There is widespread interest in the way that smart energy control systems, such as assessment and monitoring techniques for low carbon, nearly-zero energy and net positive buildings can contribute to a Sustainable future, for current and future generations. There is a turning point on the horizon for the supply of energy from finite resources such as natural gas and oil become less reliable in economic terms and extraction become more challenging, and more unacceptable socially, such as adverse public reaction to 'fracking'. Thus, in 2016 these challenges are having a major influence on the design, optimisation, performance measurements, operation and preservation of: buildings, neighbourhoods, cities, regions, countries and continents. The source and nature of energy, the security of supply and the equity of distribution, the environmental impact of its supply and utilization, are all crucial matters to be addressed by suppliers, consumers, governments, industry, academia, and financial institutions. This book entitled 'Smart Energy Control Systems for Sustainable Buildings' contains eleven chapters written by international experts based on enhanced conference papers presented at the Sustainability and Energy in Buildings International conference series. This book will be of interest to University staff and students; and also industry practioners.

Highlights key research currently being undertaken within the field of telepresence, providing the most detailed account of the field to date, advancing our understanding of a fundamental property of all media - the illusion of presence; the sense of "being there" inside a virtual environment, with actual or virtual others. This collection has been put together by leading international scholars from America, Europe, and Asia. Together, they describe the state-of-the-art in presence theory, research and technology design for an advanced academic audience. Immersed in Media provides research that can help designers optimize presence for users of advanced media technologies such as virtual and augmented reality, collaborative social media, robotics, and artificial intelligence and lead us to better understand human cognition, emotion and behaviour.

The first book of its kind devoted to this topic, this comprehensive text/reference presents state-of-the-art research and reviews current challenges in the application of computer vision to problems in sports. Opening with a detailed introduction to the use of computer vision across the entire life-cycle of a sports event, the text then progresses to examine cutting-edge techniques for tracking the ball, obtaining the whereabouts and pose of the players, and identifying the sport being played from video footage. The work concludes by investigating a selection of systems for the automatic analysis and classification of sports play. The insights provided by this pioneering collection will be of great interest to researchers and practitioners involved in computer vision, sports analysis and media production.

This book gathers a selection of the best papers presented during the 14th International Conference on Location Based Services, which was held in Zurich (Switzerland) between the 15th and 17th January 2018. It presents a general overview of recent research activities related to location based services. Such activities have grown in importance over the past several years, especially those concerning outdoor/indoor positioning, smart environments, spatial modeling, personalization and context-awareness, cartographic communication, novel user interfaces, crowdsourcing, social media, big data analysis, usability and privacy.

The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.

Ontologies form an indispensable basis for modeling and engineering languages for business enterprise and information systems: fostering a need for the integration of structural and behavioral aspects in domain-oriented ontologies.

The book presents an integrative review of paleoneurology, the study of endocranial morphology in fossil species. The main focus is on showing how computed methods can be used to support advances in evolutionary neuroanatomy, paleoanthropology and archaeology and how they have contributed to creating a completely new perspective in cognitive neuroscience. Moreover, thanks to its multidisciplinary approach, the book addresses students and researchers approaching human paleoneurology from different angles and for different purposes, such as biologists, physicians, anthropologists, archaeologists and computer scientists. The individual chapters, written by international experts, represent authoritative reviews of the most important topics in the field. All the concepts are presented in an easy-to-understand style, making them accessible to university students, newcomers and also to anyone interested in understanding how methods like biomedical imaging, digital anatomy and computed and multivariate morphometrics can be used for analyzing ontogenetic and phylogenetic changes according to the principles of functional morphology, morphological integration and modularity.

This book explains the most prominent and some promising new, general techniques that combine metaheuristics with other optimization methods. A first introductory chapter reviews the basic principles of local search, prominent metaheuristics, and tree search, dynamic programming, mixed integer linear programming, and constraint programming for combinatorial optimization purposes. The chapters that follow present five generally applicable hybridization strategies, with exemplary case studies on selected problems: incomplete solution representations and decoders; problem instance reduction; large neighborhood search; parallel non-independent construction of solutions within metaheuristics; and hybridization based on complete solution archives. The authors are among the leading researchers in the hybridization of metaheuristics with other techniques for optimization, and their work reflects the broad shift to problem-oriented rather than algorithm-oriented approaches, enabling faster and more effective implementation in real-life applications. This hybridization is not restricted to different variants of metaheuristics but includes, for example, the combination of mathematical programming, dynamic programming, or constraint programming with metaheuristics, reflecting cross-fertilization in fields such as optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation. The book is a valuable introduction and reference for researchers and graduate students in these domains.

