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Impact of a MATLAB-controlled application on the autonomy of ischemic stroke patients in the hospital
This study explores the possibility of using a Matlab-controlled electromyographic system, based on a microcontroller, in monitoring and assisting patients with contralateral hemiplegia following an ischemic stroke, paralyzed on one side of the body and bedridden. The main aim is, by generating electrical signals based on the level of flexion of the patient’s healthy arm or clenching of the patient’s healthy fist, the system can control various devices and alert medical staff. The technology provides support and independence to patients in performing some of their daily activities.
Journal Article
Introduction to Matrix Analytic Methods in Queues 1
Matrix-analytic methods (MAM) were introduced by Professor Marcel Neuts and have been applied to a variety of stochastic models since. In order to provide a clear and deep understanding of MAM while showing their power, this book presents MAM concepts and explains the results using a number of worked-out examples. This book’s approach will inform and kindle the interest of researchers attracted to this fertile field. To allow readers to practice and gain experience in the algorithmic and computational procedures of MAM, Introduction to Matrix Analytic Methods in Queues 1 provides a number of computational exercises. It also incorporates simulation as another tool for studying complex stochastic models, especially when the state space of the underlying stochastic models under analytic study grows exponentially. The book’s detailed approach will make it more accessible for readers interested in learning about MAM in stochastic models.
eBook
Computational Colour Science Using MATLAB, 2nd Edition
Computational Colour Science Using MATLAB 2nd Edition offers a practical, problem-based approach to colour physics. The book focuses on the key issues encountered in modern colour engineering, including efficient representation of colour information, Fourier analysis of reflectance spectra and advanced colorimetric computation. Emphasis is placed on the practical applications rather than the techniques themselves, with material structured around key topics. These topics include colour calibration of visual displays, computer recipe prediction and models for colour-appearance prediction. Each topic is carefully introduced at three levels to aid student understanding. First, theoretical ideas and background information are discussed, then explanations of mathematical solutions follow and finally practical solutions are presented using MATLAB. The content includes: A compendium of equations and numerical data required by the modern colour and imaging scientist. Numerous examples of solutions and algorithms for a wide-range of computational problems in colour science. Example scripts using the MATLAB programming language. This 2nd edition contains substantial new and revised material, including three innovative chapters on colour imaging, psychophysical methods, and physiological colour spaces; the MATLAB toolbox has been extended with a professional, optimized, toolbox to go alongside the current teaching toolbox; and a java toolbox has been added which will interest users who are writing web applications and/or applets or mobile phone applications. Computational Colour Science Using MATLAB 2nd Edition is an invaluable resource for students taking courses in colour science, colour chemistry and colour physics as well as technicians and researchers working in the area. In addition, it acts a useful reference for professionals and researchers working in colour dependent industries such as textiles, paints, print & electronic imaging. Review from First Edition: \"...highly recommended as a concise introduction to the practicalities of colour science...\" (Color Technology, 2004)
eBook
Advanced numerical methods with Matlab 1 : function approximation and system resolution
Most physical problems can be written in the form of mathematical equations (differential, integral, etc.). Mathematicians have always sought to find analytical solutions to the equations encountered in the different sciences of the engineer (mechanics, physics, biology, etc.). These equations are sometimes complicated and much effort is required to simplify them. In the middle of the 20th century, the arrival of the first computers gave birth to new methods of resolution that will be described by numerical methods. They allow solving numerically as precisely as possible the equations encountered (resulting from the modeling of course) and to approach the solution of the problems posed. The approximate solution is usually computed on a computer by means of a suitable algorithm. The objective of this book is to introduce and study the basic numerical methods and those advanced to be able to do scientific computation. The latter refers to the implementation of approaches adapted to the treatment of a scientific problem arising from physics (meteorology, pollution, etc.) or engineering (structural mechanics, fluid mechanics, signal processing, etc.).-- Provided by Publisher.
Book
Matlab: A Practical Introduction to Programming and Problem Solving, 2nd Edition
Assuming no knowledge of programming, this book presents both programming concepts and MATLAB’s built-in functions, providing a perfect platform for exploiting MATLAB’s extensive capabilities for tackling engineering problems. It starts with programming concepts such as variables, assignments, input/output, and selection statements, moves onto loops and then solves problems using both the ‘programming concept’ and the ‘power of MATLAB’ side-by-side. In-depth coverage is given to input/output, a topic that is fundamental to many engineering applications. Ancillaries available with the text: Instructor solution manual (available Aug. 1st) electronic images from the text (available Aug 16th) m-files (available Aug 1st) * Presents programming concepts and MATLAB built-in functions side-by-side, giving students the ability to program efficiently and exploit the power of MATLAB to solve problems. * In depth coverage of file input/output, a topic essential for many engineering applications * Systematic, step-by-step approach, building on concepts throughout the book, facilitating easier learning * Sections on ‘common pitfalls’ and ‘programming guidelines’ direct students towards best practice * New to this edition: More engineering applications help the reader learn Matlab in the context of solving technical problems New and revised end of chapter problems Stronger coverage of loops and vectorizing in a new chapter, chapter 5 Updated to reflect current features and functions of the current release of Matlab
eBook
MATLAB for dummies
Plot graphs, solve equations, and write code in a flash! If you work in a STEM field, chances are you'll be using MATLAB on a daily basis. MATLAB is a popular and powerful computational tool and this book provides everything you need to start manipulating and plotting your data. MATLAB has rapidly become the premier data tool, and MATLAB For Dummies is a comprehensive guide to the fundamentals. MATLAB For Dummies guides you through this complex computational language from installation to visualization to automation. Learn MATLAB's language fundamentals including syntax, operators, and data types Understand how to use the most important window in MATLAB - the Command Window Get the basics of linear algebra to get up and running with vectors, matrices, and hyperspace Automate your work with programming scripts and functions Plot graphs in 2D and 3D to visualize your data Includes a handy guide for MATLAB's functions and plotting routines MATLAB is an essential part of the analysis arsenal and MATLAB For Dummies provides clear, thorough guidance to get the most out of your data.-- Source other than Library of Congress.
Book
Raincloud plots: a multi-platform tool for robust data visualization
Across scientific disciplines, there is a rapidly growing recognition of the need for more statistically robust, transparent approaches to data visualization. Complementary to this, many scientists have called for plotting tools that accurately and transparently convey key aspects of statistical effects and raw data with minimal distortion. Previously common approaches, such as plotting conditional mean or median barplots together with error-bars have been criticized for distorting effect size, hiding underlying patterns in the raw data, and obscuring the assumptions upon which the most commonly used statistical tests are based. Here we describe a data visualization approach which overcomes these issues, providing maximal statistical information while preserving the desired ‘inference at a glance’ nature of barplots and other similar visualization devices. These “raincloud plots” can visualize raw data, probability density, and key summary statistics such as median, mean, and relevant confidence intervals in an appealing and flexible format with minimal redundancy. In this tutorial paper, we provide basic demonstrations of the strength of raincloud plots and similar approaches, outline potential modifications for their optimal use, and provide open-source code for their streamlined implementation in R, Python and Matlab ( https://github.com/RainCloudPlots/RainCloudPlots ). Readers can investigate the R and Python tutorials interactively in the browser using Binder by Project Jupyter.
Journal Article