ISSN (Print): 2210-3279
ISSN (Online): 2210-3287
Volume 11, 9 Issues, 2021
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ISSN (Print): 2210-3279
ISSN (Online): 2210-3287
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Author(s): Enrico Vezzetti and Federica Marcolin
eISBN: 978-1-68108-044-4, 2015
Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images.
This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods.
Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.
Author(s): Pierre Lorrentz
eISBN: 978-1-68108-090-1, 2015
An intelligent system is one which exhibits characteristics including, but not limited to, learning, adaptation, and problem-solving. Artificial Neural Network (ANN) Systems are intelligent systems designed on the basis of statistical models of learning that mimic biological systems such as the human central nervous system. Such ANN systems represent the theme of this book. This book also describes concepts related to evolutionary methods, clustering algorithms, and other networks which are complementary to ANN systems.
The book is divided into two parts. The first part explains basic concepts derived from the natural biological neuron and introduces purely scientific frameworks used to develop a viable ANN model. The second part expands over to the design, analysis, performance assessment, and testing of ANN models. Concepts such as Bayesian networks, multi-classifiers, and neuromorphic ANN systems are explained, among others.
Artificial Neural Systems: Principles and Practice takes a developmental perspective on the subject of ANN systems, making it a beneficial resource for students undertaking graduate courses and research projects, and working professionals (engineers, software developers) in the field of intelligent systems design.
Author(s): Terje Kristensen
eISBN: 978-1-68108-299-8, 2016
This brief text presents a general guideline for writing advanced algorithms for solving engineering and data visualization problems. The book starts with an introduction to the concept of evolutionary algorithms followed by details on clustering and evolutionary programming. Subsequent chapters present information on aspects of computer system design, implementation and data visualization. The book concludes with notes on the possible applications of evolutionary algorithms in the near future.
This book is intended as a supplementary guide for students and technical apprentices learning machine language, or participating in advanced software programming, design and engineering courses.
Editor(s): Faria Nassiri-Mofakham
eISBN: 978-1-68108-502-9, 2017
ISBN: 978-1-68108-503-6 ISSN: 2543-1560 (Print) ISSN: 2543-1579 (Online)
Intelligent Computational Systems presents current and future developments in intelligent computational systems in a multi-disciplinary context. Readers will learn about the pervasive and ubiquitous roles of artificial intelligence (AI) and gain a perspective about the need for intelligent systems to behave rationally when interacting with humans in complex and realistic domains.
This reference covers widespread applications of AI discussed in 11 chapters which cover topics such as AI and behavioral simulations, AI schools, automated negotiation, language analysis and learning, financial prediction, sensor management, Multi-agent systems, and much more.
This reference work is will assist researchers, advanced-level students and practitioners in information technology and computer science fields interested in the broad applications of AI.
Author(s): Andre A. Keller
eISBN: 978-1-68108-568-5, 2017
Multi-Objective Optimization in Theory and Practice is a traditional two-part approach to solving multi-objective optimization (MOO) problems namely the use of classical methods and evolutionary algorithms.
This first book is devoted to classical methods including the extended simplex method by Zeleny and preference-based techniques. This part covers three main topics through nine chapters. The first topic focuses on the design of such MOO problems, their complexities including nonlinearities and uncertainties, and optimality theory. The second topic introduces the founding solving methods including the extended simplex method to linear MOO problems and weighting objective methods. The third topic deals with particular structures of MOO problems, such as mixed-integer programming, hierarchical programming, fuzzy logic programming, and bimatrix games.
Multi-Objective Optimization in Theory and Practice is a user-friendly book with detailed, illustrated calculations, examples, test functions, and small-size applications in Mathematica® (among other mathematical packages) and from scholarly literature. It is an essential handbook for students and teachers involved in advanced optimization courses in engineering, information science, and mathematics degree programs.
Editor(s): Ana Claudia Teodoro
eISBN: 978-1-68108-611-8, 2018
ISBN: 978-1-68108-612-5 ISSN: 2589-3785 (Print) ISSN: 2589-3793 (Online)
GIS - An Overview of Applications is a compilation of reviews that give an overview of the latest advances in Geographic Information System (GIS) technology. The multidisciplinary nature of the book gives readers perspectives in research fields as diverse as forest management, land use and cover, tourism, environment impact assessment, climate change studies, biodiversity and health care and mobility studies.
The book is a suitable reference for graduates involved in data engineering and GIS courses as well as working professionals in the field of data engineering, analysis and management.
