This book is the product of Research Study Group (RSG) 13 on "Human Engineering Evaluation on the Use of Colour in Electronic Displays," of Panel 8, "Defence Applications of Human and Biomedical Sciences," of the NATO Defence Research Group. RSG 13 was chaired by Heino Widdel (Germany) and consisted of Jeffrey Grossman (United States), Jean-Pierre Menu (France), Giampaolo Noja (Italy, point of contact), David Post (United States), and Jan Walraven (Netherlands). Initially, Christopher Gibson (United Kingdom) and Sharon McFaddon (Canada) participated also. Most of these representatives served previously on the NATO program committee that produced Proceedings of a Workshop on Colour Coded vs. Monochrome Displays (edited by Christopher Gibson and published by the Royal Aircraft Establishment, Farnborough, England) in 1984. RSG 13 can be regarded as a descendent of that program committee. RSG 13 was formed in 1987 for the purpose of developing and distributing guidance regarding the use of color on electronic displays. During our first meeting, we discussed the fact that, although there is a tremendous amount of information available concerning color vision, color perception, colorimetry, and color displays-much of it relevant to display design-it is scattered across numerous texts, journals, conference proceedings, and technical reports. We decided that we could fulfill the RSG's purpose best by producing a book that consolidates and summarizes this information, emphasizing those aspects that are most applicable to display design.

This volume focuses on new challenges in distributed Information Filtering and Retrieval. It collects invited chapters and extended research contributions from the DART 2011 Workshop, held in Palermo (Italy), on September 2011, and co-located with the XII International Conference of the Italian Association on Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world applications. The chapters of this book present a comprehensive review of related works and state of the art. Authors, both practitioners and researchers, shared their results in several topics such as "Multi-Agent Systems", "Natural Language Processing", "Automatic Advertisement", "Customer Interaction Analytics", "Opinion Mining".

Renewable energy sources such as wind power have attracted much attention because they are environmentally friendly, do not produce carbon dioxide and other emitants, and can enhance a nation's energy security. For example, recently more significant amounts of wind power are being integrated into conventional power grids. Therefore, it is necessary to address various important and challenging issues related to wind power systems, which are significantly different from the traditional generation systems. This book is a resource for engineers, practitioners, and decision-makers interested in studying or using the power of computational intelligence based algorithms in handling various important problems in wind power systems at the levels of power generation, transmission, and distribution. Researchers have been developing biologically-inspired algorithms in a wide variety of complex large-scale engineering domains. Distinguished from the traditional analytical methods, the new methods usually accomplish the task through their computationally efficient mechanisms. Computational intelligence methods such as evolutionary computation, neural networks, and fuzzy systems have attracted much attention in electric power systems. Meanwhile, modern electric power systems are becoming more and more complex in order to meet the growing electricity market. In particular, the grid complexity is continuously enhanced by the integration of intermittent wind power as well as the current restructuring efforts in electricity industry. Quite often, the traditional analytical methods become less efficient or even unable to handle this increased complexity. As a result, it is natural to apply computational intelligence as a powerful tool to deal with various important and pressing problems in the current wind power systems. This book presents the state-of-the-art development in the field of computational intelligence applied to wind power systems by reviewing the most up-to-date work and representative practical problems collecting contributions from leading experts in electrical engineering, system engineering, and other disciplines.

Foundations of Genetic Algorithms 1991 (FOGA 1) discusses the theoretical foundations of genetic algorithms (GA) and classifier systems. This book compiles research papers on selection and convergence, coding and representation, problem hardness, deception, classifier system design, variation and recombination, parallelization, and population divergence. Other topics include the non-uniform Walsh-schema transform; spurious correlations and premature convergence in genetic algorithms; and variable default hierarchy separation in a classifier system. The grammar-based genetic algorithm; conditions for implicit parallelism; and analysis of multi-point crossover are also elaborated. This text likewise covers the genetic algorithms for real parameter optimization and isomorphisms of genetic algorithms. This publication is a good reference for students and researchers interested in genetic algorithms.

