Recent Advances in Electrical and Information Technologies for Sustainable Development

Proceedings of the 3rd International Conference on Electrical and Information Technologies -- ICEIT 2017, Morocco

Author: Soumia El Hani,Mohamad Essaaidi

Publisher: Springer

ISBN: 3030052761

Category: Electric power systems

Page: 210

View: 1380

DOWNLOAD NOW »

The book includes the best extended papers which were selected from the 3rd International Conference of Electrical and Information Technologies (ICEIT 2017, Morocco). The book spans two inter-related research domains which shaped modern societies, solved many of their development problems, and contributed to their unprecedented economic growth and social welfare. Selected papers are based on original and high quality research. They were peer reviewed by experts in the field. They are grouped into five parts. Part I deals with Power System and Electronics topics that include Power Electronics & Energy Conversion, Actuators & Micro/Nanotechnology, etc. Part II relates to Control Systems and their applications. Part III concerns the topic of Information Technology that basically includes Smart Grid, Information Security, Cloud Computing Distributed, Big Data, etc. Part IV discusses Telecommunications and Vehicular Technologies topics that include, Green Networking and Communications, Wireless Ad-hoc and Sensor Networks, etc. Part V covers Green Applications and Interdisciplinary topics, that include intelligent and Green Technologies for Transportation Systems, Smart Cities, etc. This book offers a good opportunity for young researchers, novice scholars and whole academic sphere to explore new trends in Electrical and information Technologies.
Release

Computational Statistics Handbook with MATLAB

Author: Wendy L. Martinez,Angel R. Martinez

Publisher: CRC Press

ISBN: 1466592745

Category: Business & Economics

Page: 731

View: 2148

DOWNLOAD NOW »

A Strong Practical Focus on Applications and Algorithms Computational Statistics Handbook with MATLAB®, Third Edition covers today’s most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of the bestselling previous editions. The text keeps theoretical concepts to a minimum, emphasizing the implementation of the methods. New to the Third Edition This third edition is updated with the latest version of MATLAB and the corresponding version of the Statistics and Machine Learning Toolbox. It also incorporates new sections on the nearest neighbor classifier, support vector machines, model checking and regularization, partial least squares regression, and multivariate adaptive regression splines. Web Resource The authors include algorithmic descriptions of the procedures as well as examples that illustrate the use of algorithms in data analysis. The MATLAB code, examples, and data sets are available online.
Release

Exploratory Data Analysis with MATLAB

Author: Wendy L. Martinez,Angel R. Martinez,Jeffrey Solka

Publisher: CRC Press

ISBN: 1315349841

Category: Mathematics

Page: 590

View: 7034

DOWNLOAD NOW »

Praise for the Second Edition: "The authors present an intuitive and easy-to-read book. ... accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB." —Adolfo Alvarez Pinto, International Statistical Review "Practitioners of EDA who use MATLAB will want a copy of this book. ... The authors have done a great service by bringing together so many EDA routines, but their main accomplishment in this dynamic text is providing the understanding and tools to do EDA. —David A Huckaby, MAA Reviews Exploratory Data Analysis (EDA) is an important part of the data analysis process. The methods presented in this text are ones that should be in the toolkit of every data scientist. As computational sophistication has increased and data sets have grown in size and complexity, EDA has become an even more important process for visualizing and summarizing data before making assumptions to generate hypotheses and models. Exploratory Data Analysis with MATLAB, Third Edition presents EDA methods from a computational perspective and uses numerous examples and applications to show how the methods are used in practice. The authors use MATLAB code, pseudo-code, and algorithm descriptions to illustrate the concepts. The MATLAB code for examples, data sets, and the EDA Toolbox are available for download on the book’s website. New to the Third Edition Random projections and estimating local intrinsic dimensionality Deep learning autoencoders and stochastic neighbor embedding Minimum spanning tree and additional cluster validity indices Kernel density estimation Plots for visualizing data distributions, such as beanplots and violin plots A chapter on visualizing categorical data
Release

Textual Data Science with R

Author: Mónica Bécue-Bertaut

Publisher: CRC Press

ISBN: 1351816357

Category: Mathematics

Page: 204

View: 5632

DOWNLOAD NOW »

Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential.
Release

Computational Statistics Handbook with MATLAB, Second Edition

Author: Wendy L. Martinez,Angel R. Martinez

Publisher: Chapman and Hall/CRC

ISBN: 9781584885665

Category: Mathematics

Page: 792

View: 5556

DOWNLOAD NOW »

