This book describes how the principle of self-sufficiency can be applied to a reconfigurable modular robotic organism. It shows the design considerations for a novel REPLICATOR robotic platform, both hardware and software, featuring the behavioral characteristics of social insect colonies. Following a comprehensive overview of some of the bio-inspired techniques already available, and of the state-of-the-art in re-configurable modular robotic systems, the book presents a novel power management system with fault-tolerant energy sharing, as well as its implementation in the REPLICATOR robotic modules. In addition, the book discusses, for the first time, the concept of "artificial energy homeostasis" in the context of a modular robotic organism, and shows its verification on a custom-designed simulation framework in different dynamic power distribution and fault tolerance scenarios. This book offers an ideal reference guide for both hardware engineers and software developers involved in the design and implementation of autonomous robotic systems.

The author defines "Geometric Algebra Computing" as the geometrically intuitive development of algorithms using geometric algebra with a focus on their efficient implementation, and the goal of this book is to lay the foundations for the widespread use of geometric algebra as a powerful, intuitive mathematical language for engineering applications in academia and industry. The related technology is driven by the invention of conformal geometric algebra as a 5D extension of the 4D projective geometric algebra and by the recent progress in parallel processing, and with the specific conformal geometric algebra there is a growing community in recent years applying geometric algebra to applications in computer vision, computer graphics, and robotics. This book is organized into three parts: in Part I the author focuses on the mathematical foundations; in Part II he explains the interactive handling of geometric algebra; and in Part III he deals with computing technology for high-performance implementations based on geometric algebra as a domain-specific language in standard programming languages such as C++ and OpenCL. The book is written in a tutorial style and readers should gain experience with the associated freely available software packages and applications. The book is suitable for students, engineers, and researchers in computer science, computational engineering, and mathematics.

This book presents the edited proceedings of the 16th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2017), which was held on May 24-26, 2017 in Wuhan, China. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, share their experiences and exchange new ideas and information. The research results included relate to all aspects (theory, applications and tools) of computer and information science, and discuss the practical challenges encountered and the solutions adopted to solve them. The work selected represents 17 of the most promising papers from the conference, written by authors who are certain to make further significant contributions to the field of computer and information science.

This illuminating collection offers a fresh look at the very latest advances in the field of embedded computer vision. Emerging areas covered by this comprehensive text/reference include the embedded realization of 3D vision technologies for a variety of applications, such as stereo cameras on mobile devices. Recent trends towards the development of small unmanned aerial vehicles (UAVs) with embedded image and video processing algorithms are also examined. Topics and features: discusses in detail three major success stories - the development of the optical mouse, vision for consumer robotics, and vision for automotive safety; reviews state-of-the-art research on embedded 3D vision, UAVs, automotive vision, mobile vision apps, and augmented reality; examines the potential of embedded computer vision in such cutting-edge areas as the Internet of Things, the mining of large data streams, and in computational sensing; describes historical successes, current implementations, and future challenges.

This textbook provides a step-by-step approach to numerical methods in engineering modelling. The authors provide a consistent treatment of the topic, from the ground up, to reinforce for students that numerical methods are a set of mathematical modelling tools which allow engineers to represent real-world systems and compute features of these systems with a predictable error rate. Each method presented addresses a specific type of problem, namely root-finding, optimization, integral, derivative, initial value problem, or boundary value problem, and each one encompasses a set of algorithms to solve the problem given some information and to a known error bound. The authors demonstrate that after developing a proper model and understanding of the engineering situation they are working on, engineers can break down a model into a set of specific mathematical problems, and then implement the appropriate numerical methods to solve these problems.