Mining Spatio-Temporal Information Systems, an edited volume is composed of chapters from leading experts in the field of Spatial-Temporal Information Systems and addresses the many issues in support of modeling, creation, querying, visualizing and mining. Mining Spatio-Temporal Information Systems is intended to bring together a coherent body of recent knowledge relating to STIS data modeling, design, implementation and STIS in knowledge discovery. In particular, the reader is exposed to the latest techniques for the practical design of STIS, essential for complex query processing.
Mining Spatio-Temporal Information Systems is structured to meet the needs of practitioners and researchers in industry and graduate-level students in Computer Science.

This book presents the cutting edge developments within a broad field related to robotic sailing. The contributions were presented during the 8th International Robotic Sailing Conference, which has taken place as a part of the 2015 World Robotic Sailing Championships in Mariehamn, Aland (Finland), August 31st - September 4th 2015. Since more than a decade, a series of competitions such as the World Robotic Sailing Championship have stimulated a variety of groups to work on research and development around autonomous sailing robots, which involves boat designers, naval architects, electrical engineers and computer scientists. While many of the challenges in building a truly autonomous sailboat are still unsolved, the books presents the state of the art of research and development within platform optimization, route and stability planning, collision avoidance, power management and boat control.

Intelligent agents are one of the most promising business tools in our information rich world. An intelligent agent consists of a software system capable of performing intelligent tasks within a dynamic and unpredictable environment. They can be characterised by various attributes including: autonomous, adaptive, collaborative, communicative, mobile, and reactive. Many problems are not well defined and the information needed to make decisions is not available. These problems are not easy to solve using conventional computing approaches. Here, the intelligent agent paradigm may play a major role in helping to solve these problems. This book, written for application researchers, covers a broad selection of research results that demonstrate, in an authoritative and clear manner, the applications of agents within our information society.

This book highlights and explains the significance of philosophical, logical, and scientific principles for engineering education/training and engineering works. In so doing, it aims to help to rectify the neglect of philosophy and logic in current education and training programs, which emphasize analytical and numerical methods at the expense of the innovative practical and creative abilities so important for engineering in the past. Individual chapters examine the relation of philosophy, logic, and science to engineering, drawing attention to, for example, the significance of ethics, the relevance of the philosophy of science, and the increasing importance of application of fuzzy logic to engineering. Modeling principles and philosophy in engineering are discussed, and the impact of different education systems, examined. Too often engineers have become reliant on readily available formulations and software; this book offers an antidote, promoting the recognition of artistic and humanitarian aspects and their integration in engineering works.

An Introduction to Fuzzy Logic Applications in Intelligent Systems consists of a collection of chapters written by leading experts in the field of fuzzy sets. Each chapter addresses an area where fuzzy sets have been applied to situations broadly related to intelligent systems. The volume provides an introduction to and an overview of recent applications of fuzzy sets to various areas of intelligent systems. Its purpose is to provide information and easy access for people new to the field. The book also serves as an excellent reference for researchers in the field and those working in the specifics of systems development. People in computer science, especially those in artificial intelligence, knowledge-based systems, and intelligent systems will find this to be a valuable sourcebook. Engineers, particularly control engineers, will also have a strong interest in this book. Finally, the book will be of interest to researchers working in decision support systems, operations research, decision theory, management science and applied mathematics. An Introduction to Fuzzy Logic Applications in Intelligent Systems may also be used as an introductory text and, as such, it is tutorial in nature.

Prescriptive Bayesian decision making has reached a high level of maturity and is well-supported algorithmically. However, experimental data shows that real decision makers choose such Bayes-optimal decisions surprisingly infrequently, often making decisions that are badly sub-optimal. So prevalent is such imperfect decision-making that it should be accepted as an inherent feature of real decision makers living within interacting societies.

To date such societies have been investigated from an economic and gametheoretic perspective, and even to a degree from a physics perspective. However, little research has been done from the perspective of computer science and associated disciplines like machine learning, information theory and neuroscience. This book is a major contribution to such research.

Some of the particular topics addressed include: How should we formalise rational decision making of a single imperfect decision maker? Does the answer change for a system of imperfect decision makers? Can we extend existing prescriptive theories for perfect decision makers to make them useful for imperfect ones? How can we exploit the relation of these problems to the control under varying and uncertain resources constraints as well as to the problem of the computational decision making? What can we learn from natural, engineered, and social systems to help us address these issues?"