Including contributions from leading experts in the field, this book covers applications and developments of heuristic search methods for solving complex optimization problems. The book covers various local search strategies including genetic algorithms, simulated annealing, tabu search and hybrids thereof. These methods have proved extraordinarily successful by solving some of the most difficult, real-world problems. At the interface between Artificial Intelligence and Operational Research, research in this exciting area is progressing apace spurred on by the needs of industry and commerce. The introductory chapter provides a clear overview of the basic techniques and useful pointers to further reading and to current research. The second section of the book covers some of the most recent and exciting developments of the basic techniques, with suggestions not only for extending and improving these but also for hybridizing and incorporating automatic adaption. The third section contains a number of case studies, surveys and comparative studies which span a wide range of application areas ranging from the classic Steiner tree problem to more practical problems arising in telecommunications and data analysis. The coverage of the latest research and the illustrative case studies will ensure that the book is invaluable for researchers and professionals with an interest in heuristic search methods.

Local Area Networks (LANs) have a high potential for alleviating many of the problems associated with stand-alone microcomputers. Networking microcomputers to share information, software and hardware, as well as facilite electronic mail is not only feasible and desirable, but also logical. Harry Kibirige's issue-oriented study explores microcomputer networking systems with particular emphasis on LANs. Although his analysis emphasizes issues from an information scientist's perspective, readers who want to gain an understanding of LAN technology and its applications should find it useful. Written with a minimum of jargon, the book can be used in academic, corporate, library, federal and state agency, and not-for-profit organizational settings. The author begins with an introduction to the general concepts surrounding LANs. He discusses LANs as structures for processing information and compares and contrasts them with other structures such as time-sharing systems. Also considered are salient factors concerned with LAN design and implementation. In a chapter devoted to choosing an LAN, Kibirige explains in detail the fundamental problems of choice as well as steps which should be taken in making a final selection. Other issues covered are the relationship of LANs to other existing automation programs, significant management issues, currently implemented alternatives to LANS, technology trends which will impact the future of LANs, and social issues concerned with LANs. Finally, Kibirige summarizes the results of the CUNY study of microcomputer networking systems, a report that emphasized information center/libraries.

This book examines the principles of and advances in personalized task recommendation in crowdsourcing systems, with the aim of improving their overall efficiency. It discusses the challenges faced by personalized task recommendation when crowdsourcing systems channel human workforces, knowledge, skills and perspectives beyond traditional organizational boundaries. The solutions presented help interested individuals find tasks that closely match their personal interests and capabilities in a context of ever-increasing opportunities of participating in crowdsourcing activities. In order to explore the design of mechanisms that generate task recommendations based on individual preferences, the book first lays out a conceptual framework that guides the analysis and design of crowdsourcing systems. Based on a comprehensive review of existing research, it then develops and evaluates a new kind of task recommendation service that integrates with existing systems. The resulting prototype provides a platform for both the field study and the practical implementation of task recommendation in productive environments.

This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of Big Data Analysis along with its pitfalls and challenges.

The goal of this book is to crystallize the emerging mobile computing technologies and trends into positive efforts to focus on the most promising solutions in services computing. Many toys built today are increasingly using these technologies together and it is important to understand the various research and practical issues. The book will provide clear proof that mobile technologies are playing an ever increasing important and critical role in supporting toy computing, which is a new research discipline in computer science. It is also expected that the book will further research new best practices and directions in toy computing. The goal of this book is to bring together academics and practitioners to describe the use and synergy between the above-mentioned technologies. This book is mainly intended for researchers and students working in computer science and engineering, and for toy industry technology providers, having particular interests in mobile services. The wide range of authors of this book will help the various communities understand both specific and common problems. This book facilities software developers and researchers to become more aware of this challenging research opportunity. As well, the book is soliciting shall provide valuable strategic outlook on the emerging toy industry.

This monograph presents the concept of agents and agent systems. It starts with a formal approach and then presents examples of practical applications. In order to form the principles of construction of autonomous agents, a model of the agent is introduced. Subsequent parts of the monograph include several examples of applications of the term agent. Descriptions of different examples of applications of agent systems in such fields as evolution systems, mobile robot systems, artificial intelligence systems are given. The book constitutes an outline of methodology of the design and realization of agent systems based on the M-agent architecture oriented on different areas of applications.