As with the bestselling first edition, Computational Statistics Handbook with MATLAB®, Second Edition covers some of the most commonly used contemporary techniques in computational statistics. With a strong, practical focus on implementing the methods, the authors include algorithmic descriptions of the procedures as well as examples that illustrate the use of the algorithms in data analysis. Updated for MATLAB® R2007a and the Statistics Toolbox, Version 6.0, this edition incorporates many additional computational statistics topics. New to the Second Edition • New functions for multivariate normal and multivariate t distributions • Updated information on the new MATLAB functionality for univariate and bivariate histograms, glyphs, and parallel coordinate plots • New content on independent component analysis, nonlinear dimensionality reduction, and multidimensional scaling • New topics on linear classifiers, quadratic classifiers, and voting methods, such as bagging, boosting, and random forests • More methods for unsupervised learning, including model-based clustering and techniques for assessing the results of clustering • A new chapter on parametric models that covers spline regression models, logistic regression, and generalized linear models • Expanded information on smoothers, such as bin smoothing, running mean and line smoothers, and smoothing splines With numerous problems and suggestions for further reading, this accessible text facilitates an understanding of computational statistics concepts and how they are employed in data analysis.
Release

Music Data Analysis

Foundations and Applications

Author: Claus Weihs,Dietmar Jannach,Igor Vatolkin,Guenter Rudolph

Publisher: CRC Press

ISBN: 1315353830

Category: Business & Economics

Page: 694

View: 7848

DOWNLOAD NOW »

This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as chord and harmony, instrument and tempo recognition. It also discusses the implementation aspects of music data analysis such as architecture, user interface and hardware. It is ideal for use in university classes with an interest in music data analysis. It also could be used in computer science and statistics as well as musicology.
Release

Statistics and Data Analysis for Microarrays using MATLAB , 2nd edition

Author: Sorin Draghici

Publisher: Chapman and Hall/CRC

ISBN: 9781439809778

Category: Science

Page: 706

View: 6305

DOWNLOAD NOW »

Bridging the gap between introductory theory and practical knowledge, this second edition reflects the fast-moving field of DNA microarrays by adding new and updated chapters that cover cutting-edge microarray topics. This edition now offers the option of learning elements of MATLAB® in parallel with data analysis. The author also includes Bioconductor tools that are linked to the theoretical concepts discussed in the text. This edition also features more opportunities for readers to practice everything that they have learned from the book. The accompanying CD-ROM provides MATLAB code and tips on how to use the MATLAB Bioinformatics toolbox.
Release

Introduction to Machine Learning and Bioinformatics

Author: Sushmita Mitra,Sujay Datta,Theodore Perkins,George Michailidis

Publisher: Chapman and Hall/CRC

ISBN: N.A

Category: Mathematics

Page: 384

View: 1277

DOWNLOAD NOW »

Lucidly Integrates Current Activities Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other. Examines Connections between Machine Learning & Bioinformatics The book begins with a brief historical overview of the technological developments in biology. It then describes the main problems in bioinformatics and the fundamental concepts and algorithms of machine learning. After forming this foundation, the authors explore how machine learning techniques apply to bioinformatics problems, such as electron density map interpretation, biclustering, DNA sequence analysis, and tumor classification. They also include exercises at the end of some chapters and offer supplementary materials on their website. Explores How Machine Learning Techniques Can Help Solve Bioinformatics Problems Shedding light on aspects of both machine learning and bioinformatics, this text shows how the innovative tools and techniques of machine learning help extract knowledge from the deluge of information produced by today’s biological experiments.
Release

Applied Stochastic Modelling, Second Edition

Author: Byron J.T. Morgan

Publisher: CRC Press

ISBN: 1420011650

Category: Mathematics

Page: 368

View: 1321

DOWNLOAD NOW »

Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications. It also successfully revises standard probability and statistical theory. Along with an updated bibliography and improved figures, this edition offers numerous updates throughout. New to the Second Edition An extended discussion on Bayesian methods A large number of new exercises A new appendix on computational methods The book covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. Although the book can be used without reference to computational programs, the author provides the option of using powerful computational tools for stochastic modelling. All of the data sets and MATLAB® and R programs found in the text as well as lecture slides and other ancillary material are available for download at www.crcpress.com Continuing in the bestselling tradition of its predecessor, this textbook remains an excellent resource for teaching students how to fit stochastic models to data.
Release