"Progress in Expressive Image Synthesis" (MEIS2015), was held in Fukuoka, Japan, September 25-27, 2015. The aim of the symposium was to provide a unique venue where various issues in computer graphics (CG) application fields could be discussed by mathematicians, CG researchers, and practitioners. Through the previous symposiums MEIS2013 and MEIS2014, mathematicians as well as CG researchers have recognized that CG is a specific and practical activity derived from mathematical theories. Issues found in CG broaden the field of mathematics and vice versa, and CG visualizes mathematical theories in an aesthetic manner. In this volume, the editors aim to provoke interdisciplinary research projects through the peer-reviewed papers and poster presentations at the this year's symposium. This book captures interactions among mathematicians, CG researchers, and practitioners sharing important, state-of-the-art issues in graphics and visual perception. The book is suitable for all CG researchers seeking open problem areas and especially for those entering the field who have not yet selected a research direction.

This book highlights the ability of neural networks (NNs) to be excellent pattern matchers and their importance in information retrieval (IR), which is based on index term matching. The book defines a new NN-based method for learning image similarity and describes how to use fuzzy Gaussian neural networks to predict personality.It introduces the fuzzy Clifford Gaussian network, and two concurrent neural models: (1) concurrent fuzzy nonlinear perceptron modules, and (2) concurrent fuzzy Gaussian neural network modules.Furthermore, it explains the design of a new model of fuzzy nonlinear perceptron based on alpha level sets and describes a recurrent fuzzy neural network model with a learning algorithm based on the improved particle swarm optimization method.

This book shows cognitive scientists in training how mathematics, computer science and science can be usefully and seamlessly intertwined. It is a follow-up to the first two volumes on mathematics for cognitive scientists, and includes the mathematics and computational tools needed to understand how to compute the terms in the Fourier series expansions that solve the cable equation. The latter is derived from first principles by going back to cellular biology and the relevant biophysics. A detailed discussion of ion movement through cellular membranes, and an explanation of how the equations that govern such ion movement leading to the standard transient cable equation are included. There are also solutions for the cable model using separation of variables, as well an explanation of why Fourier series converge and a description of the implementation of MatLab tools to compute the solutions. Finally, the standard Hodgkin - Huxley model is developed for an excitable neuron and is solved using MatLab.

This book provides an overview of the research work on data privacy and privacy enhancing technologies carried by the participants of the ARES project. ARES (Advanced Research in Privacy an Security, CSD2007-00004) has been one of the most important research projects funded by the Spanish Government in the fields of computer security and privacy. It is part of the now extinct CONSOLIDER INGENIO 2010 program, a highly competitive program which aimed to advance knowledge and open new research lines among top Spanish research groups. The project started in 2007 and will finish this 2014. Composed by 6 research groups from 6 different institutions, it has gathered an important number of researchers during its lifetime. Among the work produced by the ARES project, one specific work package has been related to privacy. This books gathers works produced by members of the project related to data privacy and privacy enhancing technologies. The presented works not only summarize important research carried in the project but also serve as an overview of the state of the art in current research on data privacy and privacy enhancing technologies.

This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows readers to gain a practical working understanding of the content. This updated new edition presents recently published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep learning, big data and cloud computing. Each chapter features state-of-the-art descriptions and significant research findings. The topics covered include: * multilayer perceptron; * the Hopfield network; * associative memory models;* clustering models and algorithms; * t he radial basis function network; * recurrent neural networks; * nonnegative matrix factorization; * independent component analysis; *probabilistic and Bayesian networks; and * fuzzy sets and logic. Focusing on the prominent accomplishments and their practical aspects, this book provides academic and technical staff, as well as graduate students and researchers with a solid foundation and comprehensive reference on the fields of neural networks, pattern recognition, signal processing, and machine learning.

Mismatch or best match? This book demonstrates that best matching of individual entities to each other is essential to ensure smooth conduct and successful competitiveness in any distributed system, natural and artificial. Interactions must be optimized through best matching in planning and scheduling, enterprise network design, transportation and construction planning, recruitment, problem solving, selective assembly, team formation, sensor network design, and more. Fundamentals of best matching in distributed and collaborative systems are explained by providing: Methodical analysis of various multidimensional best matching processes Comprehensive taxonomy, comparing different best matching problems and processes Systematic identification of systems' hierarchy, nature of interactions, and distribution of decision-making and control functions Practical formulation of solutions based on a library of best matching algorithms and protocols, ready for direct applications and apps development. Designed for both academics and practitioners, oriented to systems engineers and applied operations researchers, diverse types of best matching processes are explained in production, manufacturing, business and service, based on a new reference model developed at Purdue University PRISM Center: "The PRISM Taxonomy of Best Matching". The book concludes with major challenges and guidelines for future basic and applied research in the area of best matching.