This thesis develops several systematic and unified approaches for analyzing dynamic systems with positive characteristics or a more general cone invariance property. Based on these analysis results, it uses linear programming tools to address static output feedback synthesis problems with a focus on optimal gain performances. Owing to their low computational complexity, the established controller design algorithms are applicable for large-scale systems. The theory and control strategies developed will not only be useful in handling large-scale positive delay systems with improved solvability and at lower cost, but also further our understanding of the system characteristics in other related areas, such as distributed coordination of networked multi-agent systems, formation control of multiple robots.

This book introduces numerous algorithmic hybridizations between both worlds that show how machine learning can improve and support evolution strategies. The set of methods comprises covariance matrix estimation, meta-modeling of fitness and constraint functions, dimensionality reduction for search and visualization of high-dimensional optimization processes, and clustering-based niching. After giving an introduction to evolution strategies and machine learning, the book builds the bridge between both worlds with an algorithmic and experimental perspective. Experiments mostly employ a (1+1)-ES and are implemented in Python using the machine learning library scikit-learn. The examples are conducted on typical benchmark problems illustrating algorithmic concepts and their experimental behavior. The book closes with a discussion of related lines of research.

This book presents a unique approach to stream data mining. Unlike the vast majority of previous approaches, which are largely based on heuristics, it highlights methods and algorithms that are mathematically justified. First, it describes how to adapt static decision trees to accommodate data streams; in this regard, new splitting criteria are developed to guarantee that they are asymptotically equivalent to the classical batch tree. Moreover, new decision trees are designed, leading to the original concept of hybrid trees. In turn, nonparametric techniques based on Parzen kernels and orthogonal series are employed to address concept drift in the problem of non-stationary regressions and classification in a time-varying environment. Lastly, an extremely challenging problem that involves designing ensembles and automatically choosing their sizes is described and solved. Given its scope, the book is intended for a professional audience of researchers and practitioners who deal with stream data, e.g. in telecommunication, banking, and sensor networks.

This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning. Now in one self-contained volume, this book systematically covers key statistical, probabilistic, combinatorial and geometric ideas for understanding, analyzing and developing nearest neighbor methods. Gerard Biau is a professor at Universite Pierre et Marie Curie (Paris). Luc Devroye is a professor at the School of Computer Science at McGill University (Montreal).

This is the proceedings of the Eighth International Conference on Design Computing and Cognition (DCC'18) held at the Polytecnico di Milano in Italy. This volume presents both advances in theory and applications and demonstrates the depth and breadth of design computing and design cognition. Design thinking, the label given to the acts of designing, has become a paradigmatic view that has transcended the discipline of design and is now widely used in business and elsewhere. As a consequence there is an increasing interest in design research. This volume contains papers that represent the state-of-the-art research and developments in design computing and design cognition. This book is of particular interest to researchers, developers and users of advanced computation in design and those who need to gain a better understanding of designing that can be obtained through empirical studies.

The field of mechatronics (which is the synergistic combination of precision mechanical engineering, electronic control and systems thinking in the design of products and manufacturing processes) is gaining much attention in industries and academics. It was detected that the topics of computer vision, control and robotics are imperative for the successful of mechatronics systems. This book includes several chapters which report successful study cases about computer vision, control and robotics. The readers will have the latest information related to mechatronics, that contains the details of implementation, and the description of the test scenarios.

DeLancey shows that our best philosophical and scientific understanding of the emotions provides essential insights on key questions in the philosophy of mind and artificial intelligence. This is the first such book to offer this perspective. Passionate Engines also provides a bold new approach to the study of the mind based on the latest scientific research and along the way, provides an accessible overview of the science of emotion, with minimal jargon and explanation of the technical issues that arise. It is accessible to a wide range of readers, including philosophers, psychologists, computer scientists, and others in disciplines touching on cognitive science.

There is a deep desire in men, in order to reproduce intelligence and place it in a machine. Neural Networks are an attempt to reproduce the synaptic connections of our brain in a computer. Duplicating the way we use our neurons to think in a machine, it is expected to have a device that could be able to do intelligent tasks, the ones reserved just to humans some time ago. Neural Network is a reality now, not a fantasy, and they have been made in order to recognize patterns (a face, a photograph or a song, are patterns) and forecast trends. I have seen many books about this subject in my life. All of them are hard to read, and tedious to learn, so I decided to make my own one.

For beginner readers, I have tried to use a simple language, in order to be understood by anyone who wants to know about nets. An easy to read, practical and concise work. If you are interested in the brain functions and how can we simulate it in a computer, youll get here a differenty to penetrate into their secrets. For advanced readers who want to make their own nets, I have included a methodology for building neural networks and complete sample computer source-code with tricks that will save you a lot of time while designing it.