\r\nh=40;\r\ny_correct = 816;\r\nassert(isequal(your_fcn_name(m,v,h),y_correct))\r\n%%\r\nm=2;\r\nv=6;\r\nh=22;\r\ny_correct = 476;\r\nassert(isequal(your_fcn_name(m,v,h),y_correct))\r\n","published":true,"deleted":false,"likes_count":25,"comments_count":5,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2422,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T20:29:04.000Z","updated_at":"2026-04-03T13:59:35.000Z","published_at":"2020-12-21T20:29:04.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA bird of mass 'm' is flying with a velocity 'v' at an height 'h'. FInd it's total energy. (g=10)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":1116,"title":"Calculate the height of an object dropped from the sky","description":"Assume that an object is dropped from 1000 meters above the surface of the earth at time t=0.  The object is dropped such that the initial velocity and acceleration are both zero.\r\n\r\nWrite a function to determine the height, h, of the object at any time, t, where h=0 is the surface of the earth. Assume the acceleration due to gravity is constant 9.8 m/s^2.  Also, assume that before the object is dropped (negative t) it is being held at a constant height of 1000 meters.  Finally, assume that after the object hits the ground it remains at h=0. ","description_html":"\u003cp\u003eAssume that an object is dropped from 1000 meters above the surface of the earth at time t=0.  The object is dropped such that the initial velocity and acceleration are both zero.\u003c/p\u003e\u003cp\u003eWrite a function to determine the height, h, of the object at any time, t, where h=0 is the surface of the earth. Assume the acceleration due to gravity is constant 9.8 m/s^2.  Also, assume that before the object is dropped (negative t) it is being held at a constant height of 1000 meters.  Finally, assume that after the object hits the ground it remains at h=0.\u003c/p\u003e","function_template":"function h = height_of_object_at_time(t)\r\n  h = t;\r\nend","test_suite":"%%\r\nt = -1;\r\nh_correct = 1000;\r\nassert(abs(height_of_object_at_time(t)-h_correct)\u003c0.1)\r\n%%\r\nt = 0;\r\nh_correct = 1000;\r\nassert(abs(height_of_object_at_time(t)-h_correct)\u003c0.1)\r\n%%\r\nt = 1;\r\nh_correct = 995.1;\r\nassert(abs(height_of_object_at_time(t)-h_correct)\u003c0.1)\r\n%%\r\nt = 10;\r\nh_correct = 510;\r\nassert(abs(height_of_object_at_time(t)-h_correct)\u003c0.1)\r\n%%\r\nt = 15;\r\nh_correct = 0;\r\nassert(abs(height_of_object_at_time(t)-h_correct)\u003c0.1)\r\n","published":true,"deleted":false,"likes_count":6,"comments_count":2,"created_by":9156,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":284,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-12-12T04:04:57.000Z","updated_at":"2026-03-09T20:36:56.000Z","published_at":"2012-12-12T04:04:57.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAssume that an object is dropped from 1000 meters above the surface of the earth at time t=0. The object is dropped such that the initial velocity and acceleration are both zero.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function to determine the height, h, of the object at any time, t, where h=0 is the surface of the earth. Assume the acceleration due to gravity is constant 9.8 m/s^2. Also, assume that before the object is dropped (negative t) it is being held at a constant height of 1000 meters. Finally, assume that after the object hits the ground it remains at h=0.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":48700,"title":"Laws of motion 6","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind the force required to bring and object of mass 'm' moving with velocity 'v' to rest, in t seconds.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function f = your_fcn_name(m,v,t)\r\n  y = x;\r\nend","test_suite":"%%\r\nm=1;\r\nv=1;\r\nt=1;\r\ny_correct = 1;\r\nassert(isequal(your_fcn_name(m,v,t),y_correct))\r\n\r\n%%\r\nm=4;\r\nv=7;\r\nt=2;\r\ny_correct = 14;\r\nassert(isequal(your_fcn_name(m,v,t),y_correct))\r\n\r\n%%\r\nm=6;\r\nv=19;\r\nt=2;\r\ny_correct = 57;\r\nassert(isequal(your_fcn_name(m,v,t),y_correct))\r\n","published":true,"deleted":false,"likes_count":42,"comments_count":22,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":3374,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T17:21:03.000Z","updated_at":"2026-04-03T14:14:31.000Z","published_at":"2020-12-21T17:21:03.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind the force required to bring and object of mass 'm' moving with velocity 'v' to rest, in t seconds.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48070,"title":"Center of Mass(es) in 3D Space","description":"Given a matrix of format [x1,y1,z1,m1; x2,y2,z2,m2 . . .], return the center of mass of all listed points in 3d space [xc,yc,zc]. Return pt_com = 'Bad Data' if any value for mass is negative\r\nInspired by: http://hyperphysics.phy-astr.gsu.edu/hbase/cm.html","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 72px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 36px; transform-origin: 407px 36px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 383.5px 8px; transform-origin: 383.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven a matrix of format [x1,y1,z1,m1; x2,y2,z2,m2 . . .], return the center of mass of all listed points in 3d space [xc,yc,zc]. Return pt_com = 'Bad Data' if any value for mass is negative\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 38.5px 8px; transform-origin: 38.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eInspired by: \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ehttp://hyperphysics.phy-astr.gsu.edu/hbase/cm.html\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function pt_com = com_finder(x)\r\n  pt_com = x;\r\nend","test_suite":"%%\r\nx = [10    4    12    65\r\n     3     5     8     6\r\n     7     2    13    11\r\n    10     1     6    32\r\n     8     5     2    77\r\n     4     6     9     6\r\n     4     6    15     8\r\n     7     1     6    38\r\n     6     3     8    44\r\n     2     1     1    68];\r\ny_correct = [6.7690,2.9606,6.0254];\r\nTOL = 1e-3;\r\nassert(all(abs(y_correct-com_finder(x))\u003c=TOL))\r\n\r\n%%\r\nx = [10    4    12    65\r\n     3     5     8     6\r\n     7     2    13    11\r\n    10     1     6    32\r\n     8     5     2    77\r\n     4     6     9    -6\r\n     4     6    15     8\r\n     7     1     6    38\r\n     6     3     8    44\r\n     2     1     1    68];\r\ny_correct = [6.7690,2.9606,6.0254];\r\nTOL = 1e-3;\r\nassert(isequal(com_finder(x),'Bad Data'))\r\n\r\n%%\r\n\r\nx = [-47   -41    -3    47\r\n      -3  -121    -4    75\r\n     -34   -68    -4   402\r\n     -12  -137    -3   555\r\n      -1  -106    -4   256\r\n     -29  -157    -1   163\r\n     -83  -106    -6   646\r\n      -9   -55    -2   212\r\n     -56  -149    -2   434\r\n     -65  -157    -3   431\r\n     -69  -162    -1   693\r\n     -42  -153    -6   607\r\n     -57   -16    -4   520\r\n     -25   -42    -3   160\r\n    -100  -151    -1   413\r\n     -21   -51    -3   415\r\n     -99   -29    -4   290\r\n     -45   -63    -1   534\r\n     -20  -135    -2   550\r\n     -29  -134    -3    19\r\n      -4  -178    -6   179\r\n      -6   -72    -3   111\r\n     -64   -60    -3    24\r\n     -79  -100    -2   401\r\n     -45  -200    -6   391\r\n     -98  -129    -5   111\r\n     -52   -64    -5   424\r\n     -50   -47    -2   324\r\n     -87  -176    -6   205\r\n     -52   -49    -6   487\r\n     -51  -200    -6   656\r\n     -61   -69    -5   544\r\n     -13  -153    -5   114\r\n     -21    -2    -1   661\r\n     -81  -159    -4   519\r\n     -33    -9    -5   699\r\n     -23   -42    -4    28\r\n      -7   -34    -3   332\r\n     -93  -140    -1   157\r\n     -30   -80    -1   191\r\n     -15  -124    -6   605\r\n     -72  -118    -1    94\r\n      -5  -127    -6   385\r\n     -43  -190    -6   533\r\n     -33  -191    -1   104\r\n     -19   -56    -2   548\r\n     -58   -18    -4   354\r\n     -65  -182    -3   228\r\n     -93  -131    -4   644\r\n     -11  -184    -5   107\r\n     -46   -54    -1   459\r\n      -5  -100    -4   249\r\n     -44   -28    -4   278\r\n     -81   -18    -1   458\r\n     -51   -39    -1   318\r\n     -97   -26    -6    59\r\n      -4  -134    -5   159\r\n      -4  -167    -2   625\r\n      -9  -144    -2   279\r\n     -52  -138    -1    75\r\n      -2  -156    -6   183\r\n     -48  -173    -5   215\r\n    -100   -15    -5 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   -77  -107    -1   201\r\n     -94   -48    -4   303\r\n     -85   -96    -1   101\r\n     -22   -30    -4   118\r\n      -7   -87    -1   512\r\n     -38  -132    -3   136\r\n     -77  -179    -2   298\r\n     -70  -122    -6   435\r\n     -84  -107    -1   364\r\n     -54   -62    -6   260\r\n      -9  -106    -4   567\r\n     -18  -104    -2   165\r\n     -12   -86    -5   523\r\n     -51   -25    -6   374\r\n     -45   -47    -6   139\r\n     -68   -85    -4   658\r\n     -39   -40    -1   407\r\n     -86  -148    -4   176\r\n     -45   -99    -4   500\r\n     -72   -93    -1   252\r\n     -13   -98    -2   361\r\n     -48   -24    -4   559\r\n     -90   -72    -2   605\r\n     -89    -6    -5   440\r\n     -94   -66    -2   237\r\n     -37  -166    -6   422\r\n     -91    -9    -4   217\r\n     -88  -120    -2    57\r\n     -29  -116    -1   457\r\n      -7  -115    -2   591\r\n     -23  -195    -3   232\r\n     -34  -102    -3   131\r\n     -84  -123    -4   572\r\n     -25   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 624\r\n      -9   -17    -2   327\r\n     -81  -188    -6   226\r\n     -60   -90    -6   129\r\n     -10  -150    -3   396\r\n     -42  -109    -3   131\r\n     -73  -161    -4   308\r\n     -53    -9    -6     2\r\n     -96  -106    -6   459\r\n     -78   -17    -1   253\r\n     -61  -187    -5   524\r\n     -61   -54    -5   120\r\n     -84   -58    -2   317\r\n     -42   -71    -1   675\r\n     -44   -80    -5   560\r\n     -24  -131    -6   308\r\n     -30   -62    -3   648\r\n     -67   -47    -6   529\r\n     -39  -120    -5   453\r\n     -34  -104    -1   203\r\n      -3  -109    -3   327\r\n     -79   -28    -1   222\r\n     -43  -169    -6    15\r\n     -32   -66    -4   529\r\n     -87   -22    -1   584\r\n     -44   -76    -5   308\r\n     -53  -126    -5    48\r\n     -62   -80    -5   648\r\n     -44   -68    -5   104\r\n     -33   -38    -6   188\r\n     -46   -25    -6    29\r\n     -23  -148    -3   103\r\n     -98  -200    -4   106\r\n     -39   -94    -6   397\r\n     -77   -72    -2   125\r\n      -1   -64    -2   560\r\n     -89  -161    -3   673\r\n     -91  -198    -3   526];\r\ny_correct = [-48.2024,-92.6248,-3.6100];\r\nTOL = 1e-3;\r\nassert(all(abs(y_correct-com_finder(x))\u003c=TOL))\r\n\r\n%%\r\nx = [(0:5:500)',(0:6:600)',(0:7:700)',(0:1:100)'];\r\ny_correct = [335.0000,402.0000,469.0000];\r\nTOL = 1e-3;\r\nassert(all(abs(y_correct-com_finder(x))\u003c=TOL))\r\n\r\n%%\r\nx = [(0:-5:-500)',(0:6:600)',(0:-7:-700)',(0:8:800)'];\r\ny_correct = [-335.0000,402.0000,-469.0000];\r\nTOL = 1e-3;\r\nassert(all(abs(y_correct-com_finder(x))\u003c=TOL))\r\n\r\n%%\r\nx = circshift(spiral(4),2,2)-2;\r\nassert(isequal(com_finder(x),'Bad Data'))\r\n\r\n%%\r\nid = randi([7 11]);\r\nx = randi(100,id,4);\r\nx(id,4) = -x(id,4);\r\nassert(isequal(com_finder(x),'Bad Data'))\r\n\r\n%%\r\nx = [zeros(17,3) (1:17)'];\r\ny_correct = zeros(1,3);\r\nTOL = 1e-3;\r\nassert(all(abs(y_correct-com_finder(x))\u003c=TOL))\r\n\r\n\r\n%%\r\n%Cheating is bad\r\nfunctions={'!','feval','eval','str2func','str2num','regex','system','dos','unix','perl','assert','fopen','write','save','setenv','path','please'};\r\nassessFunctionAbsence(functions, 'FileName', 'com_finder.m');\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":728283,"edited_by":223089,"edited_at":"2023-02-02T12:44:18.000Z","deleted_by":null,"deleted_at":null,"solvers_count":17,"test_suite_updated_at":"2023-02-02T12:44:18.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-17T20:58:08.000Z","updated_at":"2026-03-05T14:22:01.000Z","published_at":"2020-12-18T16:06:36.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a matrix of format [x1,y1,z1,m1; x2,y2,z2,m2 . . .], return the center of mass of all listed points in 3d space [xc,yc,zc]. Return pt_com = 'Bad Data' if any value for mass is negative\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInspired by: \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ehttp://hyperphysics.phy-astr.gsu.edu/hbase/cm.html\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":561,"title":"Find the jerk","description":"No, it's not the author of this problem...\r\n\r\nJerk is the rate of change in acceleration over time of an object.  So, if given the position of an object over time in the form of a 1-by-N vector, return the indices i where there is nonzero jerk.  \r\n\r\nSuper rad bonus hint: The signal you need to find the jerk of will be given by the variable sig, created with the commands \r\n\r\n  h = 0.065; % stepsize\r\n  t = -10:h:10;\r\n  sigCoefs = 2*rand(1,3)-1;\r\n  sig = polyval(sigCoefs,t);\r\n  breakPoint = randi(length(sig)-2)+1;\r\n  sig(breakPoint) = (1.01)*sig(breakPoint); % this creates a nonzero jerk\r\n \r\nCheck the signal visually with\r\n\r\n  plot(t,sig,'k.-')\r\n\r\nNow, using just sig, determine breakPoint.\r\n ","description_html":"\u003cp\u003eNo, it's not the author of this problem...\u003c/p\u003e\u003cp\u003eJerk is the rate of change in acceleration over time of an object.  So, if given the position of an object over time in the form of a 1-by-N vector, return the indices i where there is nonzero jerk.\u003c/p\u003e\u003cp\u003eSuper rad bonus hint: The signal you need to find the jerk of will be given by the variable sig, created with the commands\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eh = 0.065; % stepsize\r\nt = -10:h:10;\r\nsigCoefs = 2*rand(1,3)-1;\r\nsig = polyval(sigCoefs,t);\r\nbreakPoint = randi(length(sig)-2)+1;\r\nsig(breakPoint) = (1.01)*sig(breakPoint); % this creates a nonzero jerk\r\n\u003c/pre\u003e\u003cp\u003eCheck the signal visually with\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eplot(t,sig,'k.-')\r\n\u003c/pre\u003e\u003cp\u003eNow, using just sig, determine breakPoint.\u003c/p\u003e","function_template":"function idx = findAJerk(sig)\r\n  idx = find(sig\u003e0);\r\nend","test_suite":"%% \r\n\r\n  h = 0.065; % stepsize\r\n  t = -10:h:10;\r\n\r\nfor tr = 1:1000\r\n  sigCoefs = 2*rand(1,3)-1;\r\n  sig = polyval(sigCoefs,t);\r\n  breakPoint = randi(length(sig)-2)+1;\r\n  sig(breakPoint) = (1.01)*sig(breakPoint);\r\n  assert(any(abs(findAJerk(sig) - breakPoint)\u003c=6)) % extra wide window out of kindness\r\nend\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":4,"created_by":2688,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":73,"test_suite_updated_at":"2012-04-07T16:14:29.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-04-07T03:32:53.000Z","updated_at":"2026-01-31T12:36:27.000Z","published_at":"2012-04-07T03:37:20.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNo, it's not the author of this problem...\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eJerk is the rate of change in acceleration over time of an object. So, if given the position of an object over time in the form of a 1-by-N vector, return the indices i where there is nonzero jerk.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSuper rad bonus hint: The signal you need to find the jerk of will be given by the variable sig, created with the commands\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[h = 0.065; % stepsize\\nt = -10:h:10;\\nsigCoefs = 2*rand(1,3)-1;\\nsig = polyval(sigCoefs,t);\\nbreakPoint = randi(length(sig)-2)+1;\\nsig(breakPoint) = (1.01)*sig(breakPoint); % this creates a nonzero jerk]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCheck the signal visually with\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[plot(t,sig,'k.-')]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNow, using just sig, determine breakPoint.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1280,"title":"Elastic Collision 001: 1-D","description":"Elastic Collision of two particles. \r\n\u003chttp://en.wikipedia.org/wiki/Elastic_collision wiki Elastic Collision\u003e\r\n\r\nSolve Conservation of Momentum and Kinetic Energy Equations for a point elastic collision.\r\n\r\n  m1*u1+m2*u2=m1*v1+m2*v2\r\n  m1*u1^2+m2*u2^2=m1*v1^2+m2*v2^2\r\n\r\nElastic Collision Gifs from wikipedia.   [used  \u003c \u003c copy image location \u003e \u003e]\r\n\r\n\u003c\u003chttp://upload.wikimedia.org/wikipedia/commons/c/c6/Elastischer_sto%C3%9F.gif\u003e\u003e\r\n\r\n\u003c\u003chttp://upload.wikimedia.org/wikipedia/commons/d/d2/Elastischer_sto%C3%9F2.gif\u003e\u003e\r\n\r\nGiven [m1,u1,m2,u2] solve for v1 and v2 under ideal elastic collision conditions.\r\n\r\n*Input:* [10, 1, 10, 0]\r\n\r\n*Output:* [0 1]  v1 and v2\r\n\r\n*Future:* 2-D Elastic equal masses, 2-D Elastic equal masses with find contact, Relativistic Elastic, and 3-D Elastic Equal Masses ","description_html":"\u003cdiv style = \"text-align: start; line-height: 20px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: normal; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"display: block; min-width: 0px; padding-top: 0px; transform-origin: 332px 241.5px; vertical-align: baseline; perspective-origin: 332px 241.5px; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eElastic Collision of two particles. \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://en.wikipedia.org/wiki/Elastic_collision\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ewiki Elastic Collision\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eSolve Conservation of Momentum and Kinetic Energy Equations for a point elastic collision.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-bottom: 10px; margin-left: 3px; margin-right: 3px; margin-top: 10px; transform-origin: 329px 20px; perspective-origin: 329px 20px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-height: 18px; padding-left: 4px; transform-origin: 329px 10px; white-space: nowrap; perspective-origin: 329px 10px; \"\u003e\u003cspan style=\"border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-right: 45px; min-height: 0px; padding-left: 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; perspective-origin: 0px 0px; margin-right: 45px; \"\u003e\u003cspan style=\"margin-right: 0px; \"\u003em1*u1+m2*u2=m1*v1+m2*v2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-height: 18px; padding-left: 4px; transform-origin: 329px 10px; white-space: nowrap; perspective-origin: 329px 10px; \"\u003e\u003cspan style=\"border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-right: 45px; min-height: 0px; padding-left: 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; perspective-origin: 0px 0px; margin-right: 45px; \"\u003e\u003cspan style=\"margin-right: 0px; \"\u003em1*u1^2+m2*u2^2=m1*v1^2+m2*v2^2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 10px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eElastic Collision Gifs from wikipedia. [used \u0026lt; \u0026lt; copy image location \u0026gt; \u0026gt;]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: center; transform-origin: 309px 33px; white-space: pre-wrap; perspective-origin: 309px 33px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" 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\" 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\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven [m1,u1,m2,u2] solve for v1 and v2 under ideal elastic collision conditions.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: bold; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e [10, 1, 10, 0]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: bold; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e [0 1] v1 and v2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 21px; white-space: pre-wrap; perspective-origin: 309px 21px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: bold; \"\u003eFuture:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e 2-D Elastic equal masses, 2-D Elastic equal masses with find contact, Relativistic Elastic, and 3-D Elastic Equal Masses\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [v1 v2]=OneD_Elastic(m1,u1,m2,u2)\r\n\r\n v1=0;\r\n \r\n v2=0;\r\n\r\n\r\nend","test_suite":"m1=3;u1=4;m2=5;u2=-6;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[-8.5 1.5]))\u003c.01)\r\n\r\n%%\r\n\r\nm1=2;u1=4;m2=2;u2=0;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[0 4]))\u003c.01)\r\n\r\n%%\r\n\r\nm1=6;u1=4;m2=6;u2=2;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[2 4]))\u003c.01)\r\n\r\n%%\r\n\r\nm1=6;u1=4;m2=3;u2=2;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[2.6667 4.6667]))\u003c.01)\r\n\r\n%%\r\n\r\nm1=3;u1=6;m2=3;u2=-6;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[-6 6]))\u003c.01)\r\n\r\n%%\r\n\r\nm1=1;u1=100;m2=100;u2=0;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[-98.0198 1.9802]))\u003c.01)\r\n\r\n%%\r\n\r\nm1=6;u1=-4;m2=4;u2=-6;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[-5.6 -3.6]))\u003c.01)\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":3,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":73,"test_suite_updated_at":"2020-09-28T20:12:24.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-02-19T04:35:34.000Z","updated_at":"2026-02-13T20:05:06.000Z","published_at":"2013-02-19T05:18:20.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eElastic Collision of two particles. \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Elastic_collision\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ewiki Elastic Collision\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSolve Conservation of Momentum and Kinetic Energy Equations for a point elastic collision.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[m1*u1+m2*u2=m1*v1+m2*v2\\nm1*u1^2+m2*u2^2=m1*v1^2+m2*v2^2]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eElastic Collision Gifs from wikipedia. [used \u0026lt; \u0026lt; copy image location \u0026gt; \u0026gt;]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"center\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"center\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven [m1,u1,m2,u2] solve for v1 and v2 under ideal elastic collision conditions.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e [10, 1, 10, 0]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e [0 1] v1 and v2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eFuture:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e 2-D Elastic equal masses, 2-D Elastic equal masses with find contact, Relativistic Elastic, and 3-D Elastic Equal 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telescope","description":"Two grandkids Dorothy and Benjamin are sharing a telescope made by their grandpa, who used an old lens of spectacles as the objective. This objective lens has power of p diopter. Dorothy definitively watches a doghouse at distance d meters. Benjamin basically watches a birdhouse at distance b meters. After watching the doghouse, how much shift of the eyepiece in mm is necessary to watch the birdhouse? Please give a general solution, the test suite may be more extensive later.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 105px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 52.5px; transform-origin: 407px 52.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 52.5px; text-align: left; transform-origin: 384px 52.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 383.5px 8px; transform-origin: 383.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTwo grandkids Dorothy and Benjamin are sharing a telescope made by their grandpa, who used an old lens of spectacles as the objective. This objective lens has power of p diopter. Dorothy definitively watches a doghouse at distance d meters. Benjamin basically watches a birdhouse at distance b meters. After watching the doghouse, how much shift of the eyepiece in mm is necessary to watch the birdhouse? Please give a general solution, the test suite may be more extensive later.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function mm = telescope(d,b,p)\r\n% diopter = 1/focal_length_meter = 1/object_distance + 1/image_distance\r\nmm=1000*meter;\r\nend","test_suite":"%%\r\nfiletext = fileread('telescope.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'regexp') || ...\r\n          contains(filetext, 'switch') || contains(filetext, 'elseif'); \r\nassert(~illegal)\r\n\r\n%%\r\nd=200; b=100; p=0.5;\r\nmm = telescope(d,b,p)\r\nmm_correct = 21;\r\nassert(abs(round(mm) - mm_correct)\u003c1000*eps)\r\n\r\n%%\r\nd=100; b=200; p=0.5;\r\nmm = telescope(d,b,p)\r\nmm_correct = 21;\r\nassert(abs(round(abs(mm)) - mm_correct)\u003c1000*eps)\r\n\r\n%%\r\nd=100; b=100; p=0.5;\r\nmm = telescope(d,b,p)\r\nmm_correct = 0;\r\nassert(round(mm) == mm_correct)\r\n\r\n%%\r\nd=51; b=26; p=1;\r\nmm = telescope(d,b,p)\r\nmm_correct = 20;\r\nassert(round(mm) == mm_correct)\r\n\r\n%%\r\nd=4004; b=8; p=0.25;\r\nmm = telescope(d,b,p)\r\nmm_correct = d-b;\r\nassert(round(mm) == mm_correct)\r\n\r\n%%\r\nd=255; b=55; p=0.2;\r\nmm = telescope(d,b,p)\r\nmm_correct = (d-b)*p*10;\r\nassert(abs(mm - mm_correct)\u003c1e-4)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":3,"created_by":166,"edited_by":223089,"edited_at":"2023-01-07T06:15:33.000Z","deleted_by":null,"deleted_at":null,"solvers_count":26,"test_suite_updated_at":"2023-01-07T06:15:33.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-03-04T22:25:38.000Z","updated_at":"2025-12-12T09:35:32.000Z","published_at":"2012-03-05T20:14:39.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTwo grandkids Dorothy and Benjamin are sharing a telescope made by their grandpa, who used an old lens of spectacles as the objective. This objective lens has power of p diopter. Dorothy definitively watches a doghouse at distance d meters. Benjamin basically watches a birdhouse at distance b meters. After watching the doghouse, how much shift of the eyepiece in mm is necessary to watch the birdhouse? Please give a general solution, the test suite may be more extensive later.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48690,"title":"Laws of motion 4","description":"Given the initial velocity 'u', final velocity 'v' and acceleration 'a', find the distance travelled.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 284.5px 8px; transform-origin: 284.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven the initial velocity 'u', final velocity 'v' and acceleration 'a', find the distance travelled.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s = your_fcn_name(u,v,a)\r\n  y = x;\r\nend","test_suite":"%%\r\nu=0\r\nv=1;\r\na=1;\r\ny_correct = 0.5;\r\nassert(isequal(your_fcn_name(u,v,a),y_correct))\r\n\r\n%%\r\nu=0\r\nv=10;\r\na=1;\r\ny_correct = 50;\r\nassert(isequal(your_fcn_name(u,v,a),y_correct))\r\n\r\n%%\r\nu=20\r\nv=100;\r\na=1;\r\ny_correct = 4800;\r\nassert(isequal(your_fcn_name(u,v,a),y_correct))\r\n","published":true,"deleted":false,"likes_count":10,"comments_count":5,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2501,"test_suite_updated_at":"2021-02-01T10:35:57.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T17:03:05.000Z","updated_at":"2026-04-03T14:11:33.000Z","published_at":"2020-12-21T17:03:05.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven the initial velocity 'u', final velocity 'v' and acceleration 'a', find the distance travelled.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":369,"title":"Basic electricity in a dry situation","description":"\u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \r\n\r\nThis is a very hypothetical situation between two individuals in a very dry atmosphere. \r\n\r\nHe came running in rubber boots when she was combing her hair. \r\n\r\nAround N number of electrons moved from one person to the other upon contact. \r\n\r\nWhat was the voltage between them before the contact? \r\n\r\nAssume it is a simple RC type electrical circuit with equivalent capacitance of about 16 pico farads. \r\n\r\nPlease assume that every electron carries about 160 zepto coulombs.\r\n\r\nFor more info on capacitors: \u003chttps://en.wikipedia.org/wiki/Capacitor\u003e","description_html":"\u003cp\u003e\u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889\u003c/p\u003e\u003cp\u003eThis is a very hypothetical situation between two individuals in a very dry atmosphere.\u003c/p\u003e\u003cp\u003eHe came running in rubber boots when she was combing her hair.\u003c/p\u003e\u003cp\u003eAround N number of electrons moved from one person to the other upon contact.\u003c/p\u003e\u003cp\u003eWhat was the voltage between them before the contact?\u003c/p\u003e\u003cp\u003eAssume it is a simple RC type electrical circuit with equivalent capacitance of about 16 pico farads.\u003c/p\u003e\u003cp\u003ePlease assume that every electron carries about 160 zepto coulombs.\u003c/p\u003e\u003cp\u003eFor more info on capacitors: \u003ca href = \"https://en.wikipedia.org/wiki/Capacitor\"\u003ehttps://en.wikipedia.org/wiki/Capacitor\u003c/a\u003e\u003c/p\u003e","function_template":"function V = volts(N)\r\n  V = 10000;\r\nend","test_suite":"%%\r\nN = 10^10;\r\nV = 150;\r\nassert(volts(N)\u003eV/pi)\r\n%%\r\nN = 10^11;\r\nV = 700;\r\nassert(volts(N)\u003cV*pi)\r\n%%\r\nN = 10^12;\r\nV = 10000;\r\nassert(volts(N)\u003eV/sqrt(pi))\r\n","published":true,"deleted":false,"likes_count":8,"comments_count":4,"created_by":166,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":595,"test_suite_updated_at":"2012-02-20T20:05:18.000Z","rescore_all_solutions":false,"group_id":34,"created_at":"2012-02-20T20:05:18.000Z","updated_at":"2026-03-18T13:23:56.000Z","published_at":"2017-10-16T01:45:05.