This book provides an overview of the current research in the interdisciplinary area of personal assistants (PA) and cognitively inspired systems. It discusses the most relevant topics in this highly diversified domain, like reasoning, health, personalization, robotics, and ethical and social issues. Personal assistants (PA) are a relatively new concept directed at people with cognitive or physical disabilities, and is expanding to include complex platforms such as sensors, actuators, monitoring abilities and decision processes. Designed for a general audience, it is also of interest to undergraduates, graduates and researchers involved with intelligent systems, ambient intelligence or ambient assisted living. The content goes from an introduction of the field (aimed at undergraduates and a general readership) to specific and complex architectures (aimed at graduates and researchers).

This timely review book summarizes the state-of-the-art developments in nature-inspired optimization algorithms and their applications in engineering. Algorithms and topics include the overview and history of nature-inspired algorithms, discrete firefly algorithm, discrete cuckoo search, plant propagation algorithm, parameter-free bat algorithm, gravitational search, biogeography-based algorithm, differential evolution, particle swarm optimization and others. Applications include vehicle routing, swarming robots, discrete and combinatorial optimization, clustering of wireless sensor networks, cell formation, economic load dispatch, metamodeling, surrogated-assisted cooperative co-evolution, data fitting and reverse engineering as well as other case studies in engineering. This book will be an ideal reference for researchers, lecturers, graduates and engineers who are interested in nature-inspired computation, artificial intelligence and computational intelligence. It can also serve as a reference for relevant courses in computer science, artificial intelligence and machine learning, natural computation, engineering optimization and data mining.

(Preliminary) The book is a comprehensive collection of the most recent and significant research and applications in the field of fuzzy logic. It covers fuzzy structures, systems, rules, operations as well as important applications, e.g in decision making, environmental prediction and prevention, and communication. It is dedicated to Enric Trillas as an acknowledgement for his pioneering research in the field. The book include a foreword by Lotfi A. Zadeh.

Reviews different machine learning and deep learning techniques with a biomedical perspective Provides the relevant case studies that demonstrate applicability of different AI techniques Explain different kinds of inputs like various image modalities, biomedical signals types, etc. Covers the latest trends of AI-based biomedical domains including IoT, drug discovery, biomechanics, robotics, electronic health records, etc. Discusses the research challenges and opportunities in AI and biomedical domain

This book studies how technological solutions can be used to alleviate the current state of legal systems, with their clogged up courtrooms and inefficient conflict resolution methods. It reviews the shortcomings and disadvantages of traditional and alternative conflict resolution methods and turns to Artificial Intelligence for problem-solving techniques and solutions. The book is divided into four parts. The first part presents a general and systematic analysis of the current state of the legal systems, identifying the main problems and their causes.It then moves on to present UM Court: a framework for testing and prototyping conflict resolution services. This framework was developed with the objective of using Artificial Intelligence techniques to build a service environment for conflict resolution. The third part of the book takes a step into the future by analyzing the use of Intelligent Environments in the support of conflict management and resolution. It describes the approach taken and the experiments performed in the Intelligent Systems Lab of the University of Minho. The final part of the book contains the conclusions and shows the potential advantages of the use of Intelligent Environments as a way to implement better conflict resolution procedures (virtual or real), in which all the participants have access to more and better information and are able to take better informed decisions."

This book reviews a blend of artificial intelligence (AI) approaches that can take e-learning to the next level by adding value through customization. It investigates three methods: crowdsourcing via social networks; user profiling through machine learning techniques, and personal learning portfolios using learning analytics. Technology and education have drawn closer together over the years as they complement each other within the domain of e-learning, and different generations of online education reflect the evolution of new technologies as researcher and developers continuously seek to optimize the electronic medium to enhance the effectiveness of e-learning. Artificial intelligence (AI) for e-learning promises personalized online education through a combination of different intelligent techniques that are grounded in established learning theories while at the same time addressing a number of common e-learning issues. This book is intended for education technologists and e-learning researchers as well as for a general readership interested in the evolution of online education based on techniques like machine learning, crowdsourcing, and learner profiling that can be merged to characterize the future of personalized e-learning.

