tag:www.mathworks.com,2005:/matlabcentral/fileexchange/feedMATLAB Central File Exchangeicon.pnglogo.pngMATLAB Central - File Exchange - product:"MATLAB Report Generator"User-contributed code library2014-12-18T23:48:54-05:00191100tag:www.mathworks.com,2005:FileInfo/480782014-10-29T15:07:32Z2014-12-10T21:07:24ZExample Deployable SimBiology® App for Evaluating PK/PD Drug EfficacyAn example deployable MATLAB® app for simulating a mechanistic PK/PD model built using SimBiology®.<p>This package contains an example of a MATLAB® application built using GUIDE for simulating a SimBiology® model. The SimBiology® model that is included is based on a tumor growth model developed by Koch, Walz, Lahu, and Schropp. Users can use the app as an example interface for entering an initial tumor weight, cell line, and dosing schedule, in order to simulate tumor growth inhibition in response to different drug therapies and generate a report. Using MATLAB Compiler®, the SimBiology® model can be deployed as part of a standalone MATLAB® app for distribution to other users.
<br />
<br />This package includes the MATLAB® GUIDE files, MATLAB Compiler® deployment script, tumor growth SimBiology® model, and MATLAB Report Generator® files.
<br />
<br />To run the app, execute the following command at the MATLAB® command prompt:
<br />
<br />>> TumorGrowthInhibition
<br />
<br />To deploy the app using MATLAB Compiler®, execute the following command:
<br />
<br />>> deployApp
<br />
<br />In MATLAB Report Generator® 4.0 (R2014b), the new Document Object Model (DOM) API is used for generating reports.
<br />Technical Article:
<br /><a href="http://www.mathworks.com/company/newsletters/articles/building-deployable-applications-for-evaluating-pkpd-drug-efficacy.html">http://www.mathworks.com/company/newsletters/articles/building-deployable-applications-for-evaluating-pkpd-drug-efficacy.html</a></p>
<p>References:
<br />Koch, G., Walz A., Lahu, G., and Schropp, J. (2009) Modeling of tumor growth and anticancer effects of combination therapy. Journal of Pharmacokinetics and Pharmacodynamics. 36:179-197.</p>Anitahttp://www.mathworks.com/matlabcentral/fileexchange/authors/158010MATLAB 8.4 (R2014b)MATLAB CompilerMATLAB Report GeneratorSimBiologyMATLABThis requires MATLAB R2012b or later.falsetag:www.mathworks.com,2005:FileInfo/484902014-11-18T01:40:21Z2014-12-09T07:10:31ZLynx MATLAB ToolboxA toolbox for the design of complex machine learning experiments<p>Lynx is a research-oriented MATLAB toolbox for designing in a fast way supervised machine learning experiments. Details of a simulation can be specified under a configuration file, and the toolbox takes charge of loading data, partitioning it, testing the algorithms and visualizing the results. Additionally, it has support for parallelizing the experiments, and enabling GPU support. This makes large experiments easily repeatable and modifiable.
<br />We have currently pre-implemented several algorithms (e.g. support vector machines, kernel ridge regression...), optimization routines (grid-search procedures, searching the optimal feature subset...), and datasets.
<br />You can see examples of use (taken from my research papers) on:
<br /><a href="http://ispac.ing.uniroma1.it/scardapane/software/code/">http://ispac.ing.uniroma1.it/scardapane/software/code/</a>
<br />Please do not hesitate to contact me for any help. The toolbox has been tested on MATLAB R2013a.</p>Simonehttp://www.mathworks.com/matlabcentral/fileexchange/authors/427352MATLAB 8.1 (R2013a)MATLAB Distributed Computing ServerMATLAB Report GeneratorNeural Network ToolboxParallel Computing ToolboxStatistics ToolboxMATLAB3162784214773215282191224093273842806731272falsetag:www.mathworks.com,2005:FileInfo/115652006-06-28T10:23:57Z2014-11-30T01:19:25ZGenetic Algorithms ApplicationDrawing the largest circle in a space of stars without enclosing any of them using Genetic Algorithm<p>This code is an application of GA.