This book presents the state-of-the-art in various aspects of analysis and mining of online social networks. Within the broader context of online social networks, it focuses on important and upcoming topics of social network analysis and mining such as the latest in sentiment trends research and a variety of techniques for community detection and analysis. The book collects chapters that are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'2015), which was held in Paris, France in August 2015. All papers have been peer reviewed and checked carefully for overlap with the literature. The book will appeal to students and researchers in social network analysis/mining and machine learning.

Based on the proceedings of a conference on Influence Diagrams for Decision Analysis, Inference and Prediction held at the University of California at Berkeley in May of 1988, this is the first book devoted to the subject. The editors have brought together recent results from researchers actively investigating influence diagrams and also from practitioners who have used influence diagrams in developing models for problem-solving in a wide range of fields.

This book presents the latest achievements in the theory and practice of SEMS Group interaction by scientists from the Russian Academy of Sciences. It also discusses the development of methods for the design and simulation of SEMS Group interaction based on the principles of safety, flexibility and adaptability in behavior and intelligence and parallelism in information processing, computation and control. Recently, the task has been to ensure the functioning of robots within the framework of collective collaboration, so that they function efficiently, reliably and safely in real time. The topics covered include, but are not limited to, the following: - the planning behavior of the SEMS group;- methods and principles of designing of automatic control systems;- mathematical and computer modeling group interaction;- safety, flexibility and adaptability of the SEMS Group;- information-measuring soft- and hardware. This book is intended for students, scientists and engineers specializing in the field of smart electromechanical systems and robotics.

The objective of this book is to contribute to the development of the intelligent information and database systems with the essentials of current knowledge, experience and know-how. The book contains a selection of 40 chapters based on original research presented as posters during the 8th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2016) held on 14-16 March 2016 in Da Nang, Vietnam. The papers to some extent reflect the achievements of scientific teams from 17 countries in five continents. The volume is divided into six parts: (a) Computational Intelligence in Data Mining and Machine Learning, (b) Ontologies, Social Networks and Recommendation Systems, (c) Web Services, Cloud Computing, Security and Intelligent Internet Systems, (d) Knowledge Management and Language Processing, (e) Image, Video, Motion Analysis and Recognition, and (f) Advanced Computing Applications and Technologies. The book is an excellent resource for researchers, those working in artificial intelligence, multimedia, networks and big data technologies, as well as for students interested in computer science and other related fields.

This volume is the first of the new series Advances in Dynamics and Delays. It offers the latest advances in the research of analyzing and controlling dynamical systems with delays, which arise in many real-world problems. The contributions in this series are a collection across various disciplines, encompassing engineering, physics, biology, and economics, and some are extensions of those presented at the IFAC (International Federation of Automatic Control) conferences since 2011. The series is categorized in five parts covering the main themes of the contributions: * Stability Analysis and Control Design * Networks and Graphs * Time Delay and Sampled-Data Systems * Computational and Software Tools * Applications This volume will become a good reference point for researchers and PhD students in the field of delay systems, and for those willing to learn more about the field, and it will also be a resource for control engineers, who will find innovative control methodologies for relevant applications, from both theory and numerical analysis perspectives.

This edited monograph includes state-of-the-art contributions on continuous time dynamical networks with delays. The book is divided into four parts. The first part presents tools and methods for the analysis of time-delay systems with a particular attention on control problems of large scale or infinite-dimensional systems with delays. The second part of the book is dedicated to the use of time-delay models for the analysis and design of Networked Control Systems. The third part of the book focuses on the analysis and design of systems with asynchronous sampling intervals which occur in Networked Control Systems. The last part of the book exposes several contributions dealing with the design of cooperative control and observation laws for networked control systems. The target audience primarily comprises researchers and experts in the field of control theory, but the book may also be beneficial for graduate students.