Innovations in Intelligent Systems is a rare collection of the latest developments in intelligent paradigms such as knowledge-based systems, computational intelligence and hybrid combinations as well as practical applications in engineering, science, business and commerce. The book covers central topics such as intelligent multi-agent systems, data mining, case-based reasoning, and rough sets. Essential techniques to the development of intelligent machines are investigated such as pattern recognition and classification, machine learning, natural language processing, grammar, evolutionary schemes, fuzzy-neural procedures, and intelligent vision. The book also includes useful applications ranging from medical diagnosis and technical/medical language translation, to power demand forecasting and manufacturing plants. Due to its depth and breadth of the coverage and the usefulness of the techniques and applications, this book is a valuable reference for experts and students alike.

Emerging Practices in Telehealth: Best Practices in a Rapidly Changing Field is an introduction to telehealth basics, best practices and implementation methods. The book guides the reader from start to finish through the workflow implementation of telehealth technology, including EMRs, clinical workflows, RPM, billing systems, and patient experience. It also explores how telehealth can increase healthcare access and decrease disparities across the globe. Practicing clinicians, medical fellows, allied healthcare professionals, hospital administrators, and hospital IT professionals will all benefit from this practical guidebook.

This book provides a new point of view on the field of financial engineering, through the application of multicriteria intelligent decision aiding systems. The aim of the book is to provide a review of the research in the area and to explore the adequacy of the tools and systems developed according to this innovative approach in addressing complex financial decision problems, encountered within the field of financial engineering. Audience: Researchers and professionals such as financial managers, financial engineers, investors, operations research specialists, computer scientists, management scientists and economists.

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data-processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interest from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental powers of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimen tal, and methodological studies will also appear from time to time. The present volume reflects the kind of insights that can be obtained when research workers in philosophy, artificial intelligence, and computer science explore problems of common concern. The issues here tend to fall into two broad but varied sets, namely: those concerned with content and concepts, on the one hand, and those concerned with semantics and epistemology, on the other. The collection begins with a prologue that focuses upon the relations between connectionism and alternative conceptions of nativism and ends with an epilogue that examines the significance of alternative conceptions of the Frame Problem for artificial intelligence. Because these papers are rich and diverse, they ought to appeal to a wide and heterogeneous audience. J.H.F."

COGNITIVE COMPUTING MODELS IN COMMUNICATION SYSTEMS A concise book on the latest research focusing on problems and challenges in the areas of data transmission technology, computer algorithms, AI-based devices, computer technology, and their solutions. The book provides a comprehensive overview of state-of-the-art research work on cognitive models in communication systems and computing techniques. It also bridges the gap between various communication systems and solutions by providing the current models and computing techniques, their applications, the strengths and limitations of the existing methods, and the future directions in this area. The contributors showcase their latest research work focusing on the issues, challenges, and solutions in the field of data transmission techniques, computational algorithms, artificial intelligence (AI)-based devices, and computing techniques. Readers will find in this succinctly written and unique book: Topics covering the applications of advanced cognitive devices, models, architecture, and techniques. A range of case studies and applications that will provide readers with the tools to apply cutting-edge models and algorithms. In-depth information about new cognitive computing models and conceptual frameworks and their implementation. Audience The book is designed for researchers and electronics engineers, computer science engineers, industrial engineers, and mechanical engineers (both in academia and industry) working in the fields of machine learning, cognitive computing, mobile communication, and wireless network system.

Many business decisions are made in the absence of complete information about the decision consequences. Credit lines are approved without knowing the future behavior of the customers; stocks are bought and sold without knowing their future prices; parts are manufactured without knowing all the factors affecting their final quality; etc. All these cases can be categorized as decision making under uncertainty. Decision makers (human or automated) can handle uncertainty in different ways. Deferring the decision due to the lack of sufficient information may not be an option, especially in real-time systems. Sometimes expert rules, based on experience and intuition, are used. Decision tree is a popular form of representing a set of mutually exclusive rules. An example of a two-branch tree is: if a credit applicant is a student, approve; otherwise, decline. Expert rules are usually based on some hidden assumptions, which are trying to predict the decision consequences. A hidden assumption of the last rule set is: a student will be a profitable customer. Since the direct predictions of the future may not be accurate, a decision maker can consider using some information from the past. The idea is to utilize the potential similarity between the patterns of the past (e.g., "most students used to be profitable") and the patterns of the future (e.g., "students will be profitable").

