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.

This book provides a thorough investigation of the application of chaos theory and fractal analysis to computer vision. The field of chaos theory has been studied in dynamical physical systems, and has been very successful in providing computational models for very complex problems ranging from weather systems to neural pathway signal propagation. Computer vision researchers have derived motivation for their algorithms from biology and physics for many years as witnessed by the optical flow algorithm, the oscillator model underlying graphical cuts and of course neural networks. These algorithms are very helpful for a broad range of computer vision problems like motion segmentation, texture analysis and change detection. The contents of this book include chapters in biological vision systems, foundations of chaos and fractals, behavior of images and image sequences in phase space, mathematical measures for analyzing phase space, applications to pre-attentive vision and applications to post-attentive vision. This book is intended for graduate students, upper division undergraduates, researchers and practitioners in image processing and computer vision. The readers will develop a solid understanding of the concepts of chaos theory and their application to computer vision. Readers will be introduced to a new way of thinking about computer vision problems from the perspective of complex dynamical systems. This new approach will provide them a deeper understanding of the various phenomena present in complex image scenes.

Agent-based Computational Economics using NetLogo explores how researchers can create, use and implement multi-agent computational models in Economics by using NetLogo software platform. Problems of economic science can be solved using multi-agent modelling (MAM). This technique uses a computer model to simulate the actions and interactions of autonomous entities in a network, in order to analyze the effects on the entire economic system. MAM combines elements of game theory, complex systems, emergence and evolutionary programming. The Monte Carlo method is also used in this e-book to introduce random elements. The 11 models presented in this text simulate the simultaneous operations of several agents in an attempt to recreate and predict complex economic phenomena. This e-book explains the topic in a systematic manner, starting with an introduction for readers followed subsequently by methodology and implementation using NetLogo. The volume ends with conclusions based on the results of the experiments presented. The e-book is intended as a concise and vital resource for economists, applied mathematicians, social sciences scientists, systems analysts, operations researchers and numerical analysts

Advances in Face Image Analysis: Theory and applications describes several approaches to facial image analysis and recognition. Eleven chapters cover advances in computer vision and pattern recognition methods used to analyze facial data. The topics addressed in this book include automatic face detection, 3D face model fitting, robust face recognition, facial expression recognition, face image data embedding, model-less 3D face pose estimation and image-based age estimation. The chapters are also written by experts from a different research groups. Readers will, therefore, have access to contemporary knowledge on facial recognition with some diverse perspectives offered for individual techniques. The book is a useful resource for a wide audience such as i) researchers and professionals working in the field of face image analysis, ii) the entire pattern recognition community interested in processing and extracting features from raw face images, and iii) technical experts as well as postgraduate computer science students interested in cutting edge concepts of facial image recognition.

Geosimulation has recently emerged at the intersection of Geographic Information Science, Complex Systems Theory and Computer Science. Geosimulation aims at understanding the dynamics of complex human-driven spatial systems through the use of spatially explicit computer simulation. The approaches and tools for validating Geosimulation models are especially important for understanding their complex and spatially heterogeneous outcomes. The Ebook presents the recent conceptual and methodological advances achieved in the field. It should be very useful for scientists and graduate students working in the fields of Complex Systems Modelling, Geocomputation, Science, Geography, Regional Science, Computer Science, Artificial Intelligence, Environment Simulation and Modeling, and Environmental Engineering.

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.

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.

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.

"Software Engineering now occupies a central place in the development of technology and in the advancement of the economy. From telecommunications to aerospace and from cash registers to medical imaging, software plays a vital and often decisive role in the successful accomplishment of a variety of projects. The creation of software requires a variety of techniques, tools, and especially, properly skilled engineers. This e-book focuses on core concepts and approaches that have proven useful to the author time and time again on many industry projects over a quarter century of research, development, and teaching. Enduring, lasting, and meaningful concepts, ideas, and methods in software engineering are presented and explained. The book covers essential topics of the field of software engineering with a focus on practical and commonly used techniques along with advanced topics useful for extending the reader’s knowledge regarding leading edge approaches. Building on the industrial, research, and teaching experiences of the author, a dynamic treatment of the subject is presented incorporating a wide body of published findings and techniques, novel organization of material, original concepts, contributions from specialists, and the clear, concise writing required to keep the attention of readers. Using over 20 years of lecture notes, transcripts, course notes, view graphs, published articles, and other materials, as well as industry experience on commercial software product development a “virtual toolbox” of software techniques are shared in this volume."

Enterprise Architecture (EA) has evolved to become a prominent presence in today’s information systems and technology landscape. The EA discipline is rich in frameworks, methodologies, and the like. However, the question of ‘value’ for business ;professionals remains largely unanswered – that is, how best can Enterprise Architecture and Enterprise Architects deliver value to the enterprise? Enterprise Architecture for Business Success answers this question. Enterprise Architecture for Business Success is primarily intended for IT professionals working in the area of Enterprise Architecture. The eBook gives practical insights into what constitutes EA and how it might be practiced in a typical resource constrained business environment. The contents of the eBook include a brief guideline about EA systems and terminology, followed by notes on how to design enterprise systems in line with business strategies. The eBook also presents case studies which help to demonstrate the distance between theory and reality when it comes to optimizing IT infrastructure for successfully achieving business goals. Lengthy theoretical discussions are avoided in favor of focusing more on the practice and tools of EA. Readers will find value in this eBook, whether they are an IT consultant or a manager, an EA team lead or member, or just someone keen to learn about real-world EA.