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is a very hypothetical situation between two individuals in a very dry atmosphere.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHe came running in rubber boots when she was combing her hair.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAround N number of electrons moved from one person to the other upon contact.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWhat was the voltage between them before the contact?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAssume it is a simple RC type electrical circuit with equivalent capacitance of about 16 pico farads.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePlease assume that every electron carries about 160 zepto coulombs.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor more info on capacitors:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://en.wikipedia.org/wiki/Capacitor\\\"\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026lt;https://en.wikipedia.org/wiki/Capacitor\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026gt;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61185,"title":"Compute wheel slip ratio during braking.","description":"During braking, a difference develops between the vehicle’s forward speed and the rotational speed of its wheels. This difference is captured by a quantity known as wheel slip ratio, which plays a critical role in traction control, ABS algorithms, and vehicle stability systems.\r\nGiven the vehicle longitudinal speed and wheel circumferential speed, determine the corresponding slip ratio. Your implementation should handle normal driving conditions, heavy braking scenarios, and boundary cases reliably.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 114px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 57px; transform-origin: 407px 57px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 31.5px; text-align: left; transform-origin: 383px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eDuring braking, a difference develops between the vehicle’s forward speed and the rotational speed of its wheels. This difference is captured by a quantity known as \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ewheel slip ratio\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, which plays a critical role in traction control, ABS algorithms, and vehicle stability systems.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven the vehicle longitudinal speed and wheel circumferential speed, determine the corresponding slip ratio. Your implementation should handle normal driving conditions, heavy braking scenarios, and boundary cases reliably.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s = wheelSlipRatio(v_vehicle, v_wheel)\r\ns = 0;\r\nend\r\n","test_suite":"%%\r\nv_vehicle = 20; v_wheel = 18;\r\ns_correct = 0.1;\r\nassert(abs(wheelSlipRatio(v_vehicle,v_wheel) - s_correct) \u003c 1e-6)\r\n\r\n%%\r\nv_vehicle = 25; v_wheel = 0;\r\ns_correct = 1;\r\nassert(abs(wheelSlipRatio(v_vehicle,v_wheel) - s_correct) \u003c 1e-6)\r\n\r\n%%\r\nv_vehicle = 0; v_wheel = 0;\r\ns_correct = 0;\r\nassert(abs(wheelSlipRatio(v_vehicle,v_wheel) - s_correct) \u003c 1e-6)\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-02-02T06:36:51.000Z","deleted_by":null,"deleted_at":null,"solvers_count":31,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T06:36:05.000Z","updated_at":"2026-03-31T16:45:06.000Z","published_at":"2026-02-02T06:36:51.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDuring braking, a difference develops between the vehicle’s forward speed and the rotational speed of its wheels. This difference is captured by a quantity known as \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ewheel slip ratio\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, which plays a critical role in traction control, ABS algorithms, and vehicle stability systems.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven the vehicle longitudinal speed and wheel circumferential speed, determine the corresponding slip ratio. Your implementation should handle normal driving conditions, heavy braking scenarios, and boundary cases reliably.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61140,"title":"Calculating Swimming Stroke Index (SI)","description":"In competitive swimming, speed () is only one part of the equation. High efficiency is defined by moving fast while maintaining a high Distance Per Stroke (DPS). The Stroke Index (SI) is a common metric used by coaches to quantify this efficiency.\r\nYour task is to calculate the Stroke Index based on a single pool length. However, you must account for the glide distance after the wall push-off, as no strokes are taken during that phase.\r\n\r\nWhere:\r\n is the velocity over the entire length (m/s).\r\nDPS is the distance covered per stroke during the swimming phase only.\r\nConstraint:If the glide distance (pushOff) is greater than or equal to the pool length (poolLength), the scenario is physically impossible for this calculation. In such cases, the function must return NaN.\r\nInputs\r\npoolLength: Pool length in meters (e.g., 50).\r\ntime: Time taken to complete the length in seconds.\r\nstrokeCount: Total number of individual arm strokes taken.\r\npushOff: Glide distance (meters) covered before the first stroke begins.\r\nOutput\r\nSI: The Stroke Index rounded to two decimal place","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 483.562px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 408px 241.781px; transform-origin: 408px 241.781px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn competitive swimming, speed (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003ev\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) is only one part of the equation. High efficiency is defined by moving fast while maintaining a high \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eDistance Per Stroke (DPS)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eStroke Index (SI)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is a common metric used by coaches to quantify this efficiency.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYour task is to calculate the Stroke Index based on a single pool length. However, you must account for the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eglide distance\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e after the wall push-off, as no strokes are taken during that phase.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"82\" height=\"18\" alt=\"SI = v*DPS\" style=\"width: 82px; height: 18px;\"\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWhere:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 40.875px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 391px 20.4375px; transform-origin: 391px 20.4375px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2188px; text-align: left; transform-origin: 363px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003ev\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the velocity over the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eentire\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e length (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em/s\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e).\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2188px; text-align: left; transform-origin: 363px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003eDPS\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the distance covered per stroke during the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eswimming phase only\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 43px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 21.5px; text-align: left; transform-origin: 384px 21.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eConstraint:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf the glide distance (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epushOff\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) is greater than or equal to the pool length (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epoolLength\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e), the scenario is physically impossible for this calculation. In such cases, the function must return \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; font-weight: 700; \"\u003eNaN\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInputs\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003col style=\"block-size: 83.75px; font-family: Helvetica, Arial, sans-serif; list-style-type: decimal; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 391px 41.875px; transform-origin: 391px 41.875px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epoolLength\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Pool length in meters (e.g., 50).\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003etime\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Time taken to complete the length in seconds.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003estrokeCount\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Total number of individual arm strokes taken.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epushOff\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Glide distance (meters) covered before the first stroke begins.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 20.9375px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 391px 10.4688px; transform-origin: 391px 10.4688px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eSI\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: The Stroke Index rounded to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003etwo decimal place\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function SI = calculateStrokeIndex(poolLength, time, strokeCount, pushOff)\r\n  SI = 1;\r\nend","test_suite":"%% Test Case 1:\r\nassert(isequal(calculateStrokeIndex(50, 35, 30, 5), 2.14));\r\n\r\n%% Test Case 2: Short Course Sprint\r\nassert(isequal(calculateStrokeIndex(25, 15, 12, 6), 2.64));\r\n\r\n%% Test Case 3:\r\nresult = calculateStrokeIndex(25, 10, 15, 30);\r\nassert(isnan(result), 'Function should return NaN when glide distance exceeds pool length');\r\n\r\n%% Test Case 4:\r\nresult = calculateStrokeIndex(50, 40, 20, 50);\r\nassert(isnan(result));\r\n\r\n%% Test Case 5:\r\nfor i = 1:5\r\n    L_rand = 50;\r\n    T_rand = 30 + rand*20;\r\n    S_rand = 20 + randi(20);\r\n    G_rand = rand*10;\r\n    \r\n    v = L_rand / T_rand;\r\n    DPS = (L_rand - G_rand) / S_rand;\r\n    expected = round(v * DPS, 2);\r\n    \r\n    assert(abs(calculateStrokeIndex(L_rand, T_rand, S_rand, G_rand) - expected) \u003c 1e-8);\r\nend","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":4996329,"edited_by":4996329,"edited_at":"2025-12-18T10:10:12.000Z","deleted_by":null,"deleted_at":null,"solvers_count":10,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-12-18T09:56:54.000Z","updated_at":"2026-02-26T10:57:38.000Z","published_at":"2025-12-18T10:03:46.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn competitive swimming, speed (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"v\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$v$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e) is only one part of the equation. High efficiency is defined by moving fast while maintaining a high \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eDistance Per Stroke (DPS)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. The \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eStroke Index (SI)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is a common metric used by coaches to quantify this efficiency.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYour task is to calculate the Stroke Index based on a single pool length. However, you must account for the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eglide distance\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e after the wall push-off, as no strokes are taken during that phase.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"SI = v*DPS\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$$SI = v \\\\cdot DPS$$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWhere:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"v\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$v$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the velocity over the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eentire\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e length (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em/s\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eDPS\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is the distance covered per stroke during the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eswimming phase only\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eConstraint:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eIf the glide distance (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epushOff\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e) is greater than or equal to the pool length (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epoolLength\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e), the scenario is physically impossible for this calculation. In such cases, the function must return \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eNaN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInputs\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epoolLength\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Pool length in meters (e.g., 50).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003etime\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Time taken to complete the length in seconds.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003estrokeCount\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Total number of individual arm strokes taken.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epushOff\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Glide distance (meters) covered before the first stroke begins.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eSI\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: The Stroke Index rounded to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003etwo decimal place\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"}],"problem_search":{"errors":[],"problems":[{"id":61183,"title":"Estimate brake line pressure required for a given force.","description":"Hydraulic braking systems amplify pedal input to generate braking force. Given braking force and piston area, compute the hydraulic pressure required inside the brake lines.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eHydraulic braking systems amplify pedal input to generate braking force. Given braking force and piston area, compute the hydraulic pressure required inside the brake lines.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function P = brakePressure(F,A)\r\nP = 0;\r\nend\r\n","test_suite":"%%\r\nF = 4000; A = 0.004;\r\nP_correct = 1e6;\r\nassert(abs(brakePressure(F,A)-P_correct) \u003c 1)\r\n\r\n%%\r\nF = 3000; A = 0.003;\r\nP_correct = 1e6;\r\nassert(abs(brakePressure(F,A)-P_correct) \u003c 1)\r\n\r\n%%\r\nF = 0; A = 0.005;\r\nP_correct = 0;\r\nassert(isequal(brakePressure(F,A),P_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-02-02T06:25:47.000Z","deleted_by":null,"deleted_at":null,"solvers_count":39,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T06:25:43.000Z","updated_at":"2026-03-31T16:42:26.000Z","published_at":"2026-02-02T06:25:47.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHydraulic braking systems amplify pedal input to generate braking force. Given braking force and piston area, compute the hydraulic pressure required inside the brake lines.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":1875,"title":"GJam: 2013 China Event: Cannon Angle","description":"This Challenge is derived from \u003chttp://code.google.com/codejam/contest/2933486/dashboard#s=p1 GJam 2013 China Captain Hammer\u003e. The problem is modified to fit within Cody dimensions.\r\n\r\nThe Challenge is to return the lower angle of a cannon given a target distance and an initial cannonball velocity. Gravity is a constant at 9.8m/sec^2, A valid solution is assured. (Error tolerance 2e-6).\r\n\r\n*Input:* [v d]  Velocity and Distance in meters.\r\n\r\n*Output:* theta  in units of degrees with an accuracy of 2e-6\r\n\r\n\r\n*Competition Summary:*  Best Time of 8 minutes,  755/1070 completed\r\n\r\nThe winner completed all three GJam China Challenges in 26 minutes with second at 43 minutes.\r\n","description_html":"\u003cp\u003eThis Challenge is derived from \u003ca href = \"http://code.google.com/codejam/contest/2933486/dashboard#s=p1\"\u003eGJam 2013 China Captain Hammer\u003c/a\u003e. The problem is modified to fit within Cody dimensions.\u003c/p\u003e\u003cp\u003eThe Challenge is to return the lower angle of a cannon given a target distance and an initial cannonball velocity. Gravity is a constant at 9.8m/sec^2, A valid solution is assured. (Error tolerance 2e-6).\u003c/p\u003e\u003cp\u003e\u003cb\u003eInput:\u003c/b\u003e [v d]  Velocity and Distance in meters.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e theta  in units of degrees with an accuracy of 2e-6\u003c/p\u003e\u003cp\u003e\u003cb\u003eCompetition Summary:\u003c/b\u003e  Best Time of 8 minutes,  755/1070 completed\u003c/p\u003e\u003cp\u003eThe winner completed all three GJam China Challenges in 26 minutes with second at 43 minutes.\u003c/p\u003e","function_template":"function theta=Cannon(v,d)\r\n  theta=0;\r\nend","test_suite":"%%\r\ntic\r\nvd=[249 6326 ];\r\nexp=44.5948575;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[77 41 ];\r\nexp=1.9429163;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[28 11 ];\r\nexp=3.9516039;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[105 21 ];\r\nexp=0.5347917;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[147 51 ];\r\nexp=0.6626633;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3210 ];\r\nexp=10.2293872;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[219 61 ];\r\nexp=0.3570850;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[240 41 ];\r\nexp=0.1998405;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[179 3269 ];\r\nexp=44.5041154;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3480 ];\r\nexp=11.1338133;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[102 81 ];\r\nexp=2.1878908;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[121 51 ];\r\nexp=0.9781434;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[138 31 ];\r\nexp=0.4570257;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[210 4500 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[192 3761 ];\r\nexp=44.4745779;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[37 41 ];\r\nexp=8.5337735;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[32 41 ];\r\nexp=11.5514232;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[199 81 ];\r\nexp=0.5742839;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3360 ];\r\nexp=10.7304643;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[233 71 ];\r\nexp=0.3671784;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[266 81 ];\r\nexp=0.3214027;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[27 21 ];\r\nexp=8.1988972;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[279 21 ];\r\nexp=0.0757408;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5230 ];\r\nexp=17.3572961;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[279 51 ];\r\nexp=0.1839431;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[218 21 ];\r\nexp=0.1240585;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7690 ];\r\nexp=28.4309587;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[89 31 ];\r\nexp=1.0990234;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[141 2028 ];\r\nexp=44.2618026;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[178 81 ];\r\nexp=0.7178094;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[132 71 ];\r\nexp=1.1443126;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 690 ];\r\nexp=2.1544417;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6970 ];\r\nexp=24.6861041;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[41 1 ];\r\nexp=0.1670142;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[123 21 ];\r\nexp=0.3897097;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[48 61 ];\r\nexp=7.5190650;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[77 81 ];\r\nexp=3.8470546;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[152 71 ];\r\nexp=0.8628902;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[267 11 ];\r\nexp=0.0433201;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[164 21 ];\r\nexp=0.2192071;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4310 ];\r\nexp=13.9947943;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[256 71 ];\r\nexp=0.3041622;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[192 41 ];\r\nexp=0.3122545;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7110 ];\r\nexp=25.3662790;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[98 31 ];\r\nexp=0.9063600;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[286 21 ];\r\nexp=0.0720786;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[44 91 ];\r\nexp=13.7142226;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8360 ];\r\nexp=32.7741901;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5060 ];\r\nexp=16.7170592;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[194 81 ];\r\nexp=0.6042720;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[96 61 ];\r\nexp=1.8595639;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[190 1 ];\r\nexp=0.0077770;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[237 51 ];\r\nexp=0.2549165;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[52 31 ];\r\nexp=3.2254600;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[250 71 ];\r\nexp=0.3189378;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[29 61 ];\r\nexp=22.6508544;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4030 ];\r\nexp=13.0143792;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[39 31 ];\r\nexp=5.7607904;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[62 61 ];\r\nexp=4.4733355;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[246 61 ];\r\nexp=0.2829993;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[86 51 ];\r\nexp=1.9374169;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[252 91 ];\r\nexp=0.4023216;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[275 11 ];\r\nexp=0.0408363;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[49 81 ];\r\nexp=9.6529702;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[127 11 ];\r\nexp=0.1914728;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[223 61 ];\r\nexp=0.3443890;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[160 21 ];\r\nexp=0.2303047;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[196 31 ];\r\nexp=0.2265546;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[55 91 ];\r\nexp=8.5730698;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[110 1234 ];\r\nexp=44.0395169;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[274 61 ];\r\nexp=0.2281140;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6800 ];\r\nexp=23.8846446;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3310 ];\r\nexp=10.5630642;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[44 31 ];\r\nexp=4.5141266;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[295 1 ];\r\nexp=0.0032261;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[64 11 ];\r\nexp=0.7540525;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[240 21 ];\r\nexp=0.1023567;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[91 21 ];\r\nexp=0.7120327;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1870 ];\r\nexp=5.8744286;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1730 ];\r\nexp=5.4290641;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[259 51 ];\r\nexp=0.2134486;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[51 91 ];\r\nexp=10.0258563;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4200 ];\r\nexp=13.6075829;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[262 81 ];\r\nexp=0.3312919;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[74 81 ];\r\nexp=4.1674764;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[88 81 ];\r\nexp=2.9417237;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[255 91 ];\r\nexp=0.3929103;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[72 41 ];\r\nexp=2.2226617;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7900 ];\r\nexp=29.6707716;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1620 ];\r\nexp=5.0800699;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[253 71 ];\r\nexp=0.3114186;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[265 91 ];\r\nexp=0.3638145;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[248 1 ];\r\nexp=0.0045647;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6090 ];\r\nexp=20.7696393;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[158 71 ];\r\nexp=0.7985813;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2170 ];\r\nexp=6.8338053;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1500 ];\r\nexp=4.7002140;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[163 31 ];\r\nexp=0.3275780;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[139 31 ];\r\nexp=0.4504729;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[271 21 ];\r\nexp=0.0802786;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[113 41 ];\r\nexp=0.9016072;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[156 81 ];\r\nexp=0.9346125;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[100 61 ];\r\nexp=1.7135925;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[85 91 ];\r\nexp=3.5451226;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[43 61 ];\r\nexp=9.4316060;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[57 61 ];\r\nexp=5.3012744;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[136 61 ];\r\nexp=0.9260755;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5200 ];\r\nexp=17.2436039;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[159 71 ];\r\nexp=0.7885653;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[86 61 ];\r\nexp=2.3180653;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8140 ];\r\nexp=31.2094004;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5190 ];\r\nexp=17.2057754;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[259 6845 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6570 ];\r\nexp=22.8379951;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[285 71 ];\r\nexp=0.2454102;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6460 ];\r\nexp=22.3511092;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[75 573 ];\r\nexp=43.3260450;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[46 41 ];\r\nexp=5.4730826;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[52 21 ];\r\nexp=2.1824862;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5950 ];\r\nexp=20.1913108;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[68 91 ];\r\nexp=5.5599659;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[64 21 ];\r\nexp=1.4399949;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[36 11 ];\r\nexp=2.3856596;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[134 21 ];\r\nexp=0.3283507;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[9 1 ];\r\nexp=3.4745532;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[143 31 ];\r\nexp=0.4256222;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[116 91 ];\r\nexp=1.9000393;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[23 41 ];\r\nexp=24.7121091;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8390 ];\r\nexp=33.0022766;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[200 51 ];\r\nexp=0.3579647;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[66 91 ];\r\nexp=5.9068209;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[203 21 ];\r\nexp=0.1430697;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 230 ];\r\nexp=0.7175455;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7250 ];\r\nexp=26.0668121;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[81 71 ];\r\nexp=3.0438586;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[184 91 ];\r\nexp=0.7547006;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[273 41 ];\r\nexp=0.1544470;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[224 91 ];\r\nexp=0.5091983;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[25 1 ];\r\nexp=0.4492173;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[243 51 ];\r\nexp=0.2424831;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4920 ];\r\nexp=16.1968290;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 840 ];\r\nexp=2.6239945;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2740 ];\r\nexp=8.6794304;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[49 91 ];\r\nexp=10.9018740;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[244 81 ];\r\nexp=0.3819768;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[197 31 ];\r\nexp=0.2242603;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[186 31 ];\r\nexp=0.2515707;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[278 71 ];\r\nexp=0.2579249;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[258 1 ];\r\nexp=0.0042177;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2990 ];\r\nexp=9.5002916;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[10 1 ];\r\nexp=2.8120066;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7390 ];\r\nexp=26.7901102;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 430 ];\r\nexp=1.3418485;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[46 215 ];\r\nexp=42.3568299;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6250 ];\r\nexp=21.4435357;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[109 1 ];\r\nexp=0.0236301;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[152 31 ];\r\nexp=0.3767088;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[290 41 ];\r\nexp=0.1368700;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[277 21 ];\r\nexp=0.0768385;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[136 81 ];\r\nexp=1.2298703;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 910 ];\r\nexp=2.8433535;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[224 21 ];\r\nexp=0.1175014;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2440 ];\r\nexp=7.7039453;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[119 71 ];\r\nexp=1.4081796;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[20 31 ];\r\nexp=24.7100694;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5120 ];\r\nexp=16.9419243;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1940 ];\r\nexp=6.0976449;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[119 1445 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[255 6635 ];\r\nexp=44.7753101;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 280 ];\r\nexp=0.8735777;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[219 41 ];\r\nexp=0.2400045;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[262 61 ];\r\nexp=0.2494890;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 970 ];\r\nexp=3.0315083;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7720 ];\r\nexp=28.6029416;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[189 31 ];\r\nexp=0.2436475;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[110 51 ];\r\nexp=1.1836603;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[298 61 ];\r\nexp=0.1928498;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[231 5445 ];\r\nexp=44.9999996;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[69 81 ];\r\nexp=4.7988649;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[107 11 ];\r\nexp=0.2697430;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[114 21 ];\r\nexp=0.4536767;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[47 225 ];\r\nexp=43.2757298;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[17 1 ];\r\nexp=0.9716372;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[130 81 ];\r\nexp=1.3460985;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4630 ];\r\nexp=15.1376561;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[121 91 ];\r\nexp=1.7460565;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[82 41 ];\r\nexp=1.7129065;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[199 31 ];\r\nexp=0.2197751;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[93 71 ];\r\nexp=2.3071761;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5540 ];\r\nexp=18.5513095;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[126 41 ];\r\nexp=0.7251166;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4260 ];\r\nexp=13.8184496;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 440 ];\r\nexp=1.3730779;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3130 ];\r\nexp=9.9634881;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[145 61 ];\r\nexp=0.8146500;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1170 ];\r\nexp=3.6596870;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[200 4081 ];\r\nexp=44.4955953;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[271 41 ];\r\nexp=0.1567351;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1490 ];\r\nexp=4.6685979;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[291 21 ];\r\nexp=0.0696230;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[139 51 ];\r\nexp=0.7411528;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[53 51 ];\r\nexp=5.1245500;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[42 71 ];\r\nexp=11.6156650;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[243 91 ];\r\nexp=0.4326773;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4430 ];\r\nexp=14.4204070;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[210 11 ];\r\nexp=0.0700282;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[112 61 ];\r\nexp=1.3657683;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[219 31 ];\r\nexp=0.1814659;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4910 ];\r\nexp=16.1599009;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[44 11 ];\r\nexp=1.5959920;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[192 11 ];\r\nexp=0.0837741;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[276 71 ];\r\nexp=0.2616766;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[75 91 ];\r\nexp=4.5611459;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[166 21 ];\r\nexp=0.2139567;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[195 41 ];\r\nexp=0.3027202;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[116 81 ];\r\nexp=1.6909858;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[282 8114 ];\r\nexp=44.6253583;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[37 11 ];\r\nexp=2.2581760;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1910 ];\r\nexp=6.0019356;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[182 1 ];\r\nexp=0.0084757;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[176 21 ];\r\nexp=0.1903338;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[120 1 ];\r\nexp=0.0194965;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1320 ];\r\nexp=4.1319681;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[298 9061 ];\r\nexp=44.6614758;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7700 ];\r\nexp=28.4881098;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[79 636 ];\r\nexp=43.5312934;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5280 ];\r\nexp=17.5474818;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[227 31 ];\r\nexp=0.1689006;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[275 41 ];\r\nexp=0.1522086;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[171 1 ];\r\nexp=0.0096012;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[229 91 ];\r\nexp=0.4872031;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[200 1 ];\r\nexp=0.0070187;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[147 41 ];\r\nexp=0.5327126;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[169 31 ];\r\nexp=0.3047300;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[133 41 ];\r\nexp=0.6507837;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1150 ];\r\nexp=3.5967945;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[147 1 ];\r\nexp=0.0129922;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[144 51 ];\r\nexp=0.6905672;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[30 51 ];\r\nexp=16.8668385;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[217 4805 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[131 1 ];\r\nexp=0.0163597;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[58 41 ];\r\nexp=3.4299252;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[116 61 ];\r\nexp=1.2731382;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[43 1 ];\r\nexp=0.1518392;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[167 21 ];\r\nexp=0.2114020;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[295 31 ];\r\nexp=0.1000086;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[217 51 ];\r\nexp=0.3040728;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7220 ];\r\nexp=25.9148699;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[25 51 ];\r\nexp=26.5497777;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3620 ];\r\nexp=11.6073520;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[67 31 ];\r\nexp=1.9402732;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 31 ];\r\nexp=0.0967027;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8610 ];\r\nexp=34.8206771;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[81 91 ];\r\nexp=3.9060385;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[57 31 ];\r\nexp=2.6826598;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 180 ];\r\nexp=0.5615346;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[73 81 ];\r\nexp=4.2832883;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[201 21 ];\r\nexp=0.1459311;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[68 11 ];\r\nexp=0.6679330;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[159 51 ];\r\nexp=0.5663996;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[204 1 ];\r\nexp=0.0067462;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[189 81 ];\r\nexp=0.6366722;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 590 ];\r\nexp=1.8417362;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[149 61 ];\r\nexp=0.7714868;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8980 ];\r\nexp=38.9553303;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[216 11 ];\r\nexp=0.0661918;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[119 91 ];\r\nexp=1.8053178;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[125 81 ];\r\nexp=1.4560313;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6750 ];\r\nexp=23.6536081;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 790 ];\r\nexp=2.4674046;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4520 ];\r\nexp=14.7419107;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6830 ];\r\nexp=24.0242561;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[94 51 ];\r\nexp=1.6213062;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[75 21 ];\r\nexp=1.0483648;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5630 ];\r\nexp=18.9049816;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[86 71 ];\r\nexp=2.6991243;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[43 31 ];\r\nexp=4.7284323;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[193 31 ];\r\nexp=0.2336526;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[259 31 ];\r\nexp=0.1297425;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[287 21 ];\r\nexp=0.0715772;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6870 ];\r\nexp=24.2115915;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[57 41 ];\r\nexp=3.5519442;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[239 11 ];\r\nexp=0.0540650;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[192 71 ];\r\nexp=0.5407548;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8470 ];\r\nexp=33.6315148;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[77 61 ];\r\nexp=2.8933815;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[105 1125 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 9183 ];\r\nexp=44.6530547;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7170 ];\r\nexp=25.6638839;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5560 ];\r\nexp=18.6296154;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 980 ];\r\nexp=3.0628800;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[145 91 ];\r\nexp=1.2154985;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5820 ];\r\nexp=19.6630507;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[32 61 ];\r\nexp=17.8587444;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5270 ];\r\nexp=17.5093740;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[237 31 ];\r\nexp=0.1549479;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[168 1 ];\r\nexp=0.0099472;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[41 71 ];\r\nexp=12.2256701;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[207 11 ];\r\nexp=0.0720728;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[250 61 ];\r\nexp=0.2740155;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 51 ];\r\nexp=0.1590921;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[161 51 ];\r\nexp=0.5524132;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[265 1 ];\r\nexp=0.0039979;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[246 21 ];\r\nexp=0.0974246;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[195 61 ];\r\nexp=0.4503988;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[160 2612 ];\r\nexp=44.6077195;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6150 ];\r\nexp=21.0206716;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[83 21 ];\r\nexp=0.8559461;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[160 61 ];\r\nexp=0.6690338;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[156 61 ];\r\nexp=0.7037899;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[162 1 ];\r\nexp=0.0106977;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[166 61 ];\r\nexp=0.6215362;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[107 51 ];\r\nexp=1.2510059;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[215 41 ];\r\nexp=0.2490182;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[212 91 ];\r\nexp=0.5684822;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[84 61 ];\r\nexp=2.4300259;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6630 ];\r\nexp=23.1071658;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[119 61 ];\r\nexp=1.2097168;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[7 1 ];\r\nexp=5.7684795;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6730 ];\r\nexp=23.5617578;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2860 ];\r\nexp=9.0724806;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[274 21 ];\r\nexp=0.0785303;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1510 ];\r\nexp=4.7318359;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[42 21 ];\r\nexp=3.3498826;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5220 ];\r\nexp=17.3193640;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8670 ];\r\nexp=35.3730578;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[18 31 ];\r\nexp=34.8306447;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8540 ];\r\nexp=34.2104815;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[256 21 ];\r\nexp=0.0899619;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[91 71 ];\r\nexp=2.4099422;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[247 51 ];\r\nexp=0.2346928;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[56 21 ];\r\nexp=1.8813698;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[135 91 ];\r\nexp=1.4023810;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3930 ];\r\nexp=12.6682378;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[97 41 ];\r\nexp=1.2237457;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[280 8000 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[280 41 ];\r\nexp=0.1468211;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[147 21 ];\r\nexp=0.2728412;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[23 11 ];\r\nexp=5.8790664;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[139 1 ];\r\nexp=0.0145308;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[78 620 ];\r\nexp=43.5307164;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[250 41 ];\r\nexp=0.1841728;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[69 41 ];\r\nexp=2.4205902;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2730 ];\r\nexp=8.6467533;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[141 91 ];\r\nexp=1.2854868;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3800 ];\r\nexp=12.2211854;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[290 11 ];\r\nexp=0.0367211;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[276 21 ];\r\nexp=0.0773963;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[105 11 ];\r\nexp=0.2801172;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[238 81 ];\r\nexp=0.4014801;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[200 91 ];\r\nexp=0.6387576;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[293 41 ];\r\nexp=0.1340815;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[299 9122 ];\r\nexp=44.6851269;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[21 1 ];\r\nexp=0.6366722;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[36 91 ];\r\nexp=21.7406299;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[270 7438 ];\r\nexp=44.5863296;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5870 ];\r\nexp=19.8652679;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[125 21 ];\r\nexp=0.3773380;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[132 81 ];\r\nexp=1.3055882;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4510 ];\r\nexp=14.7060881;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[111 91 ];\r\nexp=2.0753631;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[176 11 ];\r\nexp=0.0996981;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[76 81 ];\r\nexp=3.9496009;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[183 51 ];\r\nexp=0.4275657;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[144 41 ];\r\nexp=0.5551429;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[111 11 ];\r\nexp=0.2506519;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[232 21 ];\r\nexp=0.1095376;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[153 2388 ];\r\nexp=44.3197033;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[264 41 ];\r\nexp=0.1651571;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[203 1 ];\r\nexp=0.0068128;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[206 1 ];\r\nexp=0.0066158;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[190 41 ];\r\nexp=0.3188632;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[67 51 ];\r\nexp=3.1962494;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[59 21 ];\r\nexp=1.6946784;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8380 ];\r\nexp=32.9257979;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[108 51 ];\r\nexp=1.2279321;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[267 7274 ];\r\nexp=44.7042055;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[298 21 ];\r\nexp=0.0663905;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 9070 ];\r\nexp=40.4879078;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[247 31 ];\r\nexp=0.1426554;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1580 ];\r\nexp=4.9533543;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 310 ];\r\nexp=0.9672092;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[246 91 ];\r\nexp=0.4221877;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[110 81 ];\r\nexp=1.8807470;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[189 1 ];\r\nexp=0.0078595;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[299 91 ];\r\nexp=0.2857755;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4820 ];\r\nexp=15.8288860;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[184 41 ];\r\nexp=0.3399986;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[173 81 ];\r\nexp=0.7599105;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[201 61 ];\r\nexp=0.4239087;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1820 ];\r\nexp=5.7152103;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[130 41 ];\r\nexp=0.6811720;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[65 71 ];\r\nexp=4.7395084;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[192 91 ];\r\nexp=0.6931066;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[136 1887 ];\r\nexp=44.4506934;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[171 51 ];\r\nexp=0.4896861;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[236 91 ];\r\nexp=0.4587274;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[173 31 ];\r\nexp=0.2908008;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[35 41 ];\r\nexp=9.5737143;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 9020 ];\r\nexp=39.5832887;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[296 91 ];\r\nexp=0.2915978;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[33 41 ];\r\nexp=10.8258185;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4110 ];\r\nexp=13.2927675;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[277 1 ];\r\nexp=0.0036590;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[254 31 ];\r\nexp=0.1349008;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[82 81 ];\r\nexp=3.3899244;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[54 21 ];\r\nexp=2.0235395;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[54 91 ];\r\nexp=8.9040499;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[85 71 ];\r\nexp=2.7632032;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[14 1 ];\r\nexp=1.4329920;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[170 81 ];\r\nexp=0.7869742;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[42 51 ];\r\nexp=8.2296248;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[35 125 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3390 ];\r\nexp=10.8310888;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[122 81 ];\r\nexp=1.5285870;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[74 31 ];\r\nexp=1.5901570;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8170 ];\r\nexp=31.4129069;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1660 ];\r\nexp=5.2068859;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[134 41 ];\r\nexp=0.6411051;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[184 3454 ];\r\nexp=44.4258154;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[143 81 ];\r\nexp=1.1123483;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[67 91 ];\r\nexp=5.7294046;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[208 41 ];\r\nexp=0.2660616;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[169 81 ];\r\nexp=0.7963175;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[213 11 ];\r\nexp=0.0680695;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[152 61 ];\r\nexp=0.7413270;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[259 21 ];\r\nexp=0.0878899;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[174 71 ];\r\nexp=0.6584409;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[242 41 ];\r\nexp=0.1965510;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[265 31 ];\r\nexp=0.1239339;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6930 ];\r\nexp=24.4952155;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[177 1 ];\r\nexp=0.0089613;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8630 ];\r\nexp=35.0015489;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[281 8057 ];\r\nexp=44.7766386;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4450 ];\r\nexp=14.4916789;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[257 51 ];\r\nexp=0.2167838;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7210 ];\r\nexp=25.8644501;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8110 ];\r\nexp=31.0086245;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[120 31 ];\r\nexp=0.6044357;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4010 ];\r\nexp=12.9449893;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[85 737 ];\r\nexp=44.2615751;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[287 1 ];\r\nexp=0.0034084;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6900 ];\r\nexp=24.3530039;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[107 81 ];\r\nexp=1.9878552;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[73 91 ];\r\nexp=4.8168446;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5830 ];\r\nexp=19.7034001;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[125 51 ];\r\nexp=0.9165221;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[174 31 ];\r\nexp=0.2874678;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[258 91 ];\r\nexp=0.3838254;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[88 51 ];\r\nexp=1.8502291;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 890 ];\r\nexp=2.7806630;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[131 71 ];\r\nexp=1.1618593;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5890 ];\r\nexp=19.9464871;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[275 81 ];\r\nexp=0.3007089;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[201 31 ];\r\nexp=0.2154232;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[103 61 ];\r\nexp=1.6151178;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[169 11 ];\r\nexp=0.1081282;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[234 81 ];\r\nexp=0.4153242;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[127 41 ];\r\nexp=0.7137400;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[45 61 ];\r\nexp=8.5850615;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[268 71 ];\r\nexp=0.2775328;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[120 81 ];\r\nexp=1.5800158;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2520 ];\r\nexp=7.9631306;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[39 91 ];\r\nexp=17.9483177;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[113 31 ];\r\nexp=0.6816548;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[152 91 ];\r\nexp=1.1060655;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1260 ];\r\nexp=3.9429273;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6980 ];\r\nexp=24.7340581;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[212 61 ];\r\nexp=0.3810567;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[8 1 ];\r\nexp=4.4040343;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[153 61 ];\r\nexp=0.7316660;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[55 1 ];\r\nexp=0.0928099;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3080 ];\r\nexp=9.7977560;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[108 81 ];\r\nexp=1.9511562;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[81 41 ];\r\nexp=1.7555143;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[242 71 ];\r\nexp=0.3403741;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[46 81 ];\r\nexp=11.0165379;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[221 1 ];\r\nexp=0.0057482;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[249 71 ];\r\nexp=0.3215048;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7440 ];\r\nexp=27.0544802;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[45 21 ];\r\nexp=2.9165098;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[289 21 ];\r\nexp=0.0705899;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7520 ];\r\nexp=27.4846425;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[235 1 ];\r\nexp=0.0050837;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[299 1234 ];\r\nexp=3.8870928;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[250 1 ];\r\nexp=0.0044920;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[176 51 ];\r\nexp=0.4622558;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8510 ];\r\nexp=33.9588221;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[151 31 ];\r\nexp=0.3817151;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[61 1 ];\r\nexp=0.0754501;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[132 31 ];\r\nexp=0.4995219;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[238 21 ];\r\nexp=0.1040843;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[238 91 ];\r\nexp=0.4510494;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[101 31 ];\r\nexp=0.8533003;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[252 1 ];\r\nexp=0.0044210;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[101 41 ];\r\nexp=1.1286835;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[152 51 ];\r\nexp=0.6197772;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8830 ];\r\nexp=37.0236469;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[240 31 ];\r\nexp=0.1510984;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[134 51 ];\r\nexp=0.7975086;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1020 ];\r\nexp=3.1884039;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[257 91 ];\r\nexp=0.3868183;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[128 11 ];\r\nexp=0.1884927;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6160 ];\r\nexp=21.0627029;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[213 31 ];\r\nexp=0.1918335;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[255 51 ];\r\nexp=0.2201977;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[126 11 ];\r\nexp=0.1945242;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[280 51 ];\r\nexp=0.1826315;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[150 41 ];\r\nexp=0.5116148;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7480 ];\r\nexp=27.2684278;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4140 ];\r\nexp=13.3975114;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[133 51 ];\r\nexp=0.8095495;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[168 41 ];\r\nexp=0.4078483;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[281 71 ];\r\nexp=0.2524469;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[147 2205 ];\r\nexp=45.0000000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[113 1 ];\r\nexp=0.0219868;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[242 61 ];\r\nexp=0.2924323;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[56 91 ];\r\nexp=8.2607465;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[260 21 ];\r\nexp=0.0872152;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[22 31 ];\r\nexp=19.4398009;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[165 71 ];\r\nexp=0.7322451;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2190 ];\r\nexp=6.8980297;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7570 ];\r\nexp=27.7582308;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[141 41 ];\r\nexp=0.5790205;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4840 ];\r\nexp=15.9022391;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[142 11 ];\r\nexp=0.1531570;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7750 ];\r\nexp=28.7765421;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[232 81 ];\r\nexp=0.4225163;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[53 21 ];\r\nexp=2.1007558;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[123 81 ];\r\nexp=1.5038100;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[210 51 ];\r\nexp=0.3246830;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[273 1 ];\r\nexp=0.0037670;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[50 81 ];\r\nexp=9.2565056;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[298 1 ];\r\nexp=0.0031614;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[166 11 ];\r\nexp=0.1120718;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6260 ];\r\nexp=21.4861399;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[253 81 ];\r\nexp=0.3552825;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[144 91 ];\r\nexp=1.2324494;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[288 8463 ];\r\nexp=44.6385985;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[268 7328 ];\r\nexp=44.5316039;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[297 61 ];\r\nexp=0.1941507;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[62 41 ];\r\nexp=2.9999445;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[223 5074 ];\r\nexp=44.6458418;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[248 91 ];\r\nexp=0.4154052;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[106 61 ];\r\nexp=1.5249020;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[211 41 ];\r\nexp=0.2585494;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[120 21 ];\r\nexp=0.4094400;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[210 1 ];\r\nexp=0.0063662;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4660 ];\r\nexp=15.2461386;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[172 71 ];\r\nexp=0.6738453;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[214 91 ];\r\nexp=0.5579047;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[131 11 ];\r\nexp=0.1799582;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[50 255 ];\r\nexp=44.1896883;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[227 51 ];\r\nexp=0.2778715;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4330 ];\r\nexp=14.0654935;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[115 1 ];\r\nexp=0.0212287;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[80 91 ];\r\nexp=4.0049368;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[228 21 ];\r\nexp=0.1134147;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[104 11 ];\r\nexp=0.2855301;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[260 61 ];\r\nexp=0.2533422;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[290 1 ];\r\nexp=0.0033383;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[105 81 ];\r\nexp=2.0644344;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[57 71 ];\r\nexp=6.1830728;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[43 188 ];\r\nexp=42.5787456;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[214 71 ];\r\nexp=0.4352775;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[284 11 ];\r\nexp=0.0382891;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[267 41 ];\r\nexp=0.1614665;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[270 31 ];\r\nexp=0.1193862;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[131 51 ];\r\nexp=0.8344642;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[70 71 ];\r\nexp=4.0817971;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[21 41 ];\r\nexp=32.8296766;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[282 91 ];\r\nexp=0.3212706;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[24 11 ];\r\nexp=5.3933350;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[226 21 ];\r\nexp=0.1154310;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[227 11 ];\r\nexp=0.0599322;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4800 ];\r\nexp=15.7556484;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[134 81 ];\r\nexp=1.2668806;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[256 61 ];\r\nexp=0.2613212;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8860 ];\r\nexp=37.3715407;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[230 81 ];\r\nexp=0.4298969;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[182 91 ];\r\nexp=0.7713825;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[142 2057 ];\r\nexp=44.3369812;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[32 71 ];\r\nexp=21.4019868;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[142 61 ];\r\nexp=0.8494455;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3170 ];\r\nexp=10.0963242;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[191 61 ];\r\nexp=0.4694629;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[190 71 ];\r\nexp=0.5522004;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[205 71 ];\r\nexp=0.4743394;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[248 71 ];\r\nexp=0.3241029;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[166 31 ];\r\nexp=0.3158443;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[145 51 ];\r\nexp=0.6810732;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6050 ];\r\nexp=20.6033628;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[254 71 ];\r\nexp=0.3089712;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[185 71 ];\r\nexp=0.5824565;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3380 ];\r\nexp=10.7975318;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[296 71 ];\r\nexp=0.2275088;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[38 81 ];\r\nexp=16.6740056;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[24 1 ];\r\nexp=0.4874355;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[280 31 ];\r\nexp=0.1110109;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8690 ];\r\nexp=35.5640799;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 4160 ];\r\nexp=13.4674481;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[252 61 ];\r\nexp=0.2696832;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[98 71 ];\r\nexp=2.0773304;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[209 81 ];\r\nexp=0.5206370;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2710 ];\r\nexp=8.5814338;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[57 21 ];\r\nexp=1.8158465;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[102 51 ];\r\nexp=1.3767520;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 1770 ];\r\nexp=5.5561708;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8160 ];\r\nexp=31.3447605;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[74 71 ];\r\nexp=3.6499694;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[51 41 ];\r\nexp=4.4432920;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[297 91 ];\r\nexp=0.2896374;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[48 71 ];\r\nexp=8.7887794;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[140 41 ];\r\nexp=0.5873229;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[284 61 ];\r\nexp=0.2123322;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[229 41 ];\r\nexp=0.2195007;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[294 81 ];\r\nexp=0.2630966;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[138 71 ];\r\nexp=1.0469250;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[84 11 ];\r\nexp=0.4376931;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[220 11 ];\r\nexp=0.0638067;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 650 ];\r\nexp=2.0293307;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[261 31 ];\r\nexp=0.1277617;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[259 11 ];\r\nexp=0.0460375;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[150 21 ];\r\nexp=0.2620364;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3580 ];\r\nexp=11.4717190;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[295 71 ];\r\nexp=0.2290539;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8330 ];\r\nexp=32.5500293;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[127 21 ];\r\nexp=0.3655463;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[196 91 ];\r\nexp=0.6651000;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7230 ];\r\nexp=25.9654030;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[55 51 ];\r\nexp=4.7550987;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[118 61 ];\r\nexp=1.2303199;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[172 61 ];\r\nexp=0.5789235;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3990 ];\r\nexp=12.8756810;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[49 41 ];\r\nexp=4.8168001;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8400 ];\r\nexp=33.0792168;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[272 51 ];\r\nexp=0.1935327;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[246 51 ];\r\nexp=0.2366048;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[209 71 ];\r\nexp=0.4563550;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[113 51 ];\r\nexp=1.1216128;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[58 11 ];\r\nexp=0.9181841;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[90 21 ];\r\nexp=0.7279469;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5580 ];\r\nexp=18.7080845;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[26 1 ];\r\nexp=0.4153242;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6020 ];\r\nexp=20.4792082;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[153 71 ];\r\nexp=0.8516442;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[231 71 ];\r\nexp=0.3735643;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[296 41 ];\r\nexp=0.1313774;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[218 51 ];\r\nexp=0.3012894;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[156 71 ];\r\nexp=0.8191945;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[244 91 ];\r\nexp=0.4291377;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[97 61 ];\r\nexp=1.8213680;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[33 21 ];\r\nexp=5.4466530;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[48 21 ];\r\nexp=2.5623281;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5180 ];\r\nexp=17.1679811;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3630 ];\r\nexp=11.6413032;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[164 81 ];\r\nexp=0.8456275;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[180 3306 ];\r\nexp=44.7534375;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[49 61 ];\r\nexp=7.2085690;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[89 21 ];\r\nexp=0.7444009;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 2110 ];\r\nexp=6.6413404;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[199 4040 ];\r\nexp=44.3892211;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[297 31 ];\r\nexp=0.0986662;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5920 ];\r\nexp=20.0686784;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7180 ];\r\nexp=25.7138602;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5210 ];\r\nexp=17.2814667;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[212 11 ];\r\nexp=0.0687132;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[246 1 ];\r\nexp=0.0046393;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[250 11 ];\r\nexp=0.0494119;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[47 1 ];\r\nexp=0.1270938;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[112 41 ];\r\nexp=0.9177847;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5110 ];\r\nexp=16.9043649;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6410 ];\r\nexp=22.1324926;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7030 ];\r\nexp=24.9752527;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 7970 ];\r\nexp=30.1045540;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[255 1 ];\r\nexp=0.0043176;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[222 5028 ];\r\nexp=44.4345459;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[247 61 ];\r\nexp=0.2807124;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[40 163 ];\r\nexp=43.3665978;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[88 21 ];\r\nexp=0.7614192;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[91 51 ];\r\nexp=1.7300957;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[145 21 ];\r\nexp=0.2804200;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[170 61 ];\r\nexp=0.5926273;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[95 11 ];\r\nexp=0.3421957;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[137 1 ];\r\nexp=0.0149581;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[220 51 ];\r\nexp=0.2958362;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[132 51 ];\r\nexp=0.8218652;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 6850 ];\r\nexp=24.1177523;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[271 61 ];\r\nexp=0.2331926;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[184 31 ];\r\nexp=0.2570695;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 3250 ];\r\nexp=10.3626812;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[11 1 ];\r\nexp=2.3227865;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[148 81 ];\r\nexp=1.0384257;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 5400 ];\r\nexp=18.0076051;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[287 31 ];\r\nexp=0.1056617;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[183 11 ];\r\nexp=0.0922168;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[278 81 ];\r\nexp=0.2942536;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[291 1 ];\r\nexp=0.0033154;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[64 71 ];\r\nexp=4.8902189;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[290 61 ];\r\nexp=0.2036368;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[124 51 ];\r\nexp=0.9313695;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[230 21 ];\r\nexp=0.1114509;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[109 51 ];\r\nexp=1.2054913;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[84 91 ];\r\nexp=3.6304847;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[289 81 ];\r\nexp=0.2722793;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[138 1 ];\r\nexp=0.0147421;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[130 91 ];\r\nexp=1.5124296;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[182 21 ];\r\nexp=0.1779910;\r\ntheta=Cannon(vd(1),vd(2));\r\nassert(abs(theta-exp)\u003c2e-6)\r\n%%\r\nvd=[300 8780 ];\r\nexp=36.4745305","published":true,"deleted":false,"likes_count":7,"comments_count":4,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":58,"test_suite_updated_at":"2014-02-10T18:16:06.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-09-15T23:22:36.000Z","updated_at":"2026-03-31T20:37:05.000Z","published_at":"2013-09-15T23:34:41.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis Challenge is derived from\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://code.google.com/codejam/contest/2933486/dashboard#s=p1\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eGJam 2013 China Captain Hammer\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. The problem is modified to fit within Cody dimensions.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Challenge is to return the lower angle of a cannon given a target distance and an initial cannonball velocity. Gravity is a constant at 9.8m/sec^2, A valid solution is assured. (Error tolerance 2e-6).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e [v d] Velocity and Distance in meters.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e theta in units of degrees with an accuracy of 2e-6\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCompetition Summary:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Best Time of 8 minutes, 755/1070 completed\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe winner completed all three GJam China Challenges in 26 minutes with second at 43 minutes.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":49723,"title":"Find the efficiency","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 10.5px; transform-origin: 407.5px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 172.958px 7.7px; transform-origin: 172.958px 7.7px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFind the efficiency of engine from Temperature tc and th\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = ef(tc,th)\r\n  y = x;\r\nend","test_suite":"%%\r\ntc = 50;th=60;\r\ny_correct =    16.6667;\r\nassert(isequal(ef(tc,th),y_correct))\r\n%%\r\ntc = 20;th=60;\r\ny_correct = 66.6667;\r\nassert(isequal(ef(tc,th),y_correct))\r\n%%\r\ntc = 50;th=90;\r\ny_correct = 44.4444;\r\nassert(isequal(ef(tc,th),y_correct))\r\n%%\r\ntc =20;th=80;\r\ny_correct = 75;\r\nassert(isequal(ef(tc,th),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":610936,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":36,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-31T03:31:17.000Z","updated_at":"2026-04-02T13:44:01.000Z","published_at":"2020-12-31T03:45:14.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind the efficiency of engine from Temperature tc and th\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":55160,"title":"Find distance travelled by an object starting from rest in time 't' and linear acceleration 'a' = 3t","description":"Find distance travelled by an object starting from rest in time 't' with linear acceleration a = 3t. You are given time t as an input to the function.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind distance travelled by an object starting from rest in time 't' with linear acceleration a = 3t. You are given time t as an input to the function.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s = your_fcn_name(t)\r\n  s = a;\r\nend","test_suite":"%%\r\nt = 2;\r\ny_correct = 4;\r\nassert(isequal(your_fcn_name(t),y_correct))\r\n\r\n%%\r\nt = 0;\r\ny_correct = 0;\r\nassert(isequal(your_fcn_name(t),y_correct))\r\n\r\n%%\r\nt = 1;\r\ny_correct = 0.5;\r\nassert(isequal(your_fcn_name(t),y_correct))\r\n\r\n%%\r\nt = 12;\r\ny_correct = 864;\r\nassert(isequal(your_fcn_name(t),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":2439180,"edited_by":2439180,"edited_at":"2022-07-13T19:07:25.000Z","deleted_by":null,"deleted_at":null,"solvers_count":37,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-07-13T19:07:08.000Z","updated_at":"2026-02-08T05:29:58.000Z","published_at":"2022-07-13T19:07:25.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind distance travelled by an object starting from rest in time 't' with linear acceleration a = 3t. You are given time t as an input to the function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61181,"title":"Compute braking force using vehicle mass and acceleration.","description":"Compute braking force required to stop a vehicle of mass 'm' and with acceleration 'a' \r\nRemember:  F = m × a.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 25.5px; transform-origin: 407px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCompute braking force required to stop a vehicle of mass 'm' and with acceleration 'a' \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eRemember:  F = m × a.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function F = brakingForce(m,a)\r\nF = 0;\r\nend\r\n","test_suite":"%%\r\nassert(isequal(brakingForce(1000,5),5000))\r\n\r\n%%\r\nassert(isequal(brakingForce(0,10),0))\r\n\r\n%%\r\nassert(isequal(brakingForce(1500,3),4500))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-02-02T05:31:40.000Z","deleted_by":null,"deleted_at":null,"solvers_count":43,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T05:09:13.000Z","updated_at":"2026-04-02T00:32:17.000Z","published_at":"2026-02-02T05:25:08.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCompute braking force required to stop a vehicle of mass 'm' and with acceleration 'a' \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember:  F = m × a.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":47113,"title":"Distance Travelled by Vehicle","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 101.2px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 50.6px; transform-origin: 407px 50.6px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 41.6px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 20.8px; text-align: left; transform-origin: 384px 20.8px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven a vehicle travelling at a velocity of 10m/s and having a constant acceleration of 5m/s^2, write a function that gives the distance travelled by the vehicle in time t.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.8px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.4px; text-align: left; transform-origin: 384px 10.4px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eUnits of distance is m and time sec.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.8px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.4px; text-align: left; transform-origin: 384px 10.4px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eHint:  Remember Newton\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function dist = d_in_t(t)\r\n  dist = t;\r\nend","test_suite":"%%\r\nt = 1;\r\ny_correct = 12.5;\r\nassert(isequal(d_in_t(t),y_correct))\r\n%%\r\nt = 5;\r\ny_correct = 112.5;\r\nassert(isequal(d_in_t(t),y_correct))\r\n%%\r\nt = 10;\r\ny_correct = 350;\r\nassert(isequal(d_in_t(t),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":511890,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":89,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-28T08:21:47.000Z","updated_at":"2026-02-05T15:52:02.000Z","published_at":"2020-10-28T08:21:47.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a vehicle travelling at a velocity of 10m/s and having a constant acceleration of 5m/s^2, write a function that gives the distance travelled by the vehicle in time t.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eUnits of distance is m and time sec.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHint:  Remember Newton\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":45909,"title":"Convert Angstrom to Meters","description":"Write a code that converts the angstrom unit to meters.(A is angstrom and m is meters.)","description_html":"\u003cp\u003eWrite a code that converts the angstrom unit to meters.(A is angstrom and m is meters.)\u003c/p\u003e","function_template":"function m = conv_fcn_met(A)\r\n  m = ;\r\nend","test_suite":"%%\r\nA = 1;\r\nm_correct = 10^-10;\r\nassert(isequal(conv_fcn_met(A),m_correct))\r\n\r\n%%\r\nA = 0;\r\nm_correct = 0;\r\nassert(isequal(conv_fcn_met(A),m_correct))\r\n\r\n%%\r\nA = 10;\r\nm_correct = 10^-9;\r\nassert(isequal(conv_fcn_met(A),m_correct))\r\n\r\n%%\r\nA = 400;\r\nm_correct = 4*10^-8 ;\r\nassert(isequal(conv_fcn_met(A),m_correct))\r\n\r\n%%\r\nA = 30000;\r\nm_correct = 3*10^-6;\r\nassert(isequal(conv_fcn_met(A),m_correct))\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":444624,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":102,"test_suite_updated_at":"2020-06-13T17:36:05.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-06-13T17:27:41.000Z","updated_at":"2026-02-06T10:07:54.000Z","published_at":"2020-06-13T17:27:39.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a code that converts the angstrom unit to meters.(A is angstrom and m is meters.)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1360,"title":"Special Relativity 101.","description":"Special relativity states that the effective mass of an object varies as a function of its velocity. If *c* is the speed of light (c approx. = 300,000 km/s) and *v* is the velocity of the object (in km/s), find the effective mass m' of an object traveling at a velocity v. Assume that at v = 0 m/s, m = 1 kg.","description_html":"\u003cp\u003eSpecial relativity states that the effective mass of an object varies as a function of its velocity. If \u003cb\u003ec\u003c/b\u003e is the speed of light (c approx. = 300,000 km/s) and \u003cb\u003ev\u003c/b\u003e is the velocity of the object (in km/s), find the effective mass m' of an object traveling at a velocity v. Assume that at v = 0 m/s, m = 1 kg.\u003c/p\u003e","function_template":"function mprime = specialRelativity(v)\r\n  mprime = v;\r\nend","test_suite":"%%\r\nv = 0;\r\ny_correct = 1;\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 1000;      % km/s\r\ny_correct = 1; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 10000;          % km/s\r\ny_correct = 1.0006; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 50000;          % km/s\r\ny_correct = 1.0142; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 100000;         % km/s\r\ny_correct = 1.0607; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 200000;         % km/s\r\ny_correct = 1.3416; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 250000;         % km/s\r\ny_correct = 1.8091; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 290000;         % km/s\r\ny_correct = 3.9057; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 299000;          % km/s\r\ny_correct = 12.2577; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 299900;          % km/s\r\ny_correct = 38.7331; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)\r\n\r\n%%\r\nv = 299999;           % km/s\r\ny_correct = 387.2987; % kg\r\nassert(abs(specialRelativity(v)-y_correct) \u003c= 0.0001)","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":810,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":112,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-03-19T00:59:56.000Z","updated_at":"2026-02-06T11:57:49.000Z","published_at":"2013-03-19T01:00:25.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSpecial relativity states that the effective mass of an object varies as a function of its velocity. If\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ec\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is the speed of light (c approx. = 300,000 km/s) and\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ev\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is the velocity of the object (in km/s), find the effective mass m' of an object traveling at a velocity v. Assume that at v = 0 m/s, m = 1 kg.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":53059,"title":"Siren frequency and Doppler effect.","description":"The Doppler effect is described on OpenStax University Physics at https://openstax.org/books/university-physics-volume-1/pages/17-7-the-doppler-effect and in other sources.  \r\nConsider the  Doppler effect for sound waves travelling in air.  Use the equations in the OpenStax source (or equivalent information ) to model the Doppler effect. \r\nA moving vehicle with a speed u, having a siren frequency, fs, approaches a static (fixed)  observer and then passes the static observer.   A siren , in this context,  is also called a horn.  The vehicle motion is modelled as straight-line motion. \r\nOne way of summarising the effect to the formula for two frequencies\r\n  \r\nor written in MATLAB syntax as\r\nfh = fs *(c/(c-u)) \r\nfl = fs *(c/(c+u)) \r\nwhere fs is the frequency of a siren in Hz,  c is the  speed of sound in m/s , u is the speed of the moving vehicle in m/s,  fh is the higher frequency in Hz as the vehicle approaches the  stationary observer and the fl the lower frequency  in Hz as the vehicle recedes from (passes) the observer. \r\nCalculate the siren frequency, fs, to the nearest Hz.  The function definition is \r\nfs = findSirenFrequency ( c, u, fh, fl )\r\nFor example, if  c = 345  m/s  ; u= 30.5556 m/s ;  fh = 877  Hz and fl =734 Hz   then fs= 799 Hz.   Assume  fh ≥ fl and c \u003e u.\r\n ","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 502.667px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 251.333px; transform-origin: 406.5px 251.333px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 41.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 20.6667px; text-align: left; transform-origin: 383.5px 20.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThe Doppler effect is described on OpenStax University Physics at \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://openstax.org/books/university-physics-volume-1/pages/17-7-the-doppler-effect\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ehttps://openstax.org/books/university-physics-volume-1/pages/17-7-the-doppler-effect\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e and in other sources.  \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 41.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 20.6667px; text-align: left; transform-origin: 383.5px 20.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eConsider the  Doppler effect for sound waves travelling in air.  Use the equations in the OpenStax source (or equivalent information ) to model the Doppler effect. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 41.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 20.6667px; text-align: left; transform-origin: 383.5px 20.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eA moving vehicle with a speed \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eu\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e, having a siren frequency, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efs,\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e approaches a static (fixed)  observer and then passes the static observer.   