The aim of this book is to explain to high-performance computing (HPC) developers how to utilize the Intel(r) Xeon Phi series products efficiently. To that end, it introduces some computing grammar, programming technology and optimization methods for using many-integrated-core (MIC) platforms and also offers tips and tricks for actual use, based on the authors first-hand optimization experience.

The material is organized in three sections. The first section, Basics of MIC, introduces the fundamentals of MIC architecture and programming, including the specific Intel MIC programming environment. Next, the section on Performance Optimization explains general MIC optimization techniques, which are then illustrated step-by-step using the classical parallel programming example of matrix multiplication. Finally, Project development presents a set of practical and experience-driven methods for using parallel computing in application projects, including how to determine if a serial or parallel CPU program is suitable for MIC and how to transplant a program onto MIC.

This book appeals to two main audiences: First, software developers for HPC applications it will enable them to fully exploit the MIC architecture and thus achieve the extreme performance usually required in biological genetics, medical imaging, aerospace, meteorology and other areas of HPC. Second, students and researchers engaged in parallel and high-performance computing it will guide them on how to push the limits of system performance for HPC applications. "

This book is focused on the Internet of Things (IoT) services and smart environments that can be of assistance to the elderly and individuals living with dementia or some sensory impairment. The book outlines the requirements of the systems that aim to furnish some digital sensory or cognitive assistance to the individuals and their caregivers. Internet of Things and Smart Environments: Assistive Technologies for Disability, Dementia, and Aging covers the important evolutions of the IoT, the sensors, actuators, wireless communication and pervasive computing systems, and other enabling technologies that power up this megatrend infrastructure. The use of the IoT-based systems in improving the conventional assistive technologies and provisions of ambient assisted living are also covered. The book takes an impartial, and yet holistic, view to providing research insights and inspirations for more development works in the areas related to assistive IoT. It will show the potentials of using normally available interactive devices, like smartphones or smart TVs, which can be supplemented with low-cost gadgets or apps to provide assistive capabilities. It aims to accentuate the need for taking a comprehensive and combinatory view of the comprising topics and approaches that are based on the visions and ideas from all stakeholders. The book will examine these points and considerations to conclude with recommendations for future development works and research directions. This book can be of value to a diverse array of audience. The researchers and developers in healthcare and medicine, aged care and disability services, as well as those working in the IoT-related fields, may find many parts of this book useful and stimulating. It can be of great value to postgraduate and research students working in these areas. It can also be adapted for use in upper-level classroom courses relevant to communication and smart technologies, IoT applications, and assistive technologies. Many parts of the book can be of interest to the elderly and individuals living with a disability, as well as their families and caregivers. From an industry perspective, it can be of interest to software, hardware, and particularly app developers working on the IoT applications, smart homes and environments, and assistive technologies for the elderly and people living with disability or dementia.

Traditional machining has many limitations in today's technology-driven world, which has caused industrial professionals to begin implementing various optimization techniques within their machining processes. The application of methods including machine learning and genetic algorithms has recently transformed the manufacturing industry and created countless opportunities in non-traditional machining methods. Significant research in this area, however, is still considerably lacking. Machine Learning Applications in Non-Conventional Machining Processes is a collection of innovative research on the advancement of intelligent technology in industrial environments and its applications within the manufacturing field. While highlighting topics including evolutionary algorithms, micro-machining, and artificial neural networks, this book is ideally designed for researchers, academicians, engineers, managers, developers, practitioners, industrialists, and students seeking current research on intelligence-based machining processes in today's technology-driven market.