<br />It solves the following problem:
<br />Draw the largest possible circle in a space of stars without enclosing any of them.
<br />The final output is a plot of the stars and the largest possible circle is drawn.</p>Wesam Elshamyhttp://www.mathworks.com/matlabcentral/fileexchange/authors/24384MATLAB 7.2 (R2006a)MATLABMATLAB Report Generatorfalsetag:www.mathworks.com,2005:FileInfo/115672006-06-28T10:40:08Z2014-11-30T01:17:32ZPareto Front Using Fitness SharingFinding the Pareto front of a simple problem using Genetic Algorithms with fitness sharing<p>This code finds and plots the Pareto front of the following problem:
<br />Find the smallest circle to enclose the largest no. of stars in a the following* space of stars.
<br />*a space filled with a randomly positioned stars, so you will not get the same results for two different runs</p>Wesam Elshamyhttp://www.mathworks.com/matlabcentral/fileexchange/authors/24384MATLAB 7.2 (R2006a)MATLABMapping ToolboxMATLAB Report GeneratorFixed-Point Designerfalsetag:www.mathworks.com,2005:FileInfo/298062010-12-22T04:38:32Z2014-11-30T01:16:54ZConstrained MOO using GA (ver. 2)Solving a simple MOO problem using Genetic Algorithms (GA)<p>This code is a demo of using Genetic Algorithms (GA) to solve a simple constrained multi-objective optimization (MOO) problem.
<br />The objective is to find the pareto front of the MOO problem defined as follows:
<br /> Maximize:
<br /> f1(X) = 2*x1 + 3*x2
<br /> f2(X) = 2/x1 + 1/x2
<br /> such that:
<br /> 10 > x1 > 20
<br /> 20 > x2 > 30</p>
<p>The set of non-dominated solutions is plotted in the objective space, and displayed in the console.</p>Wesam Elshamyhttp://www.mathworks.com/matlabcentral/fileexchange/authors/24384MATLAB 7.8 (R2009a)MATLABMATLAB Report Generatorfalsetag:www.mathworks.com,2005:FileInfo/414902014-02-11T18:23:18Z2014-11-20T22:02:22ZAutopilot Demo for ARP4754A, DO-178C and DO-331Demonstration of how to use MathWorks products in a workflow for ARP-4754A, DO-178C nad DO-331<p>This demonstrates a workflow going system requirements, through software desing and implementation to target production code. It includes the development steps, verification steps and evidence needed to follow these standards.</p>Bill Potterhttp://www.mathworks.com/matlabcentral/fileexchange/authors/30043MATLAB 8.4 (R2014b)Aerospace BlocksetMATLAB Report GeneratorPolyspace Code ProverSimulink CoderEmbedded CoderSimulinkSimulink Report GeneratorSimulink Verification and ValidationMATLABSimulink Code InspectorPolyspace Bug Finderfalsetag:www.mathworks.com,2005:FileInfo/484692014-11-15T18:16:13Z2014-11-18T13:04:13ZSwarmWolf -- The Artificial Wolf Pack Algorithm (AWPA)The Artificial Wolf Pack Algorithm (AWPA) - A toolbox for MATLAB<p>The AWPA is inspired by the social behaviours of the wolf pack (WP) in: Scouting, Calling and Besieging.