A siren , in this context,  is also called a horn.  The vehicle motion is modelled as straight-line motion. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.3333px; text-align: left; transform-origin: 383.5px 10.3333px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eOne way of summarising the effect to the formula for two frequencies\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.3333px; text-align: center; transform-origin: 383.5px 10.3333px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e  \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.3333px; text-align: left; transform-origin: 383.5px 10.3333px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eor written in MATLAB syntax as\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.6667px; text-align: left; transform-origin: 383.5px 10.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003efh = fs *(c/(c-u)) \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.6667px; text-align: left; transform-origin: 383.5px 10.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003efl = fs *(c/(c+u)) \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 62px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 31px; text-align: left; transform-origin: 383.5px 31px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ewhere \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efs \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eis the frequency of a siren in Hz,  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ec \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eis the  speed of sound in m/s , \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eu \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eis the speed of the moving vehicle in m/s,  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efh\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e is the higher frequency in Hz as the vehicle approaches the  stationary observer and the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efl\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e the lower frequency  in Hz as the vehicle recedes from (passes) the observer. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.3333px; text-align: left; transform-origin: 383.5px 10.3333px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eCalculate the siren frequency, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efs\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"text-decoration: underline; text-decoration-line: underline; \"\u003eto the nearest Hz.\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e  The function definition is \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.6667px; text-align: left; transform-origin: 383.5px 10.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003efs = findSirenFrequency ( c, u, fh, fl )\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 41.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 20.6667px; text-align: left; transform-origin: 383.5px 20.6667px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor example, if  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ec\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e = 345  m/s  ; \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eu\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e= 30.5556 m/s ;  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efh\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e = 877  Hz and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efl \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e=734 Hz   then \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efs\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e= 799 Hz.   Assume  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efh\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e ≥ \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003efl\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ec\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e \u0026gt; \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eu\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.3333px; text-align: left; transform-origin: 383.5px 10.3333px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function  fs = findSirenFrequency ( c, u, fh, fl )\r\n \r\n  fs=1;\r\n  \r\nend\r\n\r\n\r\n","test_suite":"%testdopp2\r\n \r\n%%\r\n%T1\r\nc = 345 ; u = 30.5556    ; fh  = 877 ;   fl =  734;\r\nfs=findSirenFrequency ( c, u, fh, fl );\r\nfs_correct = 799;\r\n%fs_correct = 801; %incorrect value should cause assert to fail.\r\ndelta=1 ; % One Hz plus or minus tolerance on answer \r\nassert(and( ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003e= fs_correct-delta , ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003c= fs_correct+delta   ...\r\n          ) == 1 ) \r\n      \r\n \r\n%%\r\n%T2      \r\nc = 335 ; u = 12.8846    ; fh  = 208 ;   fl =  193;\r\nfs=findSirenFrequency ( c, u, fh, fl );\r\nfs_correct= 200 ;\r\n%fs_correct= 322 ;\r\ndelta=1;  % One Hz plus or minus tolerance on answer \r\nassert(and( ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003e= fs_correct-delta , ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003c= fs_correct+delta   ...\r\n          ) == 1 ) \r\n \r\n%%      \r\n%T3\r\n%Test 3\r\nc = 228.9596 ; u = 111    ; fh  = 1941 ;   fl =  674;\r\nfs_correct= 1000 ;\r\n%fs_correct= 2000; %incorrect value should cause assert to fail.\r\nfs=findSirenFrequency ( c, u, fh, fl );\r\ndelta=1 ; % One Hz plus or minus tolerance on answer \r\nassert(and( ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003e= fs_correct-delta , ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003c= fs_correct+delta   ...\r\n          ) == 1 ) \r\n \r\n%%\r\n%T4   \r\nc = 335 ; u = 0    ; fh  = 333 ;   fl =  333;\r\nfs_correct= 333 ;\r\n% fs_correct= 444 ; %incorrect value should cause assert to fail.\r\nfs=findSirenFrequency ( c, u, fh, fl );\r\ndelta=1 ;% One Hz plus or minus tolerance on answer \r\nassert(and( ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003e= fs_correct-delta , ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003c= fs_correct+delta   ...\r\n          ) == 1 ) \r\n      \r\n%%\r\n%T5\r\nc = 339.0047 ; u = 200    ; fh  = 6097 ;   fl =  1572;\r\nfs_correct= 2500; \r\n%fs_correct= 232 ; %incorrect value should cause assert to fail.\r\nfs=findSirenFrequency ( c, u, fh, fl );\r\ndelta=1;  % One Hz plus or minus tolerance on answer \r\nassert(and( ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003e= fs_correct-delta , ...\r\n       findSirenFrequency ( c, u, fh, fl )\u003c= fs_correct+delta   ...\r\n          ) == 1 ) \r\n      \r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":1330792,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":30,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-11-14T02:51:12.000Z","updated_at":"2026-02-24T10:07:29.000Z","published_at":"2021-11-14T02:56:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Doppler effect is described on OpenStax University Physics at \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://openstax.org/books/university-physics-volume-1/pages/17-7-the-doppler-effect\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ehttps://openstax.org/books/university-physics-volume-1/pages/17-7-the-doppler-effect\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e and in other sources.  \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eConsider the  Doppler effect for sound waves travelling in air.  Use the equations in the OpenStax source (or equivalent information ) to model the Doppler effect. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA moving vehicle with a speed \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eu\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, having a siren frequency, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efs,\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e approaches a static (fixed)  observer and then passes the static observer.   A siren , in this context,  is also called a horn.  The vehicle motion is modelled as straight-line motion. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOne way of summarising the effect to the formula for two frequencies\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"center\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e  \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eor written in MATLAB syntax as\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efh = fs *(c/(c-u)) \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efl = fs *(c/(c+u)) \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ewhere \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efs \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eis the frequency of a siren in Hz,  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ec \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eis the  speed of sound in m/s , \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eu \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eis the speed of the moving vehicle in m/s,  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efh\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is the higher frequency in Hz as the vehicle approaches the  stationary observer and the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efl\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e the lower frequency  in Hz as the vehicle recedes from (passes) the observer. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the siren frequency, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efs\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:u/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eto the nearest Hz.\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e  The function definition is \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efs = findSirenFrequency ( c, u, fh, fl )\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example, if  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ec\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 345  m/s  ; \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eu\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e= 30.5556 m/s ;  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efh\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 877  Hz and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efl \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e=734 Hz   then \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efs\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e= 799 Hz.   Assume  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efh\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e ≥ \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efl\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ec\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u0026gt; \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eu\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61188,"title":"Compute optimal regenerative and friction brake torque blending.","description":"Electric and hybrid vehicles combine regenerative braking with traditional friction braking to maximize energy recovery while ensuring safety.\r\nGiven total braking torque demand and maximum regenerative torque capability, compute how braking effort should be split between regenerative and friction braking.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 93px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 46.5px; transform-origin: 407px 46.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eElectric and hybrid vehicles combine regenerative braking with traditional friction braking to maximize energy recovery while ensuring safety.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven total braking torque demand and maximum regenerative torque capability, compute how braking effort should be split between regenerative and friction braking.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [Tregen, Tfric] = brakeBlending(T_total, Tregen_max)\r\nTregen = 0; Tfric = 0;\r\nend\r\n","test_suite":"%%\r\nT_total = 300; Tregen_max = 200;\r\n[Tregen,Tfric] = brakeBlending(T_total,Tregen_max);\r\nassert(isequal([Tregen Tfric],[200 100]))\r\n\r\n%%\r\nT_total = 150; Tregen_max = 200;\r\n[Tregen,Tfric] = brakeBlending(T_total,Tregen_max);\r\nassert(isequal([Tregen Tfric],[150 0]))\r\n\r\n%%\r\nT_total = 0; Tregen_max = 200;\r\n[Tregen,Tfric] = brakeBlending(T_total,Tregen_max);\r\nassert(isequal([Tregen Tfric],[0 0]))\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2305225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":32,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T07:28:49.000Z","updated_at":"2026-03-31T16:49:25.000Z","published_at":"2026-02-02T07:28:49.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eElectric and hybrid vehicles combine regenerative braking with traditional friction braking to maximize energy recovery while ensuring safety.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven total braking torque demand and maximum regenerative torque capability, compute how braking effort should be split between regenerative and friction braking.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":47420,"title":"Falling on the Moon.","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 41.6px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 331.5px 20.8px; transform-origin: 331.5px 20.8px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 308.5px 20.8px; text-align: left; transform-origin: 308.5px 20.8px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eA stone of mass \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"53.5\" height=\"18\" style=\"width: 53.5px; height: 18px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e is dropped on the moon from a height \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral, STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003eh\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e. Given a gravity force \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"84.5\" height=\"18.5\" style=\"width: 84.5px; height: 18.5px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e , find the time \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral, STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003et\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e it takes to reach the ground.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function t = your_fcn_name(h)\r\n  t = [];\r\nend","test_suite":"%%\r\nh = 1.5;\r\ny_correct = 1.3608;\r\nassert(isequal(round(your_fcn_name(h),4), y_correct))\r\n%%\r\nh = 2.0;\r\ny_correct = 1.5713;\r\nassert(isequal(round(your_fcn_name(h),4), y_correct))","published":true,"deleted":false,"likes_count":3,"comments_count":5,"created_by":514092,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":52,"test_suite_updated_at":"2020-11-08T12:08:05.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-11-07T18:58:53.000Z","updated_at":"2026-02-13T18:26:21.000Z","published_at":"2020-11-07T18:58:53.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA stone of mass \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003em = 1kg\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is dropped on the moon from a height \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eh\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e. Given a gravity force \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eg = 1.62 m/s^2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e , find the time \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003et\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e it takes to reach the ground.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":49825,"title":"Angular Velocity","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven a value of velocity or a set of velocities (in a vector or matrix form) and the radius, determine the corresponding angular velocity in a circular motion.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function omega = ang_vel(v,r)\r\n  omega = alpha*v + pi*r^2;\r\nend","test_suite":"%%\r\nv=2728;\r\nr=17;\r\nv_cor=160.4706;\r\nassert(isequal(ang_vel(v,r),v_cor))\r\n%%\r\nv=[1 2 4;3 7 8];\r\nr=pi;\r\nv_cor=[0.3183 0.6366 1.2732; 0.9549 2.2282 2.5465];\r\nassert(isequal(ang_vel(v,r),v_cor))\r\n%%\r\nv=primes(19);\r\nr=sqrt(3);\r\nv_cor=[1.1547 1.7321 2.8868 4.0415 6.3509 7.5056 9.8150 10.9697];\r\nassert(isequal(ang_vel(v,r),v_cor))\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":180632,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":52,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-01-15T15:29:09.000Z","updated_at":"2026-02-19T14:19:41.000Z","published_at":"2021-01-15T15:29:09.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a value of velocity or a set of velocities (in a vector or matrix form) and the radius, determine the corresponding angular velocity in a circular motion.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":55190,"title":"Momentum Calculation","description":"A shopping cart of mass 'm1' is traveling with velocity 'u' and collides with a second shopping cart of mass 'm2.' The two shopping carts move together after the collision. Find their final velocity.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(232, 230, 227); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(232, 230, 227); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eA shopping cart of mass 'm1' is traveling with velocity 'u' and collides with a second shopping cart of mass 'm2.' The two shopping carts move together after the collision. Find their final velocity.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function v = your_fcn_name(m1, m2, u)\r\n  v = u;\r\nend","test_suite":"%%\r\nm1 = 1; m2 = 1; u = 1\r\ny_correct = 0.5;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 2; m2 = 1; u = 2\r\ny_correct = 4/3;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 2; m2 = 3; u = 4\r\ny_correct = 8/5;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 3; m2 = 5; u = 4\r\ny_correct = 1.5;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 7; m2 = 2; u = 2\r\ny_correct = 14/9;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 24; m2 = 3; u = 2\r\ny_correct = 48/27;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 5; m2 = 4; u = 4\r\ny_correct = 20/9;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%\r\nm1 = 6; m2 = 3; u = 1\r\ny_correct = 2/3;\r\nassert(isequal(your_fcn_name(m1, m2, u),y_correct))\r\n%%","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2453225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":76,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-07-13T20:36:34.000Z","updated_at":"2026-02-17T08:20:35.000Z","published_at":"2022-07-13T20:36:34.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA shopping cart of mass 'm1' is traveling with velocity 'u' and collides with a second shopping cart of mass 'm2.' The two shopping carts move together after the collision. Find their final velocity.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":45522,"title":"Electric Flux","description":"Calculate the flux passing through a surface.\r\nE is electric field, A is area.","description_html":"\u003cp\u003eCalculate the flux passing through a surface.\r\nE is electric field, A is area.\u003c/p\u003e","function_template":"function Flux = electric_fcn_flux(E,A)\r\n  Flux = ;\r\nend","test_suite":"%%\r\nE = 0;\r\nA = 10;\r\nFlux_correct = 0;\r\nassert(isequal(electric_fcn_flux(E,A),Flux_correct))\r\n\r\n%%\r\nE = 2;\r\nA = 10;\r\nFlux_correct = 20;\r\nassert(isequal(electric_fcn_flux(E,A),Flux_correct))\r\n\r\n%%\r\nE = 5;\r\nA = 10;\r\nFlux_correct = 50;\r\nassert(isequal(electric_fcn_flux(E,A),Flux_correct))\r\n\r\n%%\r\nE = 10;\r\nA = 10;\r\nFlux_correct = 100;\r\nassert(isequal(electric_fcn_flux(E,A),Flux_correct))\r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":444624,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":78,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-05-17T13:38:58.000Z","updated_at":"2026-02-10T08:26:09.000Z","published_at":"2020-05-17T13:38:58.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the flux passing through a surface. E is electric field, A is area.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":49713,"title":"Ohmic Heating","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 25.5px; transform-origin: 407.5px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 42.0083px 7.7px; transform-origin: 42.0083px 7.7px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFind Power P\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 103.475px 7.7px; transform-origin: 103.475px 7.7px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ewith Voltage V and resistance (R)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = H(V,R)\r\n  y = x;\r\nend","test_suite":"%%\r\nV= 1;R=5;\r\ny_correct = 0.2000;\r\nassert(isequal(H(V,R),y_correct))\r\n%%\r\nV= 50;R=45;\r\ny_correct =  55.5556;\r\nassert(isequal(H(V,R),y_correct))\r\n%%\r\nV= 1100;R=55;\r\ny_correct = 22000;\r\nassert(isequal(H(V,R),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":610936,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-31T03:20:57.000Z","updated_at":"2026-02-10T08:46:34.000Z","published_at":"2020-12-31T03:46:00.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind Power P\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ewith Voltage V and resistance (R)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":49830,"title":"Period of a pendulum","description":"Consider a small object hanging on a massless thread and pulled back from equilibrium at a small angle. Assuming that the pivot point is frictionless as well as no drag, determine the period of the movement of the pendulum given the length of the thread. Please use a gravitational constant of 9.8067 m/s^2.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 63px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 31.5px; transform-origin: 407px 31.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 376.5px 8px; transform-origin: 376.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eConsider a small object hanging on a massless thread and pulled back from equilibrium at a small angle. Assuming that the pivot point is frictionless as well as no drag, determine the period of the movement of the pendulum given the length of the thread. Please use a gravitational constant of 9.8067 m/s^2.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function T = pendulum(L)\r\n  T = L^(1/3)*g;\r\nend","test_suite":"%%\r\nL=10;\r\nT_corr=6.3448;\r\nassert(isequal(pendulum(L),T_corr))\r\n%%\r\nL=primes(10);\r\nT_corr=[2.8375 3.4752 4.4865 5.3084];\r\nassert(isequal(pendulum(L),T_corr))\r\n%%\r\nL=pi;\r\nT_corr=3.5563;\r\nassert(isequal(pendulum(L),T_corr))\r\n%%\r\nL=9.8067/pi^2;\r\nT_corr=2;\r\nassert(isequal(pendulum(L),T_corr))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":180632,"edited_by":223089,"edited_at":"2022-06-02T19:39:27.000Z","deleted_by":null,"deleted_at":null,"solvers_count":40,"test_suite_updated_at":"2022-06-02T19:39:27.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2021-01-15T16:08:56.000Z","updated_at":"2026-02-12T12:15:02.000Z","published_at":"2021-01-15T16:08:56.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eConsider a small object hanging on a massless thread and pulled back from equilibrium at a small angle. Assuming that the pivot point is frictionless as well as no drag, determine the period of the movement of the pendulum given the length of the thread. Please use a gravitational constant of 9.8067 m/s^2.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":8058,"title":"Kinetic Energy","description":"Given the mass m and velocity v of an object, determine its \u003chttp://en.wikipedia.org/wiki/Kinetic_energy kinetic energy\u003e.","description_html":"\u003cp\u003eGiven the mass m and velocity v of an object, determine its \u003ca href = \"http://en.wikipedia.org/wiki/Kinetic_energy\"\u003ekinetic energy\u003c/a\u003e.\u003c/p\u003e","function_template":"function y = kinetic_energy(m,v)\r\n  y = x;\r\nend","test_suite":"%%\r\nm = 20;\r\nv = 25\r\ny_correct = 6250;\r\nassert(isequal(kinetic_energy(m,v),y_correct))\r\n\r\n%%\r\nm = 1;\r\nv = 4;\r\ny_correct = 8;\r\nassert(isequal(kinetic_energy(m,v),y_correct))\r\n\r\n%%\r\nm = 6;\r\nv = 9;\r\ny_correct = 243;\r\nassert(isequal(kinetic_energy(m,v),y_correct))","published":true,"deleted":false,"likes_count":6,"comments_count":2,"created_by":33703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":388,"test_suite_updated_at":"2015-04-09T15:52:31.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2015-04-02T15:31:28.000Z","updated_at":"2026-02-11T11:51:30.000Z","published_at":"2015-04-02T15:31:27.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven the mass m and velocity v of an object, determine its\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Kinetic_energy\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ekinetic energy\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":54895,"title":"determine skid distance of car","description":"Determine the distance a car skids to a stop given initial velocity (v) and time (t).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eDetermine the distance a car skids to a stop given initial velocity (v) and time (t).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function d = skid_distance(v,t)\r\n  d = v;\r\nend","test_suite":"%%\r\nv = 22.4;\r\nt = 2.55;\r\ny_correct = 28.56;\r\ntolerance = 1e-12;\r\nassert(abs(skid_distance(v,t)-y_correct)\u003ctolerance)\r\n%%\r\nv = 26.8;\r\nt = 5.1;\r\ny_correct = 68.34;\r\ntolerance = 1e-12;\r\nassert(abs(skid_distance(v,t)-y_correct)\u003ctolerance)","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2457130,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":39,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-07-12T15:13:33.000Z","updated_at":"2026-02-12T12:28:20.000Z","published_at":"2022-07-12T15:13:33.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDetermine the distance a car skids to a stop given initial velocity (v) and time (t).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":58319,"title":"Calculate the Voltage Through a Step-Up Transformer","description":"Given a step-up transformer has a primary coil with A number loops, a secondary coil with B number loops, and a primary voltage of 12 volts. What is the secondary voltage in each transformer?","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 21px; transform-origin: 407.5px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 21px; text-align: left; transform-origin: 384.5px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven a step-up transformer has a primary coil with A number loops, a secondary coil with B number loops, and a primary voltage of 12 volts. What is the secondary voltage in each transformer?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function V_s = SecVolt(A,B)\r\n  V_s = ;\r\nend","test_suite":"%%\r\nA = 30;\r\nB = 75;\r\nassert(isequal(SecVolt(A,B),30))\r\n%%\r\nA = 20;\r\nB = 40;\r\nassert(isequal(SecVolt(A,B),24))\r\n%%\r\nA = 40;\r\nB = 90;\r\nassert(isequal(SecVolt(A,B),27))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":3227359,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":72,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-05-17T17:08:40.000Z","updated_at":"2026-02-16T11:59:58.000Z","published_at":"2023-05-17T17:08:40.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a step-up transformer has a primary coil with A number loops, a secondary coil with B number loops, and a primary voltage of 12 volts. What is the secondary voltage in each transformer?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":43065,"title":"Energy of an object","description":"Calculate the total mechanical energy of an object.\r\n\r\nTotal Energy= Potential energy + Kinetic energy\r\n\r\nP.E.=m*g*h\r\n\r\nK.E.=1/2*m*v^2\r\n\r\ng=9.8m/s^2","description_html":"\u003cp\u003eCalculate the total mechanical energy of an object.\u003c/p\u003e\u003cp\u003eTotal Energy= Potential energy + Kinetic energy\u003c/p\u003e\u003cp\u003eP.E.=m*g*h\u003c/p\u003e\u003cp\u003eK.E.=1/2*m*v^2\u003c/p\u003e\u003cp\u003eg=9.8m/s^2\u003c/p\u003e","function_template":"function y = te(m,h,v)\r\n  y = x;\r\nend","test_suite":"%%\r\nm=1;\r\nh=10;\r\nv=2;\r\ny_correct = 100;\r\nassert(isequal(te(m,h,v),y_correct))\r\n\r\n%%\r\nm=10;\r\nh=10;\r\nv=2;\r\ny_correct = 1000;\r\nassert(isequal(te(m,h,v),y_correct))\r\n\r\n%%\r\nm=1;\r\nh=10;\r\nv=20;\r\ny_correct = 298;\r\nassert(isequal(te(m,h,v),y_correct))\r\n","published":true,"deleted":false,"likes_count":8,"comments_count":0,"created_by":91311,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":458,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-05T15:51:12.000Z","updated_at":"2026-04-03T16:21:54.000Z","published_at":"2016-10-05T15:51:12.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the total mechanical energy of an object.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTotal Energy= Potential energy + Kinetic energy\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eP.E.=m*g*h\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eK.E.=1/2*m*v^2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eg=9.8m/s^2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2311,"title":"Vector Magnitude Calculator","description":"'a' is a vector that starts at the origin and ends at (x, y). Find ||a||.\r\n\r\nHint: It is as simple as \"ABC\".","description_html":"\u003cp\u003e'a' is a vector that starts at the origin and ends at (x, y). Find \u003ctt\u003e|a|\u003c/tt\u003e.\u003c/p\u003e\u003cp\u003eHint: It is as simple as \"ABC\".