The Distinguished Dissertation Series is published on behalf of the Conference of Professors and Heads of Computing and the British Computer Society, who annually select the best British PhD dissertations in computer science for publication. The dissertations are selected on behalf of the CPHC by a panel of eight academics. Each dissertation chosen makes a noteworthy contribution to the subject and reaches a high standard of exposition, placing all results clearly in the context of computer science as a whole. In this way computer scientists with significantly different interests are able to grasp the essentials - or even find a means of entry - to an unfamiliar research topic. Constraint satisfaction is a fundamental technique for knowledge representation and inference in Artificial Intelligence. This success is founded on simplicity and generality: a constraint simply expresses a set of admissible value combinations among a number of variables. However, the classical formulation of a static constraint satisfaction problem (CSP) with inflexible constraints, all of which a solution must satisfy, is insufficient to model many real problems. Recent work has addressed these shortcomings via two separate extensions, known as dynamic CSP and flexible CSP. Representing three years of PhD work by Dr. Ian Miguel, this book demonstrates how a range of instances of these two powerful extensions can be combined in order to solve more complex problems. As an application of this work, Artificial Intelligence Planning is extended to support compromise. Preferences are attached to plan goals and to the set of actions available to achieve these goals, allowing a systematic comparison of candidate plans. Although a plan may not completely satisfy all goals, nor perform the actions it uses in the most preferred situations, it may be significantly shorter than a compromise-free plan. Dr. Miguel has implemented Flexible Graphplan, a planning system based on dynamic flexible CSP, which generates a range of plans from an input problem, trading plan length against the number and severity of compromises made.

RecentyearshaveseentheapplicationofvariousNaturalComputing algorithms for the purposes of ?nancial modelling. In this context Natural Computing - gorithms can be broadly de?ned as computer algorithms whose design draws inspirationfromphenomena in the naturalworld. Particularfeatures of?nancial markets, including their dynamic and interconnected characteristics, bear p- allels with processes in the natural world and prima facie, this makes Natural Computingmethods'interesting'for?nancialmodellingapplications. Inaddition to the problem-solving potential of natural processes which Natural computing seeks to embody in its algorithms, we can also consider Natural Computing in terms of its potential to understand the natural processes which themselves serve as inspiration. For example, ?nancial and biological systems exhibit the phenomenon of emergence, or the activities of multiple individual agents c- bining to co-evolve their own environment, and a stream of work has emerged which applies learning mechanisms drawn from Natural Computing algorithms for the purposes of agent-based modelling in ?nance and economics. This book consists of eleven chapters each of which was selected following a rigorous,peer-reviewed,selectionprocess. Thechaptersillustratetheapplication of a range of cutting-edge natural computing and agent-based methodologies in computational ?nance and economics. While describing cutting edge appli- tions, the chapters are written so that they are accessible to a wide audience. Hence, they should be of interest to academics,students and practitionersin the ?elds of computational ?nance and economics.

1. The increasing number of research papers appeared in the last years that either make use of aggregation functions or contribute to its theoretieal study asses its growing importance in the field of Fuzzy Logie and in others where uncertainty and imprecision play a relevant role. Since these papers are pub lished in many journals, few books and several proceedings of conferences, books on aggregation are partieularly welcome. To my knowledge, "Agrega tion Operators. New Trends and Applications" is the first book aiming at generality, and I take it as a honour to write this Foreword in response to the gentle demand of its editors, Radko Mesiar, Tomasa Calvo and Gaspar Mayor. My pleasure also derives from the fact that twenty years aga I was one of the first Spaniards interested in the study of aggregation functions, and this book includes work by several Spanish authors. The book contains nice and relevant original papers, authored by some of the most outstanding researchers in the field, and since it can serve, as the editors point out in the Preface, as a small handbook on aggregation, the book is very useful for those entering the subject for the first time. The book also contains apart dealing with potential areas of application, so it can be helpful in gaining insight on the future developments."