<br />Note:
<br />if running with errors, please access full SwarmWolf1001 package via
<br /><a href="http://1drv.ms/1sRfFgZ">http://1drv.ms/1sRfFgZ</a></p>Leo Chenhttp://www.mathworks.com/matlabcentral/fileexchange/authors/15500MATLAB 7.9 (R2009b)Control System ToolboxDatafeed ToolboxMATLAB Report GeneratorMATLAB32022falsetag:www.mathworks.com,2005:FileInfo/461812014-05-06T20:51:53Z2014-11-06T17:50:55ZMakeHTMLTableFilterVisualizing Tables in HTML from MATLAB<p>Given a MATLAB variable in the form of a table, this example will show you how to:
<br />- with the Publish command, create a visually attractive table with a JavaScript to help filter your data
<br />(under withPublish folder, publish test_publish.m)
<br />- with MATLAB Report Generator, create a visually attractive table with a JavaScript to help filter your data
<br />(under withMLReportGenerator, run mygeneratereport.m)</p>
<p>Please note that the JavaScript used in this submission was based on work by Max Guglielmi for more information see the webpage <a href="http://tablefilter.free.fr/">http://tablefilter.free.fr/</a></p>
<p></p>Gareth Thomashttp://www.mathworks.com/matlabcentral/fileexchange/authors/69380MATLAB 8.4 (R2014b)MATLAB Report GeneratorMATLABfalsetag:www.mathworks.com,2005:FileInfo/443272013-11-15T21:48:26Z2013-11-15T21:48:26ZModel-in-the-Loop for Embedded System Test - Speed Controller CaseModel-in-the-Loop for Embedded System Test - Works best with MATLAB version of 2008. A case study. <p>Developed between 2006 - 2008 by Justyna Zander and Abel Marrero Perez at Fraunhofer Institute FOKUS, Berlin, Germany. Supervised by Ina Schieferdecker.</p>
<p>The main contribution of this thesis applies to the software built into embedded systems. In particular, it refers to the software models from which systems are built. An approach to functional black-box testing based on the system models by providing a test model is developed. It is contrasted with the currently applied test methods that form dedicated solutions, usually specialized in a concrete testing context. The test framework proposed herewith, is realized in the MATLAB®/Simulink®/Stateflow® environment and is called Model-in-the-Loop for Embedded System Test (MiLEST).</p>
<p>The developed signal-feature - oriented paradigm allows the abstract description of signals and their properties. It addresses the problem of missing reference signal flows as well as the issue of systematic test data selection. Numerous signal features are identified. Furthermore, predefined test patterns help build hierarchical test specifications, which enables a construction of the test specification along modular divide-and-conquer principles. The processing of both discrete and continuous signals is possible, so that the hybrid behavior of embedded systems can be addressed. The testing with MiLEST starts in the requirements phase and goes down to the test execution level. The essential steps in this test process are automated, such as the test data generation and test evaluation to name the most important.</p>
<p>Three case studies based on adaptive cruise control are presented. These examples correspond to component, component-in-the-loop, and integration level tests. Moreover, the quality of the test specification process, the test model, and the resulting test cases is investigated in depth. The resulting test quality metrics are applied during the test design and test execution phases so as to assess whether and how the proposed method is more effective than established techniques.</p>
<p>Available on GitHub: <a href="https://github.com/justynazander/MiLEST">https://github.com/justynazander/MiLEST</a></p>Justyna Zanderhttp://www.mathworks.com/matlabcentral/fileexchange/authors/130433MATLAB 7.6 (R2008a)MATLAB Report GeneratorSimulinkStateflowMATLABfalsetag:www.mathworks.com,2005:FileInfo/407452013-03-11T21:30:47Z2013-03-11T21:30:47ZComparing different methods to solve an Inverted Pendulum problemA simple reporting tool that shows how you can model an inverted pendulum in a few methods.<p>In order to solve an inverted pendulum dynamics, you can select several methods:
<br />1. Solving Symbolic equations.
<br />2. Solveing a MATLAB ODE
<br />3. Constructing a Simulink model
<br />4. Designing the system using SimMechanics</p>
<p>This submission show how you can leverage the reporting tools that exist in the MATLAB environemnt in order to compare the solution of all these methods, and show the advantage of each one:
<br />1. Symbolic, complete solution using the Symbolic Math toolbox.
<br />2. Parameter sweep using monte carlo simulation for a MATLAB function.
<br />3. Running the same Simulink dynamic model for different friction values.
<br />4. Modeling the problem and not the equations, using SimMechanics.</p>
<p>In order to run the comparison, simply run the following command:
<br />report symbolic_simmech;</p>
<p>The report template contains examples and how-to do it yourself.</p>
<p>I would like to acknowledge Carlos Osorio, who created some of the files and models in this example.</p>Roni Peerhttp://www.mathworks.com/matlabcentral/fileexchange/authors/120105MATLAB 8.0 (R2012b)MATLAB Report GeneratorSimMechanicsSimulinkSimulink Report GeneratorSymbolic Math ToolboxMATLABfalse