\u003c/p\u003e","function_template":"function m = vector_magnitude(x, y)\r\n  m = x;\r\nend","test_suite":"%%\r\nx = 5;\r\ny = 12;\r\nmm = 13;\r\nassert(isequal(vector_magnitude(x, y),mm))\r\n\r\n%%\r\nx = 3;\r\ny = 4;\r\nmm = 5;\r\nassert(isequal(vector_magnitude(x, y),mm))\r\n\r\n%%\r\nx = 12;\r\ny = 35;\r\nmm = 37;\r\nassert(isequal(vector_magnitude(x, y),mm))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":26349,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":167,"test_suite_updated_at":"2014-06-05T15:55:43.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-05-07T19:54:35.000Z","updated_at":"2026-02-18T09:28:19.000Z","published_at":"2014-05-07T19:54:35.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'a' is a vector that starts at the origin and ends at (x, y). Find\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e|a\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e|.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHint: It is as simple as \\\"ABC\\\".\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61187,"title":"Estimate brake disc temperature rise during braking.","description":"During braking, kinetic energy is converted into thermal energy, causing brake discs to heat up. Excessive temperature rise can lead to brake fade and reduced braking effectiveness.\r\nGiven braking energy absorbed by the disc, disc mass, and material heat capacity, estimate the resulting temperature increase.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 93px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 46.5px; transform-origin: 407px 46.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eDuring braking, kinetic energy is converted into thermal energy, causing brake discs to heat up. Excessive temperature rise can lead to brake fade and reduced braking effectiveness.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven braking energy absorbed by the disc, disc mass, and material heat capacity, estimate the resulting temperature increase.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function dT = brakeDiscTempRise(E, m, Cp)\r\ndT = 0;\r\nend\r\n","test_suite":"%%\r\nE = 150000; m = 7; Cp = 500;\r\ndT_correct = 42.8571;\r\nassert(abs(brakeDiscTempRise(E,m,Cp)-dT_correct) \u003c 1e-3)\r\n\r\n%%\r\nE = 100000; m = 5; Cp = 450;\r\ndT_correct = 44.4444;\r\nassert(abs(brakeDiscTempRise(E,m,Cp)-dT_correct) \u003c 1e-3)\r\n\r\n%%\r\nE = 0; m = 6; Cp = 500;\r\ndT_correct = 0;\r\nassert(isequal(brakeDiscTempRise(E,m,Cp),dT_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":37,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T07:26:30.000Z","updated_at":"2026-03-31T16:47:57.000Z","published_at":"2026-02-02T07:26:30.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDuring braking, kinetic energy is converted into thermal energy, causing brake discs to heat up. Excessive temperature rise can lead to brake fade and reduced braking effectiveness.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven braking energy absorbed by the disc, disc mass, and material heat capacity, estimate the resulting temperature increase.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":58832,"title":"Find the Peak Particle Velocity on a ETL structure","description":"PPV is a vibration parameter that can connect stress to a structure, it is measured in mm/s or mm/s-1. The higher the PPV the more stress to the structure. Common practices in power industries are to limit ground motion by specifying the maximum peak particle velocity (PPV). Electrical Tranmission Line (ETL) Structure's maximum PPV without having any damage to the structure is around 50.8mm/s.\r\nThere are many different equations for PPV, but all generally have the same variables. 2 site constants and 2 unknowns.\r\nUse this equation to calculate PPV with k \u0026 e being the default site constants:\r\nPPV = k(D/sqrt(Q) )^(-e)\r\nk = 185\r\ne = 1.2\r\nD = distance from blast to structure (m)\r\nQ = Charge of mass per delay (kg)\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 324px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 162px; transform-origin: 407.5px 162px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 42px; text-align: left; transform-origin: 384.5px 42px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ePPV is a vibration parameter that can connect stress to a structure, it is measured in mm/s or mm/s-1. The higher the PPV the more stress to the structure. Common practices in power industries are to limit ground motion by specifying the maximum peak particle velocity (PPV). Electrical Tranmission Line (ETL) Structure's maximum PPV without having any damage to the structure is around 50.8mm/s.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThere are many different equations for PPV, but all generally have the same variables. 2 site constants and 2 unknowns.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eUse this equation to calculate PPV with k \u0026amp; e being the default site constants:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ePPV = k(D/sqrt(Q) )^(-e)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ek = 185\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ee = 1.2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eD = distance from blast to structure (m)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eQ = Charge of mass per delay (kg)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = PPV(D,Q)\r\ny = ...\r\nend","test_suite":"%%\r\nD = 60\r\nQ = 500\r\ny_correct = 56.6;\r\nassert(isequal(PPV(D,Q),y_correct))\r\n%%\r\nD = 100\r\nQ = 1000\r\ny_correct = 46.5;\r\nassert(isequal(PPV(D,Q),y_correct))\r\n%%\r\nD = 200\r\nQ = 3000\r\ny_correct = 39.1;\r\nassert(isequal(PPV(D,Q),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":3,"created_by":3227359,"edited_by":3227359,"edited_at":"2023-08-09T12:12:17.000Z","deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-08-08T16:17:14.000Z","updated_at":"2026-03-02T09:14:51.000Z","published_at":"2023-08-08T16:19:19.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePPV is a vibration parameter that can connect stress to a structure, it is measured in mm/s or mm/s-1. The higher the PPV the more stress to the structure. Common practices in power industries are to limit ground motion by specifying the maximum peak particle velocity (PPV). Electrical Tranmission Line (ETL) Structure's maximum PPV without having any damage to the structure is around 50.8mm/s.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere are many different equations for PPV, but all generally have the same variables. 2 site constants and 2 unknowns.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eUse this equation to calculate PPV with k \u0026amp; e being the default site constants:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePPV = k(D/sqrt(Q) )^(-e)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ek = 185\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ee = 1.2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eD = distance from blast to structure (m)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eQ = Charge of mass per delay (kg)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":49698,"title":"Find the magnetic field around the wire","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 79.44px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 39.72px; transform-origin: 406.5px 39.72px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.48px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.24px; text-align: left; transform-origin: 383.5px 10.24px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind the magnetic field around the wire\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.48px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.24px; text-align: left; transform-origin: 383.5px 10.24px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003er=radius\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.48px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.24px; text-align: left; transform-origin: 383.5px 10.24px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eI=current\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = EF(I,r)\r\n  y = x;\r\nend","test_suite":"%%\r\nI=3;r=3\r\ny_correct =  2e-07;\r\nassert(abs(EF(I,r)-y_correct)\u003c0.00000001)\r\n%%\r\nI=2;r=5;\r\ny_correct =   8e-08;\r\nassert(abs(EF(I,r)-y_correct)\u003c0.0000001)\r\n%%\r\nI=5;r=6;\r\ny_correct =  1.66666e-07;\r\nassert(abs(EF(I,r)-y_correct)\u003c0.0000001)","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":610936,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":26,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-31T03:15:27.000Z","updated_at":"2026-02-17T09:16:02.000Z","published_at":"2020-12-31T03:43:39.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind the magnetic field around the wire\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003er=radius\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eI=current\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":2215,"title":"Power supply: 230V to 115V","description":"The problem is simple: we have a wall outlet which supplies 230V and an apparatus that requires 115V.\r\n\r\nSoftware is always cheaper than hardware (well, most of the time), so we solve this with a program, a Matlab function, to be precise.\r\n\r\nWrite a program that converts the supplied input voltage to the required output voltage.\r\n\r\n*If you like this problem, please like it (after solving).*","description_html":"\u003cp\u003eThe problem is simple: we have a wall outlet which supplies 230V and an apparatus that requires 115V.\u003c/p\u003e\u003cp\u003eSoftware is always cheaper than hardware (well, most of the time), so we solve this with a program, a Matlab function, to be precise.\u003c/p\u003e\u003cp\u003eWrite a program that converts the supplied input voltage to the required output voltage.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIf you like this problem, please like it (after solving).\u003c/b\u003e\u003c/p\u003e","function_template":"function V_out = transformer(V_in)\r\n  N_primary = 5432; % Number of windings on primary coil.\r\n  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vÊÔÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÆÆÆÆÆÆÆÆÆÆÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÖ¿  ·;¬÷²¸   ¦ÊÅÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÆÆÆÆÆÆÆÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ·  ·*42/\u0026bî^:¿ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÆÆÆÆÆÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ:´-ÊÊÊÊÊÊÖÔ^  ½ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÆÆËÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ· :ëÊÊÊÊÊʬ  PÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ   ²ÞÊÊÊÊÝ  WÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÉ    {ÊÊÊʲ ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÅ   ¹ÊÊÊÊÊ:ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊg  µÊÊÊÊËÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('ÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ8·gÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊÊ');\r\ndisp('Is this problem a hair-raiser?');\r\nend\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\n% On request of Ned Gulley, some extra testcases (for the, hopefully, stable voltage regulator within the input voltage range specified on the box).\r\nassert(isequal(transformer(173),115))\r\nassert(isequal(transformer(225),115))\r\nassert(isequal(transformer(145),115))\r\nassert(isequal(transformer(238),115))\r\nassert(isequal(transformer(163),115))\r\nassert(isequal(transformer(128),115))\r\nassert(isequal(transformer(216),115))\r\nassert(isequal(transformer(164),115))\r\nassert(isequal(transformer(136),115))\r\nassert(isequal(transformer(156),115))\r\nassert(isequal(transformer(166),115))\r\nassert(isequal(transformer(132),115))\r\nassert(isequal(transformer(162),115))\r\nassert(isequal(transformer(227),115))\r\nassert(isequal(transformer(203),115))\r\nassert(isequal(transformer(168),115))\r\nassert(isequal(transformer(174),115))\r\nassert(isequal(transformer(170),115))\r\nassert(isequal(transformer(161),115))\r\nassert(isequal(transformer(226),115))\r\nassert(isequal(transformer(232),115))\r\nassert(isequal(transformer(146),115))\r\nassert(isequal(transformer(151),115))\r\nassert(isequal(transformer(152),115))\r\nassert(isequal(transformer(193),115))\r\nassert(isequal(transformer(201),115))\r\nassert(isequal(transformer(192),115))\r\nassert(isequal(transformer(133),115))\r\nassert(isequal(transformer(137),115))\r\nassert(isequal(transformer(224),115))\r\nassert(isequal(transformer(200),115))\r\nassert(isequal(transformer(221),115))\r\nassert(isequal(transformer(160),115))\r\nassert(isequal(transformer(230),115))\r\nassert(isequal(transformer(176),115))\r\nassert(isequal(transformer(210),115))\r\nassert(isequal(transformer(159),115))\r\nassert(isequal(transformer(177),115))\r\nassert(isequal(transformer(126),115))\r\nassert(isequal(transformer(197),115))\r\nassert(isequal(transformer(141),115))\r\nassert(isequal(transformer(222),115))\r\nassert(isequal(transformer(189),115))\r\nassert(isequal(transformer(223),115))\r\nassert(isequal(transformer(140),115))\r\nassert(isequal(transformer(231),115))\r\nassert(isequal(transformer(236),115))\r\nassert(isequal(transformer(180),115))\r\nassert(isequal(transformer(191),115))\r\nassert(isequal(transformer(149),115))\r\nassert(isequal(transformer(172),115))\r\nassert(isequal(transformer(196),115))\r\nassert(isequal(transformer(135),115))\r\nassert(isequal(transformer(209),115))\r\nassert(isequal(transformer(144),115))\r\nassert(isequal(transformer(233),115))\r\nassert(isequal(transformer(215),115))\r\nassert(isequal(transformer(204),115))\r\nassert(isequal(transformer(187),115))\r\nassert(isequal(transformer(202),115))\r\nassert(isequal(transformer(217),115))\r\nassert(isequal(transformer(171),115))\r\nassert(isequal(transformer(153),115))\r\nassert(isequal(transformer(139),115))\r\nassert(isequal(transformer(148),115))\r\nassert(isequal(transformer(169),115))\r\nassert(isequal(transformer(130),115))\r\nassert(isequal(transformer(219),115))\r\nassert(isequal(transformer(206),115))\r\nassert(isequal(transformer(127),115))\r\nassert(isequal(transformer(129),115))\r\nassert(isequal(transformer(218),115))\r\nassert(isequal(transformer(220),115))\r\nassert(isequal(transformer(213),115))\r\nassert(isequal(transformer(207),115))\r\nassert(isequal(transformer(188),115))\r\nassert(isequal(transformer(179),115))\r\nassert(isequal(transformer(185),115))\r\nassert(isequal(transformer(131),115))\r\nassert(isequal(transformer(157),115))\r\nassert(isequal(transformer(143),115))\r\nassert(isequal(transformer(147),115))\r\nassert(isequal(transformer(138),115))\r\nassert(isequal(transformer(214),115))\r\nassert(isequal(transformer(178),115))\r\nassert(isequal(transformer(182),115))\r\nassert(isequal(transformer(195),115))\r\nassert(isequal(transformer(237),115))\r\nassert(isequal(transformer(155),115))\r\nassert(isequal(transformer(158),115))\r\nassert(isequal(transformer(199),115))\r\nassert(isequal(transformer(211),115))\r\nassert(isequal(transformer(228),115))\r\nassert(isequal(transformer(175),115))\r\nassert(isequal(transformer(150),115))\r\nassert(isequal(transformer(194),115))\r\nassert(isequal(transformer(134),115))\r\nassert(isequal(transformer(229),115))\r\nassert(isequal(transformer(181),115))\r\nassert(isequal(transformer(190),115))\r\nassert(isequal(transformer(165),115))\r\nassert(isequal(transformer(235),115))\r\nassert(isequal(transformer(239),115))\r\nassert(isequal(transformer(212),115))\r\nassert(isequal(transformer(208),115))\r\nassert(isequal(transformer(142),115))\r\nassert(isequal(transformer(198),115))\r\nassert(isequal(transformer(184),115))\r\nassert(isequal(transformer(240),115))\r\nassert(isequal(transformer(205),115))\r\nassert(isequal(transformer(234),115))\r\nassert(isequal(transformer(186),115))\r\nassert(isequal(transformer(183),115))\r\nassert(isequal(transformer(167),115))\r\nassert(isequal(transformer(154),115))\r\n\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":6556,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":108,"test_suite_updated_at":"2014-02-26T08:04:49.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-02-24T15:36:09.000Z","updated_at":"2026-02-18T14:03:38.000Z","published_at":"2014-02-24T15:36:09.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe problem is simple: we have a wall outlet which supplies 230V and an apparatus that requires 115V.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSoftware is always cheaper than hardware (well, most of the time), so we solve this with a program, a Matlab function, to be precise.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a program that converts the supplied input voltage to the required output voltage.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eIf you like this problem, please like it (after solving).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":56563,"title":"Compute the drag on a moving vehicle ","description":"We assume no rolling resistance, and the simple rule for Drag : , where  is the density of the fluid (assumed at 1.2 ),  is the surface of the vehicle,  is the drag coefficient and  is the velocity.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 56.8px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 28.4px; transform-origin: 407px 28.4px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 28.4px; text-align: left; transform-origin: 384px 28.4px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 197.083px 8px; transform-origin: 197.083px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWe assume no rolling resistance, and the simple rule for Drag : \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-15px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 90px; height: 35px;\" width=\"90\" height=\"35\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 24.8917px 8px; transform-origin: 24.8917px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, where \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003eρ\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 111.358px 8px; transform-origin: 111.358px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the density of the fluid (assumed at 1.2 \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAFAAAAAnCAYAAACYNs/UAAAFhklEQVRoQ+2aycsdRRTFv/wBRtSsREQ0QkRBMU6IERJIjMPChbMiWQhO4C4malyZhKi4jboQXAgmoOjGGXThgOCArlw4IK4dMP+Anh/UwfvqVXd1v/66nx+8hsP78rq76tape8+9t142ra2uQQxsGvT26uW1FYEDnWBF4IrAgQw0v36+bu0WThf+Fl4uPbqRPPA6LeBa4bnRKPtv4Lv05+vCB8JW4QLha+FO4Zc4/0Yi8IQM/1N4ZGQC8bwPhT2BLOaGvIdyT9woBJ4lw38XLhO+H5nABzX+l9k8eP+nwlHhqa4eeKkePC2FzXlpR/bp87ORF1AanpA6LBBOy7hu0qTvlDawzQN56RLh2WTxX/q8UPhjCSv4SnMSVjO7P6Ed72uut4S5RNIlhH/Si4gogrp3QqM9FZr0c7JhRsAnsIW5jwtXCS+WNrBGoLUHW+cEdIIFMAWa9IBw5UTzeRok7AZhV/rk+wPCTBVQI9Cxz8tTCHiJIyLg+VL4TEioyxoiYUaHawQe0QtPCujfmRMaHL3gO/1ji7AM7Y1LJpQfzm2pEYh4XyGcFNiFqS82EP1dxtz5Wh/XFweFmUTaRqDFm4Gsf3x3doHFUmmDhlwj0ApxkYT61nAunClk2y60+iLhYuEjwcnGOsa7rwjRi1nLbWnQLt0Nm7ldmEmkbQQ67pkDL8AoJt0mUBMR1k8IeWqn6HxVIOTJXO8JNwpIAe2QF3FvtqCcIPT3tTROfs//xituF4gSrig1lh8/G6OI91yecR873eFg/zlC3DQ26EfhPuHdaEwbgY75XDidFdmJXJci6Tt0P3rmP2liPPFjobbrzM9Va91ipWCSeJcNfFSghoNgNo9Mzj0+ac14Pt5jPp4n+/L8C8Ip4X7hbWEuEtoIdP0XdweCbhVKmuRdOkP34zuJhzUTONcO+YHwaVLyTSg8uuY2i3t3C9cn8myj18G8nKpcHuwvrZG5CW1Lzxf6u7H7aiIQ7SD72SiYx+0bj3WSUZxgcOULj+N1IbBP60ZEvJTmZeyYdKJ3cg+vcxkSNR7iazpb2rzGE+loFPUfWlc7CYm6kpcdcbwuXkUYfSN0ad18UkLI4f1XC5aWWMdyn4LciSzKzcJlUpMH2ij0D2HOdaK0G20GOVSsQ8XdTF/2bd3YWIjjulmIIh8TSd5FWOO72NRobxOB1ivIg0RnuTbviRoYF+JFME70jiaj+rRuUf9Ktao3rtQIRG3s4umdQzgX5R/0pvWwVlCjdZQHNN/HBPpI/sajnw6h1eaBfVq36GH55pbqWM8b73WRlF4eWNIyp3YGck3YFMaEBuSRvbj6nB862bTNEee1F831qHqoVMf6Xd+LR3SQ2vu0pxTCbt/i8VU0xlmUkIVY14PRcxfd1T6tW/SiuVOS5PVk3dIxnPXP9/g3yaX4w1FbuOQExrSfG2ViGQ+C7hF+FVwQx0zLM4T7t8IbPXYWjzqUFt9mN/fySiFvE63jJXK9FpzhN2Fn8tjanHP3cwJj2i/Vcp9oBGe8XA/xCDIaWZEQjBeFdU0D3bp1PfWOlUJ+1N+2Duwyud7ohQ8rcgL90yEDl1otN+DsWiw88Yb9wj4BzUPL7hA4/jHhtXKha+vmjUGruUqdQm0d/rmitcvo4o6146wuYzgTlnQPSXgmEclYTdrY2Kx3MWCZzwwl0EJe8y5ny7zQ9dr7tG7L5Gtu7qEEOvPWCES00cUmfUMOKEUWLmiXxepQArHbrVRTeLoEavpRyl68rN9cBnG/HgSSMN4UfID6uf7mDG2zcIvAf5F4TJg5iAxW92ndBi12jJfXg0DbBZEcq5+bviBT0wbWjvEbf7QeY8HrPeZ6EriobRBfI3nRsUd/7/9A4OiLHHOCFYED2V0ROJDAfwGM7Uo3DaS0bQAAAABJRU5ErkJggg==\" style=\"width: 40px; height: 19.5px;\" width=\"40\" height=\"19.5\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 6.21667px 8px; transform-origin: 6.21667px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e), \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 37.5px; height: 19.5px;\" width=\"37.5\" height=\"19.5\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 90.6167px 8px; transform-origin: 90.6167px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the surface of the vehicle, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-6px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 18.5px; height: 20px;\" width=\"18.5\" height=\"20\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 83.5px 8px; transform-origin: 83.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the drag coefficient and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 44.5px; height: 18.5px;\" width=\"44.5\" height=\"18.5\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 45.375px 8px; transform-origin: 45.375px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the velocity.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function F_d = drag(S, C_d, v)\r\nrho = 0;\r\nF_d = 0;\r\nend","test_suite":"%%\r\nS = 1;\r\nC_d = 0.21;\r\nv = 10;\r\nF_correct = 12.6;\r\nassert(isequal(drag(S, C_d, v), F_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":2763543,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":44,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-11-09T21:14:22.000Z","updated_at":"2026-02-17T14:32:03.000Z","published_at":"2022-11-09T21:14:22.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWe assume no rolling resistance, and the simple rule for Drag : \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eF_d=\\\\frac{1}{2}\\\\rho S C_d v^2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e, where \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e\\\\rho\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the density of the fluid (assumed at 1.2 \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ekg/m^3\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e), \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eS [m^2]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the surface of the vehicle, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eC_d\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the drag coefficient and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ev [m/s]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the velocity.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":49850,"title":"Simple Circuit of Resistors","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 345px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 172.5px; transform-origin: 407px 172.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThe configuration of a group of resistors is described in a matrix with two rows. The first row provides the information regarding the number of resistors at each junction and the second row provides the resistance of each detector at each junction. Consider the following configuration:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 222px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 111px; text-align: left; transform-origin: 384px 111px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThe circuit_def (i.e., the matrix defining the problem) for this configuration is [1 3 2; R1 R2 R3]. Find the resultant resistance for any given configuration.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = tot_res(circuit_def)\r\n  y = circuit_def(1,:)./circuit_def(2,:);\r\nend","test_suite":"%%\r\ncircuit_def=[3 3 3 3;1 2 3 4];\r\ntot_corr=3.3333;\r\nassert(abs(tot_res(circuit_def)-tot_corr)\u003c1e-3)\r\n%%\r\ncircuit_def=[1 2 3 4;1 2 3 4];\r\ntot_corr=4;\r\nassert(abs(tot_res(circuit_def)-tot_corr)\u003c1e-3)\r\n%%\r\ncircuit_def=[11 12 3 7;4 5 3 8];\r\ntot_corr=2.92316;\r\nassert(abs(tot_res(circuit_def)-tot_corr)\u003c1e-3)\r\n%%\r\ncircuit_def=[3 3 4 4 6 7 8;3 1 1 5 9 10 11];\r\ntot_corr=7.136905;\r\nassert(abs(tot_res(circuit_def)-tot_corr)\u003c1e-3)\r\n%%\r\ncircuit_def=[2 5 3;11 2 20];\r\ntot_corr=12.56667;\r\nassert(abs(tot_res(circuit_def)-tot_corr)\u003c1e-3)\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":180632,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":25,"test_suite_updated_at":"2021-01-17T21:52:11.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2021-01-17T21:37:24.000Z","updated_at":"2026-02-26T11:54:37.000Z","published_at":"2021-01-17T21:52:11.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe configuration of a group of resistors is described in a matrix with two rows. The first row provides the information regarding the number of resistors at each junction and the second row provides the resistance of each detector at each junction. Consider the following configuration:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe circuit_def (i.e., the matrix defining the problem) for this configuration is [1 3 2; R1 R2 R3]. Find the resultant resistance for any given 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dynamic load transfer to front axle during braking.","description":"During braking, load shifts from the rear axle to the front axle. Given mass, deceleration, center of gravity height, and wheelbase, compute this dynamic load transfer ,a key factor in vehicle stability and brake force distribution.\r\n\r\nUse: g = 9.81;","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 102px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 51px; transform-origin: 407px 51px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eDuring braking, load shifts from the rear axle to the front axle. Given mass, deceleration, center of gravity height, and wheelbase, compute this dynamic load transfer ,a key factor in vehicle stability and brake force distribution.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eUse: g = 9.81;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function dW = loadTransfer(m,a,h,L)\r\ndW = 0;\r\nend\r\n","test_suite":"%%\r\nm = 1200; a = 5; h = 0.5; L = 2.5;\r\ndW_correct = 1200;\r\nassert(abs(loadTransfer(m,a,h,L)-dW_correct) \u003c 1)\r\n\r\n%%\r\nm = 1000; a = 4; h = 0.45; L = 2.6;\r\ndW_correct = 692.3;\r\nassert(abs(loadTransfer(m,a,h,L)-dW_correct) \u003c 2)\r\n\r\n%%\r\nm = 0; a = 5; h = 0.5; L = 2.5;\r\ndW_correct = 0;\r\nassert(isequal(loadTransfer(m,a,h,L),dW_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-02-02T06:29:05.000Z","deleted_by":null,"deleted_at":null,"solvers_count":34,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T06:29:00.000Z","updated_at":"2026-03-31T16:44:16.000Z","published_at":"2026-02-02T06:29:05.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDuring braking, load shifts from the rear axle to the front axle. Given mass, deceleration, center of gravity height, and wheelbase, compute this dynamic load transfer ,a key factor in vehicle stability and brake force distribution.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eUse: g = 9.81;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61119,"title":"Escape from Planet ....","description":"Given a  Planets mass M, and raduis r. Calculate the surface escape velocity and the escape velocity at height h. \r\nand the difference between the Escape velocities to 5 decimal places. \r\nG ≈ 6.67×10−11 m3⋅kg−1⋅s−2","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 81px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 408px 40.5px; transform-origin: 408px 40.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven a  Planets mass M, and raduis r. Calculate the surface escape velocity and the escape velocity at height h. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eand the difference between the Escape velocities to 5 decimal places. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003eG\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e ≈ 6.67×10−11 m3⋅kg−1⋅s−2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [ve,veh,difference] = Escape(M,r,h)\r\nve  = \r\nveh  = \r\ndifference  = \r\nend","test_suite":"%% Earth at 100km \r\nM = 5.97* 10^27 ;\r\nr =  6378000; \r\nh = 100000; \r\ny_correct = [3.53364e+05,3.50626e+05, 2.73802e+03] ;\r\ntol  = 0.00002 \r\nassert(isequal(Escape(M,r,h),y_correct) \u003c tol)\r\n\r\n%%\r\nM = 20.97* 10^27 ;\r\nr =  252378000; \r\nh = 100000000; \r\ny_correct = [1.05281e+05, 8.90989e+04,1.61823e+04]\r\ntol  = 0.00002 \r\nassert(isequal(Escape(M,r,h),y_correct) \u003c tol)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5017232,"edited_by":5017232,"edited_at":"2025-12-08T04:56:12.000Z","deleted_by":null,"deleted_at":null,"solvers_count":11,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-12-07T23:58:16.000Z","updated_at":"2026-03-04T21:20:55.000Z","published_at":"2025-12-07T23:58:16.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a  Planets mass M, and raduis r. Calculate the surface escape velocity and the escape velocity at height h. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand the difference between the Escape velocities to 5 decimal places. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eG\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e ≈ 6.67×10−11 m3⋅kg−1⋅s−2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61189,"title":"Simulate full-stop emergency braking scenario.","description":"Emergency braking events demand rapid deceleration to bring the vehicle safely to rest. Given initial vehicle speed and constant deceleration, simulate the braking process and determine the time required to reach zero velocity.