Editor(s): Mangey Ram
eISBN: 978-1-68108-713-9, 2018
ISBN: 978-1-68108-714-6 ISSN: 2589-3785 (Print) ISSN: 2589-3793 (Online)
Recent developments in information science and technology have been possible due to original and timely research contributions containing new results in various fields of applied mathematics. It is also true that advances in information science create opportunities for developing mathematical models further.
Author(s): Sudip Kumar Sahana, Moumita Khowas and Keshav Sinha
eISBN: 978-1-68108-707-8, 2018
Budget Optimization and Allocation: An Evolutionary Computing Based Model is a guide for computer programmers for writing algorithms for efficient and effective budgeting. It provides a balance of theory and practice. Chapters explain evolutionary computational techniques (genetic algorithms) and compare these techniques with traditional approaches to budget allocation.
A case study on the complex and broad problem of union budgeting of India is presented. The macro and micro economic issues specific to the case discussed, with the growth rate being the final aim of the budget exercise. The authors also present a comparison of the budget allocation practices of different countries, consistent with other factors such as their local economy, culture, population, etc. The use of evolutionary computation to tackle incremental budgeting is also presented. Readers will be able to understand the synergies of modern computational techniques with tried and tested budgeting models.
Budget Optimization and Allocation: An Evolutionary Computing Based Model is a useful reference for graduate students, business enterprise programmers, and evolutionary computing/AI researchers who seek to understand new methods of budgeting.
Author(s): Rajesh Singh, Anita Gehlot, Bhupendra Singh and Sushabhan Choudhury
eISBN: 978-1-68108-727-6, 2018
This book provides a single platform for beginners in systems engineering to start Arduino interface projects with MATLAB®. It covers the basics of the programming with Arduino and Arduino interfacing with MATLAB® (with and without the use or I/O packages) in 3 sections, respectively.
-introduces readers to Arduino IDE, Proteus simulation modeling, Arduino interfaces with display devices, sensor interfaces (both digital and analog), actuators, MATLAB® GUIs, digital read/write systems with I/O interfaces and automation systems.
-organized layout for a reader friendly experience
-provides detailed circuit diagrams
-provides relevant simulation modeling instructions
This is an ideal book for engineering students and system designers for learning the basic programming and simulation of Arduino and MATLAB® based real time project prototypes.
eISBN: 978-1-68108-705-4, 2019
Multi-Objective Optimization in Theory and Practice is a simplified two-part approach to multi-objective optimization (MOO) problems.
This second part focuses on the use of metaheuristic algorithms in more challenging practical cases. The book includes ten chapters that cover several advanced MOO techniques. These include the determination of Pareto-optimal sets of solutions, metaheuristic algorithms, genetic search algorithms and evolution strategies, decomposition algorithms, hybridization of different metaheuristics, and many-objective (more than three objectives) optimization and parallel computation. The final section of the book presents information about the design and types of fifty test problems for which the Pareto-optimal front is approximated. For each of them, the package NSGA-II is used to approximate the Pareto-optimal front.
It is an essential handbook for students and teachers involved in advanced optimization courses in engineering, information science and mathematics degree programs.
Author(s): Rajesh Singh, Anita Gehlot and Bhupendra Singh
eISBN: 978-9-81141-092-5, 2019
Arduino and Scilab based Projects provides information ranging from the basics to advanced knowledge of Arduino and its interfacing with input/output devices (display devices, actuators, sensors), communication modules (RF modem, Zigbee) and Scilab. It also provides embedded system based on Arduino with simulation, programming and interfacing with Scilab, Arduino interfacing with Scilab with and without Arduino 1.1 packages. Chapters are arranged in an easy-to-understand sequence that enhances the learning experience for readers. Descriptions of real time project prototypes with programming and simulation of Arduino and Scilab.
Author(s): Ambika Nagaraj
eISBN: 978-981-14-7935-9, 2021
Introduction to Sensors in IoT and Cloud Computing Applications provides information about sensors and their applications. Readers are first introduced to the concept of small instruments and their application as sensors. The chapters which follow explain Internet of Things (IoT) architecture while providing notes on the implementation, demonstration and related issues of IoT systems. The book continues to explore the topic by providing information about sensor-cloud infrastructure, mobile cloud, fog computing (an extension of cloud computing that takes cloud computing to the cutting-edge of networking where data is produced) and integration of IoT devices with cloud computing. The book also presents notes on the taxonomy of fog-computing systems. The six chapters in this book provide essential information for general readers, and students of computer science to understand the basics of cloud computing networks, related concepts and applications.