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Books > Computing & IT > Applications of computing > Artificial intelligence > General
This comprehensive work presents the status and likely development of fault diagnosis, an emerging discipline of modern control engineering. It covers fundamentals of model-based fault diagnosis in a wide context, providing a good introduction to the theoretical foundation and many basic approaches of fault detection.
New Frontiers of Cardiovascular Screening using Unobtrusive Sensors, AI, and IoT provides insights into real-world problems in cardiovascular disease screening that can be addressed via AI, IoT and wearable based sensing. Non-Communicable Diseases (NCD) are surpassing CDS and emerging as the foremost cause of death. Hence, early screening of CVDs using wearable and other similar sensors is an extremely important global problem to solve. The digital health field is constantly changing, and this book provides a review of recent technology developments, offering unique coverage of processing time series physiological sensor data. The authors have developed this book with graduate and post graduate students in mind, making sure they provide an accessible entry point into the field. This book is particularly useful for engineers and computer scientists who want to build technologies that work in real world scenarios as it provides a practitioner's view/insights /tricks of the trade. Finally, this book helps researchers working on this important problem to quickly ramp up their knowledge and research to the state-of-the-art.
With the increasing advances in hardware technology for data collection, and advances in software technology (databases) for data organization, computer scientists have increasingly participated in the latest advancements of the outlier analysis field. Computer scientists, specifically, approach this field based on their practical experiences in managing large amounts of data, and with far fewer assumptions- the data can be of any type, structured or unstructured, and may be extremely large. Outlier Analysis is a comprehensive exposition, as understood by data mining experts, statisticians and computer scientists. The book has been organized carefully, and emphasis was placed on simplifying the content, so that students and practitioners can also benefit. Chapters will typically cover one of three areas: methods and techniques commonly used in outlier analysis, such as linear methods, proximity-based methods, subspace methods, and supervised methods; data domains, such as, text, categorical, mixed-attribute, time-series, streaming, discrete sequence, spatial and network data; and key applications of these methods as applied to diverse domains such as credit card fraud detection, intrusion detection, medical diagnosis, earth science, web log analytics, and social network analysis are covered.
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.
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.
Internet of Multimedia Things (IoMT): Techniques and Applications disseminates research efforts in the security and resilience of intelligent data-centric critical systems to support advanced research in this area. Sections cover the background of IoMT Architectures and Technologies, describe the problems that arise in IoMT Computing and protocols, and illustrate the application of IoMT on Industrial applications. The book will be beneficial for engineers, developers, solution designers, architects, system engineers and specialists from professional environments interested in the IoMT to seek appropriate solutions to their specific problems.
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.
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."
Earth observation (EO) involves the collection, analysis, and presentation of data in order to monitor and assess the status and changes in natural and built environments. This technology has many applications including weather forecasting, tracking biodiversity, measuring land-use change, monitoring and responding to natural disasters, managing natural resources, monitoring emerging diseases and health risks, and predicting, adapting to and mitigating climate change. This book shows how cutting-edge technologies such as artificial intelligence, including neural networks and deep learning, can be applied for processing satellite data for Earth observation. One of the objectives of this book is to explain how to develop a set of libraries for the implementation of artificial intelligence that could overcome some limits and encompass different aspects of research, ranging from data fusion to speckle filtering. In the first part, the authors introduce remote sensing concepts and deep neural networks and convolutional neural networks. In the second part of the book, they present the main tools used for image processing, several simulations and the data processing of specific case studies as well as the testing of related datasets. The book ends with conclusions, open questions and future works and perspectives for artificial intelligence techniques applied to future satellite missions. The book will be of interest to researchers focusing on using machine learning tools to process remote sensing data - particularly satellite data - for Earth observation. The book can also be used as a guide for researchers in many other fields of research who are interested in using ML techniques to process data and get reliable outcomes so they can make informed decisions for their specific objectives.
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.
Blockchain Applications for Healthcare Informatics: Beyond 5G offers a comprehensive survey of 5G-enabled technology in healthcare applications. This book investigates the latest research in blockchain technologies and seeks to answer some of the practical and methodological questions surrounding privacy and security in healthcare. It explores the most promising aspects of 5G for healthcare industries, including how hospitals and healthcare systems can do better. Chapters investigate the detailed framework needed to maintain security and privacy in 5G healthcare services using blockchain technologies, along with case studies that look at various performance evaluation metrics, such as privacy preservation, scalability and healthcare legislation.
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." |
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