The book offers a snapshot of the theories and applications of soft computing in the area of complex systems modeling and control. It presents the most important findings discussed during the 5th International Conference on Modelling, Identification and Control, held in Cairo, from August 31-September 2, 2013. The book consists of twenty-nine selected contributions, which have been thoroughly reviewed and extended before their inclusion in the volume. The different chapters, written by active researchers in the field, report on both current theories and important applications of soft-computing. Besides providing the readers with soft-computing fundamentals, and soft-computing based inductive methodologies/algorithms, the book also discusses key industrial soft-computing applications, as well as multidisciplinary solutions developed for a variety of purposes, like windup control, waste management, security issues, biomedical applications and many others. It is a perfect reference guide for graduate students, researchers and practitioners in the area of soft computing, systems modeling and control.

The book shows how eastern and western perspectives and conceptions can be used to addresses recent topics laying at the crossroad between philosophy and cognitive science. It reports on new points of view and conceptions discussed during the International Conference on Philosophy and Cognitive Science (PCS2013), held at the Sun Yat-sen University, in Guangzhou, China, and the 2013 Workshop on Abductive Visual Cognition, which took place at KAIST, in Deajeon, South Korea. The book emphasizes an ever-growing cultural exchange between academics and intellectuals coming from different fields. It juxtaposes research works investigating new facets on key issues between philosophy and cognitive science, such as the role of models and causal representations in science; the status of theoretical concepts and quantum principles; abductive cognition, vision, and visualization in science from an eco-cognitive perspective. Further topics are: ignorance immunization in reasoning; moral cognition, violence, and epistemology; and models and biomorphism. The book, which presents a unique and timely account of the current state-of-the art on various aspects in philosophy and cognitive science, is expected to inspire philosophers, cognitive scientists and social scientists, and to generate fruitful exchanges and collaboration among them.

This volume contains nineteen research papers belonging to the areas of computational statistics, data mining, and their applications. Those papers, all written specifically for this volume, are their authors' contributions to honour and celebrate Professor Jacek Koronacki on the occcasion of his 70th birthday. The book's related and often interconnected topics, represent Jacek Koronacki's research interests and their evolution. They also clearly indicate how close the areas of computational statistics and data mining are.

Between Certainty & Uncertainty is a one-of a-kind short course on statistics for students, engineers and researchers. It is a fascinating introduction to statistics and probability with notes on historical origins and 80 illustrative numerical examples organized in the five units:

. Chapter 1 "Descriptive Statistics" Compressing small samples, basic averages - mean and variance, their main properties including God s proof; linear transformations and "z-scored" statistics .

. Chapter 2 "Grouped data" Udny Yule s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles.

. Chapter 3 "Regression and correlation" Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt s cloud. What in fact measures the correlation coefficient?

. Chapter 4 "Binomial distribution" Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal s Arithmetical Triangle. Bernoulli s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli s Weak Law of Large Numbers and others.

. Chapter 5 "Normal distribution and binomial heritage" Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.

. Chapter 1 "Descriptive Statistics" Compressing small samples, basic averages - mean and variance, their main properties including God s proof; linear transformations and "z-scored" statistics .

. Chapter 2 "Grouped data" Udny Yule s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles.

. Chapter 3 "Regression and correlation" Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt s cloud. What in fact measures the correlation coefficient?

. Chapter 4 "Binomial distribution" Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal s Arithmetical Triangle. Bernoulli s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli s Weak Law of Large Numbers and others.

. Chapter 5 "Normal distribution and binomial heritage" Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.

. Chapter 5 "Normal distribution and binomial heritage" Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.

"

The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in financial systems when these are described in the form of nonlinear ordinary differential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial differential equations (e.g. the Black-Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to support financial engineers in decision making. The application of state-space models in financial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for finance can be eliminated. It also allows methods of fault-free performance and optimality in the management of assets and capitals and methods assuring stability in the functioning of financial systems to be established. Covering the following key areas of financial engineering: (i) control and stabilization of financial systems dynamics, (ii) state estimation and forecasting, and (iii) statistical validation of decision-making tools, the book can be used for teaching undergraduate or postgraduate courses in financial engineering. It is also a useful resource for the engineering and computer science community