\r\nYour solution should correctly handle typical braking cases and extreme boundary conditions.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 72px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 36px; transform-origin: 407px 36px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eEmergency braking events demand rapid deceleration to bring the vehicle safely to rest. Given initial vehicle speed and constant deceleration, simulate the braking process and determine the time required to reach zero velocity.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYour solution should correctly handle typical braking cases and extreme boundary conditions.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function t_stop = emergencyBrakingTime(v0,a)\r\nt_stop = 0;\r\nend\r\n","test_suite":"%%\r\nv0 = 25; a = 5;\r\nt_correct = 5;\r\nassert(abs(emergencyBrakingTime(v0,a)-t_correct) \u003c 1e-6)\r\n\r\n%%\r\nv0 = 30; a = 6;\r\nt_correct = 5;\r\nassert(abs(emergencyBrakingTime(v0,a)-t_correct) \u003c 1e-6)\r\n\r\n%%\r\nv0 = 0; a = 5;\r\nt_correct = 0;\r\nassert(isequal(emergencyBrakingTime(v0,a),t_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2305225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":32,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T07:31:11.000Z","updated_at":"2026-04-02T00:33:36.000Z","published_at":"2026-02-02T07:31:11.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEmergency braking events demand rapid deceleration to bring the vehicle safely to rest. Given initial vehicle speed and constant deceleration, simulate the braking process and determine the time required to reach zero velocity.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYour solution should correctly handle typical braking cases and extreme boundary conditions.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61180,"title":"Compute vehicle stopping distance using initial speed and constant deceleration.","description":"Given vehicle speed v (m/s) and constant deceleration a (m/s²), compute stopping distance\r\nRemember: d = v² / (2a)","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 25.5px; transform-origin: 407px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven vehicle speed \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ev\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (m/s) and constant deceleration \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ea\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (m/s²), compute stopping distance\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 10.5px; text-align: left; transform-origin: 383px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eRemember: d = v² / (2a)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function d = stoppingDistance(v,a)\r\nd = 0;\r\nend","test_suite":"%%\r\nv = 20; a = 5;\r\nd_correct = 40;\r\nassert(abs(stoppingDistance(v,a)-d_correct) \u003c 1e-6)\r\n\r\n%%\r\nv = 30; a = 10;\r\nd_correct = 45;\r\nassert(abs(stoppingDistance(v,a)-d_correct) \u003c 1e-6)\r\n\r\n%%\r\nv = 0; a = 5;\r\nd_correct = 0;\r\nassert(abs(stoppingDistance(v,a)-d_correct) \u003c 1e-6)\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-02-02T05:29:31.000Z","deleted_by":null,"deleted_at":null,"solvers_count":49,"test_suite_updated_at":"2026-02-02T05:29:31.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T04:56:51.000Z","updated_at":"2026-04-02T00:31:02.000Z","published_at":"2026-02-02T05:05:46.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven vehicle speed \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ev\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (m/s) and constant deceleration \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ea\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (m/s²), compute stopping distance\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember: d = v² / (2a)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48695,"title":"Laws of motion 5","description":"Calculate the force is u are given mass and acceleration.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 10.5px; transform-origin: 406.5px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.5px; text-align: left; transform-origin: 383.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 182.575px 7.81667px; transform-origin: 182.575px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCalculate the force is u are given mass and acceleration.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function F = your_fcn_name(m,a)\r\n  y = x;\r\nend","test_suite":"%%\r\nfiletext = fileread('your_fcn_name.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'regexp');\r\nassert(~illegal)\r\n\r\n%%\r\nm=1;\r\na=1;\r\ny_correct = 1;\r\nassert(isequal(your_fcn_name(m,a),y_correct))\r\n%%\r\nm=1;\r\na=10;\r\ny_correct = 10;\r\nassert(isequal(your_fcn_name(m,a),y_correct))\r\n%%\r\nm=10;\r\na=10;\r\ny_correct = 100;\r\nassert(isequal(your_fcn_name(m,a),y_correct))\r\n%%\r\nm=randi(10)*2;\r\na=1/m;\r\ny_correct = 1;\r\nassert(isequal(your_fcn_name(m,a),y_correct))\r\n","published":true,"deleted":false,"likes_count":13,"comments_count":1,"created_by":644918,"edited_by":223089,"edited_at":"2024-06-30T13:46:26.000Z","deleted_by":null,"deleted_at":null,"solvers_count":2565,"test_suite_updated_at":"2024-06-30T13:46:26.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T17:09:46.000Z","updated_at":"2026-04-03T14:12:21.000Z","published_at":"2020-12-21T17:09:46.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the force is u are given mass and acceleration.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48675,"title":"Laws of motion 1","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven initial velocity 'u', acceleration 'a' , find the final velocity of an object after time 't'.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function v = your_fcn_name(u,a,t)\r\n  v = x;\r\nend","test_suite":"%%\r\nu=1;\r\na=1;\r\nt=1;\r\n\r\ny_correct = 2;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n\r\n\r\n%%\r\n\r\nu=2;\r\na=2;\r\nt=2;\r\n\r\ny_correct = 6;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n\r\n%%%%%%\r\nu=0;\r\na=1;\r\nt=2;\r\n\r\ny_correct = 2;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n\r\n\r\n%%%\r\n\r\nu=0;\r\na=10;\r\nt=6;\r\n\r\ny_correct = 60;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":14,"comments_count":2,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2752,"test_suite_updated_at":"2020-12-21T16:34:02.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T16:28:05.000Z","updated_at":"2026-04-03T14:05:03.000Z","published_at":"2020-12-21T16:29:26.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven initial velocity 'u', acceleration 'a' , find the final velocity of an object after time 't'.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48900,"title":"Kinetic energy calculation","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eAn object with mass m moves with velocity v. Find its kinetic energy.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function KE = your_fcn_name(m,v)\r\n  y = x;\r\nend","test_suite":"%%\r\nm = 1;\r\nv=2\r\ny_correct = 2;\r\nassert(isequal(your_fcn_name(m,v),y_correct))\r\n%%\r\nm = 5;\r\nv=200\r\ny_correct = 100000;\r\nassert(isequal(your_fcn_name(m,v),y_correct))\r\n%%\r\nm = 10;\r\nv=28\r\ny_correct = 3920;\r\nassert(isequal(your_fcn_name(m,v),y_correct))\r\n%%\r\nm = 25;\r\nv=26\r\ny_correct = 8450;\r\nassert(isequal(your_fcn_name(m,v),y_correct))\r\n","published":true,"deleted":false,"likes_count":12,"comments_count":0,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2446,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T20:21:04.000Z","updated_at":"2026-04-03T13:57:10.000Z","published_at":"2020-12-21T20:21:04.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAn object with mass m moves with velocity v. Find its kinetic energy.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":49693,"title":"Find the magnetic field in sollinoid","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 10.5px; transform-origin: 407.5px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 84.425px 7.7px; transform-origin: 84.425px 7.7px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMagnetic field in sollinoid B\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = MF(N,l,I)\r\n  y = x;\r\nend","test_suite":"%%\r\nN=5;l=200;I=3;\r\ny_correct =  9.42477796076938e-08;\r\nassert(abs(MF(N,l,I)-y_correct)\u003c0.00000001)\r\n%%\r\nN=6;l=50;I=3;\r\ny_correct =    4.5238934211693e-07;\r\nassert(abs(MF(N,l,I)-y_correct)\u003c0.0000001)\r\n%%\r\nN=9;l=50;I=2;\r\ny_correct =  4.5238934211693e-07;\r\nassert(abs(MF(N,l,I)-y_correct)\u003c0.0000001)","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":610936,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":18,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-31T03:05:45.000Z","updated_at":"2026-02-17T08:28:07.000Z","published_at":"2020-12-31T03:41:31.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMagnetic field in sollinoid B\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48905,"title":"Potential energy calculation","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind the potential energy of an object with mass 'm' and height 'h'. Consider g=10 m/s^2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function PE = your_fcn_name(m,h)\r\n  y = x;\r\nend","test_suite":"%%\r\nm=10;\r\nh=10;\r\ny_correct = 1000;\r\nassert(isequal(your_fcn_name(m,h),y_correct))\r\n\r\n%%\r\nm=1;\r\nh=12;\r\ny_correct = 120;\r\nassert(isequal(your_fcn_name(m,h),y_correct))\r\n%%\r\nm=85;\r\nh=10;\r\ny_correct = 8500;\r\nassert(isequal(your_fcn_name(m,h),y_correct))\r\n","published":true,"deleted":false,"likes_count":15,"comments_count":0,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":3014,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T20:24:12.000Z","updated_at":"2026-04-03T13:57:53.000Z","published_at":"2020-12-21T20:24:12.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind the potential energy of an object with mass 'm' and height 'h'. Consider g=10 m/s^2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":360,"title":"peta to nano (x-ray)","description":"for certain x-ray radiation, given frequency in petahertz, give wavelength in nanometer, must be accurate +/- 25% ","description_html":"\u003cp\u003efor certain x-ray radiation, given frequency in petahertz, give wavelength in nanometer, must be accurate +/- 25%\u003c/p\u003e","function_template":"function nano = peta_to_nano(peta)\r\n  nano = NaN;\r\nend","test_suite":"%%\r\npeta = 40;\r\nnano_correct = 7.5;\r\nassert(isequal(round(peta_to_nano(peta)*1000)/1000,nano_correct))\r\n%%\r\npeta = 250;\r\nnano_correct = 1.2;\r\nassert(isequal(round(peta_to_nano(peta)*10)/10,nano_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":5,"created_by":166,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":189,"test_suite_updated_at":"2012-02-19T23:42:51.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-02-19T21:52:34.000Z","updated_at":"2026-03-05T15:59:58.000Z","published_at":"2012-02-19T23:50:23.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003efor certain x-ray radiation, given frequency in petahertz, give wavelength in nanometer, must be accurate +/- 25%\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61186,"title":"Compute optimal front–rear brake force distribution.","description":"Modern braking systems dynamically distribute braking forces between front and rear axles to maintain stability, reduce stopping distance, and prevent wheel lock.\r\nGiven total braking demand and axle load distribution, compute the optimal front and rear brake force allocation that preserves balance and traction.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 93px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 46.5px; transform-origin: 407px 46.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eModern braking systems dynamically distribute braking forces between front and rear axles to maintain stability, reduce stopping distance, and prevent wheel lock.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven total braking demand and axle load distribution, compute the optimal front and rear brake force allocation that preserves balance and traction.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [Ff, Fr] = brakeDistribution(F_total, front_ratio)\r\nFf = 0; Fr = 0;\r\nend\r\n","test_suite":"%%\r\nF_total = 6000; front_ratio = 0.6;\r\n[Ff,Fr] = brakeDistribution(F_total,front_ratio);\r\nassert(isequal([Ff Fr],[3600 2400]))\r\n\r\n%%\r\nF_total = 8000; front_ratio = 0.7;\r\n[Ff,Fr] = brakeDistribution(F_total,front_ratio);\r\nassert(isequal([Ff Fr],[5600 2400]))\r\n\r\n%%\r\nF_total = 0; front_ratio = 0.6;\r\n[Ff,Fr] = brakeDistribution(F_total,front_ratio);\r\nassert(isequal([Ff Fr],[0 0]))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-02-02T06:39:17.000Z","deleted_by":null,"deleted_at":null,"solvers_count":30,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T06:39:14.000Z","updated_at":"2026-03-31T16:46:35.000Z","published_at":"2026-02-02T06:39:17.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eModern braking systems dynamically distribute braking forces between front and rear axles to maintain stability, reduce stopping distance, and prevent wheel lock.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven total braking demand and axle load distribution, compute the optimal front and rear brake force allocation that preserves balance and traction.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48680,"title":"Laws of motion 2","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eWith the initial speed 'u', acceleration 'a', find the distance travelled by an object in 't' secods.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s = your_fcn_name(u,a,t)\r\n  y = x;\r\nend","test_suite":"%%\r\nu=1;\r\na=1;\r\nt=2\r\ny_correct = 4;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n%%\r\nu=0;\r\na=2;\r\nt=2\r\ny_correct = 4;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n%%\r\nu=54;\r\na=1;\r\nt=20\r\ny_correct = 1280;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))\r\n%%\r\nu=1;\r\na=2;\r\nt=1\r\ny_correct = 2;\r\nassert(isequal(your_fcn_name(u,a,t),y_correct))","published":true,"deleted":false,"likes_count":12,"comments_count":1,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2533,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T16:47:29.000Z","updated_at":"2026-04-03T14:06:20.000Z","published_at":"2020-12-21T16:47:29.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWith the initial speed 'u', acceleration 'a', find the distance travelled by an object in 't' secods.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48910,"title":"Total energy ","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eA bird of mass 'm' is flying with a velocity 'v' at an height 'h'. FInd it's total energy. (g=10)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function E = your_fcn_name(m,v,h)\r\n  y = x;\r\nend","test_suite":"%%\r\nm=2;\r\nv=2;\r\nh=2;\r\ny_correct = 44;\r\nassert(isequal(your_fcn_name(m,v,h),y_correct))\r\n%%\r\nm=2;\r\nv=4;\r\nh=6;\r\ny_correct = 136;\r\nassert(isequal(your_fcn_name(m,v,h),y_correct))\r\n%%\r\nm=2;\r\nv=4;\r\nh=40;\r\ny_correct = 816;\r\nassert(isequal(your_fcn_name(m,v,h),y_correct))\r\n%%\r\nm=2;\r\nv=6;\r\nh=22;\r\ny_correct = 476;\r\nassert(isequal(your_fcn_name(m,v,h),y_correct))\r\n","published":true,"deleted":false,"likes_count":25,"comments_count":5,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2422,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T20:29:04.000Z","updated_at":"2026-04-03T13:59:35.000Z","published_at":"2020-12-21T20:29:04.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA bird of mass 'm' is flying with a velocity 'v' at an height 'h'. FInd it's total energy. (g=10)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":1116,"title":"Calculate the height of an object dropped from the sky","description":"Assume that an object is dropped from 1000 meters above the surface of the earth at time t=0.  The object is dropped such that the initial velocity and acceleration are both zero.\r\n\r\nWrite a function to determine the height, h, of the object at any time, t, where h=0 is the surface of the earth. Assume the acceleration due to gravity is constant 9.8 m/s^2.  Also, assume that before the object is dropped (negative t) it is being held at a constant height of 1000 meters.  Finally, assume that after the object hits the ground it remains at h=0. ","description_html":"\u003cp\u003eAssume that an object is dropped from 1000 meters above the surface of the earth at time t=0.  The object is dropped such that the initial velocity and acceleration are both zero.\u003c/p\u003e\u003cp\u003eWrite a function to determine the height, h, of the object at any time, t, where h=0 is the surface of the earth. Assume the acceleration due to gravity is constant 9.8 m/s^2.  Also, assume that before the object is dropped (negative t) it is being held at a constant height of 1000 meters.  Finally, assume that after the object hits the ground it remains at h=0.\u003c/p\u003e","function_template":"function h = height_of_object_at_time(t)\r\n  h = t;\r\nend","test_suite":"%%\r\nt = -1;\r\nh_correct = 1000;\r\nassert(abs(height_of_object_at_time(t)-h_correct)\u003c0.1)\r\n%%\r\nt = 0;\r\nh_correct = 1000;\r\nassert(abs(height_of_object_at_time(t)-h_correct)\u003c0.1)\r\n%%\r\nt = 1;\r\nh_correct = 995.1;\r\nassert(abs(height_of_object_at_time(t)-h_correct)\u003c0.1)\r\n%%\r\nt = 10;\r\nh_correct = 510;\r\nassert(abs(height_of_object_at_time(t)-h_correct)\u003c0.1)\r\n%%\r\nt = 15;\r\nh_correct = 0;\r\nassert(abs(height_of_object_at_time(t)-h_correct)\u003c0.1)\r\n","published":true,"deleted":false,"likes_count":6,"comments_count":2,"created_by":9156,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":284,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-12-12T04:04:57.000Z","updated_at":"2026-03-09T20:36:56.000Z","published_at":"2012-12-12T04:04:57.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAssume that an object is dropped from 1000 meters above the surface of the earth at time t=0. The object is dropped such that the initial velocity and acceleration are both zero.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function to determine the height, h, of the object at any time, t, where h=0 is the surface of the earth. Assume the acceleration due to gravity is constant 9.8 m/s^2. Also, assume that before the object is dropped (negative t) it is being held at a constant height of 1000 meters. Finally, assume that after the object hits the ground it remains at h=0.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":48700,"title":"Laws of motion 6","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind the force required to bring and object of mass 'm' moving with velocity 'v' to rest, in t seconds.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function f = your_fcn_name(m,v,t)\r\n  y = x;\r\nend","test_suite":"%%\r\nm=1;\r\nv=1;\r\nt=1;\r\ny_correct = 1;\r\nassert(isequal(your_fcn_name(m,v,t),y_correct))\r\n\r\n%%\r\nm=4;\r\nv=7;\r\nt=2;\r\ny_correct = 14;\r\nassert(isequal(your_fcn_name(m,v,t),y_correct))\r\n\r\n%%\r\nm=6;\r\nv=19;\r\nt=2;\r\ny_correct = 57;\r\nassert(isequal(your_fcn_name(m,v,t),y_correct))\r\n","published":true,"deleted":false,"likes_count":42,"comments_count":22,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":3374,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T17:21:03.000Z","updated_at":"2026-04-03T14:14:31.000Z","published_at":"2020-12-21T17:21:03.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind the force required to bring and object of mass 'm' moving with velocity 'v' to rest, in t seconds.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48070,"title":"Center of Mass(es) in 3D Space","description":"Given a matrix of format [x1,y1,z1,m1; x2,y2,z2,m2 . . .], return the center of mass of all listed points in 3d space [xc,yc,zc]. Return pt_com = 'Bad Data' if any value for mass is negative\r\nInspired by: http://hyperphysics.phy-astr.gsu.edu/hbase/cm.html","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 72px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 36px; transform-origin: 407px 36px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 383.5px 8px; transform-origin: 383.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven a matrix of format [x1,y1,z1,m1; x2,y2,z2,m2 . . .], return the center of mass of all listed points in 3d space [xc,yc,zc]. Return pt_com = 'Bad Data' if any value for mass is negative\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 38.5px 8px; transform-origin: 38.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eInspired by: \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ehttp://hyperphysics.phy-astr.gsu.edu/hbase/cm.html\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function pt_com = com_finder(x)\r\n  pt_com = x;\r\nend","test_suite":"%%\r\nx = [10    4    12    65\r\n     3     5     8     6\r\n     7     2    13    11\r\n    10     1     6    32\r\n     8     5     2    77\r\n     4     6     9     6\r\n     4     6    15     8\r\n     7     1     6    38\r\n     6     3     8    44\r\n     2     1     1    68];\r\ny_correct = [6.7690,2.9606,6.0254];\r\nTOL = 1e-3;\r\nassert(all(abs(y_correct-com_finder(x))\u003c=TOL))\r\n\r\n%%\r\nx = [10    4    12    65\r\n     3     5     8     6\r\n     7     2    13    11\r\n    10     1     6    32\r\n     8     5     2    77\r\n     4     6     9    -6\r\n     4     6    15     8\r\n     7     1     6    38\r\n     6     3     8    44\r\n     2     1     1    68];\r\ny_correct = [6.7690,2.9606,6.0254];\r\nTOL = 1e-3;\r\nassert(isequal(com_finder(x),'Bad Data'))\r\n\r\n%%\r\n\r\nx = [-47   -41    -3    47\r\n      -3  -121    -4    75\r\n     -34   -68    -4   402\r\n     -12  -137    -3   555\r\n      -1  -106    -4   256\r\n     -29  -157    -1   163\r\n     -83  -106    -6   646\r\n      -9   -55    -2   212\r\n     -56  -149    -2   434\r\n     -65  -157    -3   431\r\n     -69  -162    -1   693\r\n     -42  -153    -6   607\r\n     -57   -16    -4   520\r\n     -25   -42    -3   160\r\n    -100  -151    -1   413\r\n     -21   -51    -3   415\r\n     -99   -29    -4   290\r\n     -45   -63    -1   534\r\n     -20  -135    -2   550\r\n     -29  -134    -3    19\r\n      -4  -178    -6   179\r\n      -6   -72    -3   111\r\n     -64   -60    -3    24\r\n     -79  -100    -2   401\r\n     -45  -200    -6   391\r\n     -98  -129    -5   111\r\n     -52   -64    -5   424\r\n     -50   -47    -2   324\r\n     -87  -176    -6   205\r\n     -52   -49    -6   487\r\n     -51  -200    -6   656\r\n     -61   -69    -5   544\r\n     -13  -153    -5   114\r\n     -21    -2    -1   661\r\n     -81  -159    -4   519\r\n     -33    -9    -5   699\r\n     -23   -42    -4    28\r\n      -7   -34    -3   332\r\n     -93  -140    -1   157\r\n     -30   -80    -1   191\r\n     -15  -124    -6   605\r\n     -72  -118    -1    94\r\n      -5  -127    -6   385\r\n     -43  -190    -6   533\r\n     -33  -191    -1   104\r\n     -19   -56    -2   548\r\n     -58   -18    -4   354\r\n     -65  -182    -3   228\r\n     -93  -131    -4   644\r\n     -11  -184    -5   107\r\n     -46   -54    -1   459\r\n      -5  -100    -4   249\r\n     -44   -28    -4   278\r\n     -81   -18    -1   458\r\n     -51   -39    -1   318\r\n     -97   -26    -6    59\r\n      -4  -134    -5   159\r\n      -4  -167    -2   625\r\n      -9  -144    -2   279\r\n     -52  -138    -1    75\r\n      -2  -156    -6   183\r\n     -48  -173    -5   215\r\n    -100   -15    -5 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   -77  -107    -1   201\r\n     -94   -48    -4   303\r\n     -85   -96    -1   101\r\n     -22   -30    -4   118\r\n      -7   -87    -1   512\r\n     -38  -132    -3   136\r\n     -77  -179    -2   298\r\n     -70  -122    -6   435\r\n     -84  -107    -1   364\r\n     -54   -62    -6   260\r\n      -9  -106    -4   567\r\n     -18  -104    -2   165\r\n     -12   -86    -5   523\r\n     -51   -25    -6   374\r\n     -45   -47    -6   139\r\n     -68   -85    -4   658\r\n     -39   -40    -1   407\r\n     -86  -148    -4   176\r\n     -45   -99    -4   500\r\n     -72   -93    -1   252\r\n     -13   -98    -2   361\r\n     -48   -24    -4   559\r\n     -90   -72    -2   605\r\n     -89    -6    -5   440\r\n     -94   -66    -2   237\r\n     -37  -166    -6   422\r\n     -91    -9    -4   217\r\n     -88  -120    -2    57\r\n     -29  -116    -1   457\r\n      -7  -115    -2   591\r\n     -23  -195    -3   232\r\n     -34  -102    -3   131\r\n     -84  -123    -4   572\r\n     -25   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 624\r\n      -9   -17    -2   327\r\n     -81  -188    -6   226\r\n     -60   -90    -6   129\r\n     -10  -150    -3   396\r\n     -42  -109    -3   131\r\n     -73  -161    -4   308\r\n     -53    -9    -6     2\r\n     -96  -106    -6   459\r\n     -78   -17    -1   253\r\n     -61  -187    -5   524\r\n     -61   -54    -5   120\r\n     -84   -58    -2   317\r\n     -42   -71    -1   675\r\n     -44   -80    -5   560\r\n     -24  -131    -6   308\r\n     -30   -62    -3   648\r\n     -67   -47    -6   529\r\n     -39  -120    -5   453\r\n     -34  -104    -1   203\r\n      -3  -109    -3   327\r\n     -79   -28    -1   222\r\n     -43  -169    -6    15\r\n     -32   -66    -4   529\r\n     -87   -22    -1   584\r\n     -44   -76    -5   308\r\n     -53  -126    -5    48\r\n     -62   -80    -5   648\r\n     -44   -68    -5   104\r\n     -33   -38    -6   188\r\n     -46   -25    -6    29\r\n     -23  -148    -3   103\r\n     -98  -200    -4   106\r\n     -39   -94    -6   397\r\n     -77   -72    -2   125\r\n      -1   -64    -2   560\r\n     -89  -161    -3   673\r\n     -91  -198    -3   526];\r\ny_correct = [-48.2024,-92.6248,-3.6100];\r\nTOL = 1e-3;\r\nassert(all(abs(y_correct-com_finder(x))\u003c=TOL))\r\n\r\n%%\r\nx = [(0:5:500)',(0:6:600)',(0:7:700)',(0:1:100)'];\r\ny_correct = [335.0000,402.0000,469.0000];\r\nTOL = 1e-3;\r\nassert(all(abs(y_correct-com_finder(x))\u003c=TOL))\r\n\r\n%%\r\nx = [(0:-5:-500)',(0:6:600)',(0:-7:-700)',(0:8:800)'];\r\ny_correct = [-335.0000,402.0000,-469.0000];\r\nTOL = 1e-3;\r\nassert(all(abs(y_correct-com_finder(x))\u003c=TOL))\r\n\r\n%%\r\nx = circshift(spiral(4),2,2)-2;\r\nassert(isequal(com_finder(x),'Bad Data'))\r\n\r\n%%\r\nid = randi([7 11]);\r\nx = randi(100,id,4);\r\nx(id,4) = -x(id,4);\r\nassert(isequal(com_finder(x),'Bad Data'))\r\n\r\n%%\r\nx = [zeros(17,3) (1:17)'];\r\ny_correct = zeros(1,3);\r\nTOL = 1e-3;\r\nassert(all(abs(y_correct-com_finder(x))\u003c=TOL))\r\n\r\n\r\n%%\r\n%Cheating is bad\r\nfunctions={'!','feval','eval','str2func','str2num','regex','system','dos','unix','perl','assert','fopen','write','save','setenv','path','please'};\r\nassessFunctionAbsence(functions, 'FileName', 'com_finder.m');\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":728283,"edited_by":223089,"edited_at":"2023-02-02T12:44:18.000Z","deleted_by":null,"deleted_at":null,"solvers_count":17,"test_suite_updated_at":"2023-02-02T12:44:18.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-17T20:58:08.000Z","updated_at":"2026-03-05T14:22:01.000Z","published_at":"2020-12-18T16:06:36.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a matrix of format [x1,y1,z1,m1; x2,y2,z2,m2 . . .], return the center of mass of all listed points in 3d space [xc,yc,zc]. Return pt_com = 'Bad Data' if any value for mass is negative\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInspired by: \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ehttp://hyperphysics.phy-astr.gsu.edu/hbase/cm.html\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":561,"title":"Find the jerk","description":"No, it's not the author of this problem...\r\n\r\nJerk is the rate of change in acceleration over time of an object.  So, if given the position of an object over time in the form of a 1-by-N vector, return the indices i where there is nonzero jerk.  \r\n\r\nSuper rad bonus hint: The signal you need to find the jerk of will be given by the variable sig, created with the commands \r\n\r\n  h = 0.065; % stepsize\r\n  t = -10:h:10;\r\n  sigCoefs = 2*rand(1,3)-1;\r\n  sig = polyval(sigCoefs,t);\r\n  breakPoint = randi(length(sig)-2)+1;\r\n  sig(breakPoint) = (1.01)*sig(breakPoint); % this creates a nonzero jerk\r\n \r\nCheck the signal visually with\r\n\r\n  plot(t,sig,'k.-')\r\n\r\nNow, using just sig, determine breakPoint.\r\n ","description_html":"\u003cp\u003eNo, it's not the author of this problem...\u003c/p\u003e\u003cp\u003eJerk is the rate of change in acceleration over time of an object.  So, if given the position of an object over time in the form of a 1-by-N vector, return the indices i where there is nonzero jerk.\u003c/p\u003e\u003cp\u003eSuper rad bonus hint: The signal you need to find the jerk of will be given by the variable sig, created with the commands\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eh = 0.065; % stepsize\r\nt = -10:h:10;\r\nsigCoefs = 2*rand(1,3)-1;\r\nsig = polyval(sigCoefs,t);\r\nbreakPoint = randi(length(sig)-2)+1;\r\nsig(breakPoint) = (1.01)*sig(breakPoint); % this creates a nonzero jerk\r\n\u003c/pre\u003e\u003cp\u003eCheck the signal visually with\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eplot(t,sig,'k.-')\r\n\u003c/pre\u003e\u003cp\u003eNow, using just sig, determine breakPoint.\u003c/p\u003e","function_template":"function idx = findAJerk(sig)\r\n  idx = find(sig\u003e0);\r\nend","test_suite":"%% \r\n\r\n  h = 0.065; % stepsize\r\n  t = -10:h:10;\r\n\r\nfor tr = 1:1000\r\n  sigCoefs = 2*rand(1,3)-1;\r\n  sig = polyval(sigCoefs,t);\r\n  breakPoint = randi(length(sig)-2)+1;\r\n  sig(breakPoint) = (1.01)*sig(breakPoint);\r\n  assert(any(abs(findAJerk(sig) - breakPoint)\u003c=6)) % extra wide window out of kindness\r\nend\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":4,"created_by":2688,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":73,"test_suite_updated_at":"2012-04-07T16:14:29.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-04-07T03:32:53.000Z","updated_at":"2026-01-31T12:36:27.000Z","published_at":"2012-04-07T03:37:20.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNo, it's not the author of this problem...\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eJerk is the rate of change in acceleration over time of an object. So, if given the position of an object over time in the form of a 1-by-N vector, return the indices i where there is nonzero jerk.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSuper rad bonus hint: The signal you need to find the jerk of will be given by the variable sig, created with the commands\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[h = 0.065; % stepsize\\nt = -10:h:10;\\nsigCoefs = 2*rand(1,3)-1;\\nsig = polyval(sigCoefs,t);\\nbreakPoint = randi(length(sig)-2)+1;\\nsig(breakPoint) = (1.01)*sig(breakPoint); % this creates a nonzero jerk]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCheck the signal visually with\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[plot(t,sig,'k.-')]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNow, using just sig, determine breakPoint.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1280,"title":"Elastic Collision 001: 1-D","description":"Elastic Collision of two particles. \r\n\u003chttp://en.wikipedia.org/wiki/Elastic_collision wiki Elastic Collision\u003e\r\n\r\nSolve Conservation of Momentum and Kinetic Energy Equations for a point elastic collision.\r\n\r\n  m1*u1+m2*u2=m1*v1+m2*v2\r\n  m1*u1^2+m2*u2^2=m1*v1^2+m2*v2^2\r\n\r\nElastic Collision Gifs from wikipedia.   [used  \u003c \u003c copy image location \u003e \u003e]\r\n\r\n\u003c\u003chttp://upload.wikimedia.org/wikipedia/commons/c/c6/Elastischer_sto%C3%9F.gif\u003e\u003e\r\n\r\n\u003c\u003chttp://upload.wikimedia.org/wikipedia/commons/d/d2/Elastischer_sto%C3%9F2.gif\u003e\u003e\r\n\r\nGiven [m1,u1,m2,u2] solve for v1 and v2 under ideal elastic collision conditions.\r\n\r\n*Input:* [10, 1, 10, 0]\r\n\r\n*Output:* [0 1]  v1 and v2\r\n\r\n*Future:* 2-D Elastic equal masses, 2-D Elastic equal masses with find contact, Relativistic Elastic, and 3-D Elastic Equal Masses ","description_html":"\u003cdiv style = \"text-align: start; line-height: 20px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: normal; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"display: block; min-width: 0px; padding-top: 0px; transform-origin: 332px 241.5px; vertical-align: baseline; perspective-origin: 332px 241.5px; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eElastic Collision of two particles. \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://en.wikipedia.org/wiki/Elastic_collision\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ewiki Elastic Collision\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eSolve Conservation of Momentum and Kinetic Energy Equations for a point elastic collision.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-bottom: 10px; margin-left: 3px; margin-right: 3px; margin-top: 10px; transform-origin: 329px 20px; perspective-origin: 329px 20px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-height: 18px; padding-left: 4px; transform-origin: 329px 10px; white-space: nowrap; perspective-origin: 329px 10px; \"\u003e\u003cspan style=\"border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-right: 45px; min-height: 0px; padding-left: 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; perspective-origin: 0px 0px; margin-right: 45px; \"\u003e\u003cspan style=\"margin-right: 0px; \"\u003em1*u1+m2*u2=m1*v1+m2*v2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-height: 18px; padding-left: 4px; transform-origin: 329px 10px; white-space: nowrap; perspective-origin: 329px 10px; \"\u003e\u003cspan style=\"border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-right: 45px; min-height: 0px; padding-left: 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; perspective-origin: 0px 0px; margin-right: 45px; \"\u003e\u003cspan style=\"margin-right: 0px; \"\u003em1*u1^2+m2*u2^2=m1*v1^2+m2*v2^2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 10px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eElastic Collision Gifs from wikipedia. [used \u0026lt; \u0026lt; copy image location \u0026gt; \u0026gt;]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: center; transform-origin: 309px 33px; white-space: pre-wrap; perspective-origin: 309px 33px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" 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\" 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\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven [m1,u1,m2,u2] solve for v1 and v2 under ideal elastic collision conditions.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: bold; \"\u003eInput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e [10, 1, 10, 0]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; perspective-origin: 309px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: bold; \"\u003eOutput:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e [0 1] v1 and v2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; transform-origin: 309px 21px; white-space: pre-wrap; perspective-origin: 309px 21px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: bold; \"\u003eFuture:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; transform-origin: 0px 0px; perspective-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e 2-D Elastic equal masses, 2-D Elastic equal masses with find contact, Relativistic Elastic, and 3-D Elastic Equal Masses\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [v1 v2]=OneD_Elastic(m1,u1,m2,u2)\r\n\r\n v1=0;\r\n \r\n v2=0;\r\n\r\n\r\nend","test_suite":"m1=3;u1=4;m2=5;u2=-6;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[-8.5 1.5]))\u003c.01)\r\n\r\n%%\r\n\r\nm1=2;u1=4;m2=2;u2=0;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[0 4]))\u003c.01)\r\n\r\n%%\r\n\r\nm1=6;u1=4;m2=6;u2=2;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[2 4]))\u003c.01)\r\n\r\n%%\r\n\r\nm1=6;u1=4;m2=3;u2=2;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[2.6667 4.6667]))\u003c.01)\r\n\r\n%%\r\n\r\nm1=3;u1=6;m2=3;u2=-6;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[-6 6]))\u003c.01)\r\n\r\n%%\r\n\r\nm1=1;u1=100;m2=100;u2=0;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[-98.0198 1.9802]))\u003c.01)\r\n\r\n%%\r\n\r\nm1=6;u1=-4;m2=4;u2=-6;\r\n[v1 v2]=OneD_Elastic(m1,u1,m2,u2);\r\nassert(max(abs([v1 v2]-[-5.6 -3.6]))\u003c.01)\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":3,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":73,"test_suite_updated_at":"2020-09-28T20:12:24.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-02-19T04:35:34.000Z","updated_at":"2026-02-13T20:05:06.000Z","published_at":"2013-02-19T05:18:20.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eElastic Collision of two particles. \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Elastic_collision\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ewiki Elastic Collision\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSolve Conservation of Momentum and Kinetic Energy Equations for a point elastic collision.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[m1*u1+m2*u2=m1*v1+m2*v2\\nm1*u1^2+m2*u2^2=m1*v1^2+m2*v2^2]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eElastic Collision Gifs from wikipedia. [used \u0026lt; \u0026lt; copy image location \u0026gt; \u0026gt;]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"center\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"center\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven [m1,u1,m2,u2] solve for v1 and v2 under ideal elastic collision conditions.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e [10, 1, 10, 0]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e [0 1] v1 and v2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eFuture:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e 2-D Elastic equal masses, 2-D Elastic equal masses with find contact, Relativistic Elastic, and 3-D Elastic Equal 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telescope","description":"Two grandkids Dorothy and Benjamin are sharing a telescope made by their grandpa, who used an old lens of spectacles as the objective. This objective lens has power of p diopter. Dorothy definitively watches a doghouse at distance d meters. Benjamin basically watches a birdhouse at distance b meters. After watching the doghouse, how much shift of the eyepiece in mm is necessary to watch the birdhouse? Please give a general solution, the test suite may be more extensive later.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 105px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 52.5px; transform-origin: 407px 52.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 52.5px; text-align: left; transform-origin: 384px 52.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 383.5px 8px; transform-origin: 383.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTwo grandkids Dorothy and Benjamin are sharing a telescope made by their grandpa, who used an old lens of spectacles as the objective. This objective lens has power of p diopter. Dorothy definitively watches a doghouse at distance d meters. Benjamin basically watches a birdhouse at distance b meters. After watching the doghouse, how much shift of the eyepiece in mm is necessary to watch the birdhouse? Please give a general solution, the test suite may be more extensive later.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function mm = telescope(d,b,p)\r\n% diopter = 1/focal_length_meter = 1/object_distance + 1/image_distance\r\nmm=1000*meter;\r\nend","test_suite":"%%\r\nfiletext = fileread('telescope.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'regexp') || ...\r\n          contains(filetext, 'switch') || contains(filetext, 'elseif'); \r\nassert(~illegal)\r\n\r\n%%\r\nd=200; b=100; p=0.5;\r\nmm = telescope(d,b,p)\r\nmm_correct = 21;\r\nassert(abs(round(mm) - mm_correct)\u003c1000*eps)\r\n\r\n%%\r\nd=100; b=200; p=0.5;\r\nmm = telescope(d,b,p)\r\nmm_correct = 21;\r\nassert(abs(round(abs(mm)) - mm_correct)\u003c1000*eps)\r\n\r\n%%\r\nd=100; b=100; p=0.5;\r\nmm = telescope(d,b,p)\r\nmm_correct = 0;\r\nassert(round(mm) == mm_correct)\r\n\r\n%%\r\nd=51; b=26; p=1;\r\nmm = telescope(d,b,p)\r\nmm_correct = 20;\r\nassert(round(mm) == mm_correct)\r\n\r\n%%\r\nd=4004; b=8; p=0.25;\r\nmm = telescope(d,b,p)\r\nmm_correct = d-b;\r\nassert(round(mm) == mm_correct)\r\n\r\n%%\r\nd=255; b=55; p=0.2;\r\nmm = telescope(d,b,p)\r\nmm_correct = (d-b)*p*10;\r\nassert(abs(mm - mm_correct)\u003c1e-4)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":3,"created_by":166,"edited_by":223089,"edited_at":"2023-01-07T06:15:33.000Z","deleted_by":null,"deleted_at":null,"solvers_count":26,"test_suite_updated_at":"2023-01-07T06:15:33.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-03-04T22:25:38.000Z","updated_at":"2025-12-12T09:35:32.000Z","published_at":"2012-03-05T20:14:39.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTwo grandkids Dorothy and Benjamin are sharing a telescope made by their grandpa, who used an old lens of spectacles as the objective. This objective lens has power of p diopter. Dorothy definitively watches a doghouse at distance d meters. Benjamin basically watches a birdhouse at distance b meters. After watching the doghouse, how much shift of the eyepiece in mm is necessary to watch the birdhouse? Please give a general solution, the test suite may be more extensive later.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":48690,"title":"Laws of motion 4","description":"Given the initial velocity 'u', final velocity 'v' and acceleration 'a', find the distance travelled.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 284.5px 8px; transform-origin: 284.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven the initial velocity 'u', final velocity 'v' and acceleration 'a', find the distance travelled.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s = your_fcn_name(u,v,a)\r\n  y = x;\r\nend","test_suite":"%%\r\nu=0\r\nv=1;\r\na=1;\r\ny_correct = 0.5;\r\nassert(isequal(your_fcn_name(u,v,a),y_correct))\r\n\r\n%%\r\nu=0\r\nv=10;\r\na=1;\r\ny_correct = 50;\r\nassert(isequal(your_fcn_name(u,v,a),y_correct))\r\n\r\n%%\r\nu=20\r\nv=100;\r\na=1;\r\ny_correct = 4800;\r\nassert(isequal(your_fcn_name(u,v,a),y_correct))\r\n","published":true,"deleted":false,"likes_count":10,"comments_count":5,"created_by":644918,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2501,"test_suite_updated_at":"2021-02-01T10:35:57.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-21T17:03:05.000Z","updated_at":"2026-04-03T14:11:33.000Z","published_at":"2020-12-21T17:03:05.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven the initial velocity 'u', final velocity 'v' and acceleration 'a', find the distance travelled.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":369,"title":"Basic electricity in a dry situation","description":"\u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \r\n\r\nThis is a very hypothetical situation between two individuals in a very dry atmosphere. \r\n\r\nHe came running in rubber boots when she was combing her hair. \r\n\r\nAround N number of electrons moved from one person to the other upon contact. \r\n\r\nWhat was the voltage between them before the contact? \r\n\r\nAssume it is a simple RC type electrical circuit with equivalent capacitance of about 16 pico farads. \r\n\r\nPlease assume that every electron carries about 160 zepto coulombs.\r\n\r\nFor more info on capacitors: \u003chttps://en.wikipedia.org/wiki/Capacitor\u003e","description_html":"\u003cp\u003e\u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889 \u0026#9889\u003c/p\u003e\u003cp\u003eThis is a very hypothetical situation between two individuals in a very dry atmosphere.\u003c/p\u003e\u003cp\u003eHe came running in rubber boots when she was combing her hair.\u003c/p\u003e\u003cp\u003eAround N number of electrons moved from one person to the other upon contact.\u003c/p\u003e\u003cp\u003eWhat was the voltage between them before the contact?\u003c/p\u003e\u003cp\u003eAssume it is a simple RC type electrical circuit with equivalent capacitance of about 16 pico farads.\u003c/p\u003e\u003cp\u003ePlease assume that every electron carries about 160 zepto coulombs.\u003c/p\u003e\u003cp\u003eFor more info on capacitors: \u003ca href = \"https://en.wikipedia.org/wiki/Capacitor\"\u003ehttps://en.wikipedia.org/wiki/Capacitor\u003c/a\u003e\u003c/p\u003e","function_template":"function V = volts(N)\r\n  V = 10000;\r\nend","test_suite":"%%\r\nN = 10^10;\r\nV = 150;\r\nassert(volts(N)\u003eV/pi)\r\n%%\r\nN = 10^11;\r\nV = 700;\r\nassert(volts(N)\u003cV*pi)\r\n%%\r\nN = 10^12;\r\nV = 10000;\r\nassert(volts(N)\u003eV/sqrt(pi))\r\n","published":true,"deleted":false,"likes_count":8,"comments_count":4,"created_by":166,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":595,"test_suite_updated_at":"2012-02-20T20:05:18.000Z","rescore_all_solutions":false,"group_id":34,"created_at":"2012-02-20T20:05:18.000Z","updated_at":"2026-03-18T13:23:56.000Z","published_at":"2017-10-16T01:45:05.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889 \u0026amp;#9889\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is a very hypothetical situation between two individuals in a very dry atmosphere.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHe came running in rubber boots when she was combing her hair.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAround N number of electrons moved from one person to the other upon contact.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWhat was the voltage between them before the contact?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAssume it is a simple RC type electrical circuit with equivalent capacitance of about 16 pico farads.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePlease assume that every electron carries about 160 zepto coulombs.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor more info on capacitors:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://en.wikipedia.org/wiki/Capacitor\\\"\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026lt;https://en.wikipedia.org/wiki/Capacitor\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026gt;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61185,"title":"Compute wheel slip ratio during braking.","description":"During braking, a difference develops between the vehicle’s forward speed and the rotational speed of its wheels. This difference is captured by a quantity known as wheel slip ratio, which plays a critical role in traction control, ABS algorithms, and vehicle stability systems.\r\nGiven the vehicle longitudinal speed and wheel circumferential speed, determine the corresponding slip ratio. Your implementation should handle normal driving conditions, heavy braking scenarios, and boundary cases reliably.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 114px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 407px 57px; transform-origin: 407px 57px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 31.5px; text-align: left; transform-origin: 383px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eDuring braking, a difference develops between the vehicle’s forward speed and the rotational speed of its wheels. This difference is captured by a quantity known as \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ewheel slip ratio\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, which plays a critical role in traction control, ABS algorithms, and vehicle stability systems.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 383px 21px; text-align: left; transform-origin: 383px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven the vehicle longitudinal speed and wheel circumferential speed, determine the corresponding slip ratio. Your implementation should handle normal driving conditions, heavy braking scenarios, and boundary cases reliably.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s = wheelSlipRatio(v_vehicle, v_wheel)\r\ns = 0;\r\nend\r\n","test_suite":"%%\r\nv_vehicle = 20; v_wheel = 18;\r\ns_correct = 0.1;\r\nassert(abs(wheelSlipRatio(v_vehicle,v_wheel) - s_correct) \u003c 1e-6)\r\n\r\n%%\r\nv_vehicle = 25; v_wheel = 0;\r\ns_correct = 1;\r\nassert(abs(wheelSlipRatio(v_vehicle,v_wheel) - s_correct) \u003c 1e-6)\r\n\r\n%%\r\nv_vehicle = 0; v_wheel = 0;\r\ns_correct = 0;\r\nassert(abs(wheelSlipRatio(v_vehicle,v_wheel) - s_correct) \u003c 1e-6)\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-02-02T06:36:51.000Z","deleted_by":null,"deleted_at":null,"solvers_count":31,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-02-02T06:36:05.000Z","updated_at":"2026-03-31T16:45:06.000Z","published_at":"2026-02-02T06:36:51.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDuring braking, a difference develops between the vehicle’s forward speed and the rotational speed of its wheels. This difference is captured by a quantity known as \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ewheel slip ratio\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, which plays a critical role in traction control, ABS algorithms, and vehicle stability systems.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven the vehicle longitudinal speed and wheel circumferential speed, determine the corresponding slip ratio. Your implementation should handle normal driving conditions, heavy braking scenarios, and boundary cases reliably.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61140,"title":"Calculating Swimming Stroke Index (SI)","description":"In competitive swimming, speed () is only one part of the equation. High efficiency is defined by moving fast while maintaining a high Distance Per Stroke (DPS). The Stroke Index (SI) is a common metric used by coaches to quantify this efficiency.\r\nYour task is to calculate the Stroke Index based on a single pool length. However, you must account for the glide distance after the wall push-off, as no strokes are taken during that phase.\r\n\r\nWhere:\r\n is the velocity over the entire length (m/s).\r\nDPS is the distance covered per stroke during the swimming phase only.\r\nConstraint:If the glide distance (pushOff) is greater than or equal to the pool length (poolLength), the scenario is physically impossible for this calculation. In such cases, the function must return NaN.\r\nInputs\r\npoolLength: Pool length in meters (e.g., 50).\r\ntime: Time taken to complete the length in seconds.\r\nstrokeCount: Total number of individual arm strokes taken.\r\npushOff: Glide distance (meters) covered before the first stroke begins.\r\nOutput\r\nSI: The Stroke Index rounded to two decimal place","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 483.562px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 408px 241.781px; transform-origin: 408px 241.781px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn competitive swimming, speed (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003ev\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) is only one part of the equation. High efficiency is defined by moving fast while maintaining a high \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eDistance Per Stroke (DPS)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. The \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eStroke Index (SI)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is a common metric used by coaches to quantify this efficiency.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYour task is to calculate the Stroke Index based on a single pool length. However, you must account for the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eglide distance\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e after the wall push-off, as no strokes are taken during that phase.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"82\" height=\"18\" alt=\"SI = v*DPS\" style=\"width: 82px; height: 18px;\"\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWhere:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 40.875px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 391px 20.4375px; transform-origin: 391px 20.4375px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2188px; text-align: left; transform-origin: 363px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003ev\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the velocity over the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eentire\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e length (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em/s\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e).\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2188px; text-align: left; transform-origin: 363px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003eDPS\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the distance covered per stroke during the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eswimming phase only\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 43px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 21.5px; text-align: left; transform-origin: 384px 21.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eConstraint:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf the glide distance (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epushOff\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) is greater than or equal to the pool length (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epoolLength\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e), the scenario is physically impossible for this calculation. In such cases, the function must return \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; font-weight: 700; \"\u003eNaN\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInputs\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003col style=\"block-size: 83.75px; font-family: Helvetica, Arial, sans-serif; list-style-type: decimal; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 391px 41.875px; transform-origin: 391px 41.875px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epoolLength\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Pool length in meters (e.g., 50).\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003etime\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Time taken to complete the length in seconds.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003estrokeCount\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Total number of individual arm strokes taken.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epushOff\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Glide distance (meters) covered before the first stroke begins.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 20.9375px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 391px 10.4688px; transform-origin: 391px 10.4688px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eSI\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: The Stroke Index rounded to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003etwo decimal place\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function SI = calculateStrokeIndex(poolLength, time, strokeCount, pushOff)\r\n  SI = 1;\r\nend","test_suite":"%% Test Case 1:\r\nassert(isequal(calculateStrokeIndex(50, 35, 30, 5), 2.14));\r\n\r\n%% Test Case 2: Short Course Sprint\r\nassert(isequal(calculateStrokeIndex(25, 15, 12, 6), 2.64));\r\n\r\n%% Test Case 3:\r\nresult = calculateStrokeIndex(25, 10, 15, 30);\r\nassert(isnan(result), 'Function should return NaN when glide distance exceeds pool length');\r\n\r\n%% Test Case 4:\r\nresult = calculateStrokeIndex(50, 40, 20, 50);\r\nassert(isnan(result));\r\n\r\n%% Test Case 5:\r\nfor i = 1:5\r\n    L_rand = 50;\r\n    T_rand = 30 + rand*20;\r\n    S_rand = 20 + randi(20);\r\n    G_rand = rand*10;\r\n    \r\n    v = L_rand / T_rand;\r\n    DPS = (L_rand - G_rand) / S_rand;\r\n    expected = round(v * DPS, 2);\r\n    \r\n    assert(abs(calculateStrokeIndex(L_rand, T_rand, S_rand, G_rand) - expected) \u003c 1e-8);\r\nend","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":4996329,"edited_by":4996329,"edited_at":"2025-12-18T10:10:12.000Z","deleted_by":null,"deleted_at":null,"solvers_count":10,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-12-18T09:56:54.000Z","updated_at":"2026-02-26T10:57:38.000Z","published_at":"2025-12-18T10:03:46.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn competitive swimming, speed (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"v\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$v$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e) is only one part of the equation. High efficiency is defined by moving fast while maintaining a high \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eDistance Per Stroke (DPS)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. The \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eStroke Index (SI)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is a common metric used by coaches to quantify this efficiency.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYour task is to calculate the Stroke Index based on a single pool length. However, you must account for the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eglide distance\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e after the wall push-off, as no strokes are taken during that phase.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"SI = v*DPS\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$$SI = v \\\\cdot DPS$$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWhere:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"v\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$v$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the velocity over the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eentire\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e length (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em/s\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eDPS\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is the distance covered per stroke during the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eswimming phase only\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eConstraint:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eIf the glide distance (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epushOff\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e) is greater than or equal to the pool length (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epoolLength\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e), the scenario is physically impossible for this calculation. In such cases, the function must return \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eNaN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInputs\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epoolLength\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Pool length in meters (e.g., 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