Bøger i Intelligent Systems Reference Library serien

This book presents advances in alternative swarm development that have proved to be effective in several complex problems. While there are numerous books addressing the most widely known swarm methods, namely ant colony algorithms and particle swarm optimization, those discussing new alternative approaches are rare.

The goal of this book is to provide, in a friendly and refreshing manner, both theoretical concepts and practical techniques for the important and exciting field of Artificial Intelligence that can be directly applied to real-world healthcare problems.

This book considers all aspects of managing the complexity of Multimedia Big Data Computing (MMBD) for IoT applications and develops a comprehensive taxonomy. Further, the book examines the layered architecture of MMBD computing and compares the life cycle of both big data and MMBD.

The general focus of this book is on multimodal communication, which captures the temporal patterns of behavior in various dialogue settings. After an overview of current theoretical models of verbal and nonverbal communication cues, it presents studies on a range of related topics: paraverbal behavior patterns in the classroom setting; a proposed optimal methodology for conversational analysis; a study of time and mood at work; an experiment on the dynamics of multimodal interaction from the observer's perspective; formal cues of uncertainty in conversation; how machines can know we understand them; and detecting topic changes using neural network techniques. A joint work bringing together psychologists, communication scientists, information scientists and linguists, the book will be of interest to those working on a wide range of applications from industry to home, and from health to security, with the main goals of revealing, embedding and implementing a rich spectrum of information on human behavior.

This book presents a compilation of state-of-the-art work on biomedical and cyber-physical systems in connection with the Internet of Things, and successfully blends theory and practice. The book covers the studies belonging to Biomedical and Cyber-physical System, so it is a unique effort by the research experts, who are divulging in the domain deeply. The book is very easy for the audience, who are doing study in the Biomedical and Cyber-physical System; it helps to read some real-time scenarios from where the reader in general gets many sparking ideas to convert it into the research problems in their studies. This book is of use to solve down the problems of graduate, postgraduate, doctoral industry executives, who are involving in the cutting-edge work of Internet of Things with Biomedical or Cyber-physical System, with the help of real-time solutions, given in the formation of chapters by subject's experts.The key uses of this book are in the area of Internet of Things in connection with Cyber-physical System as well as Biomedical domain.

This book explores some of the emerging scientific and technological areas in which the need for data analytics arises and is likely to play a significant role in the years to come. At the dawn of the 4th Industrial Revolution, data analytics is emerging as a force that drives towards dramatic changes in our daily lives, the workplace and human relationships. Synergies between physical, digital, biological and energy sciences and technologies, brought together by non-traditional data collection and analysis, drive the digital economy at all levels and offer new, previously-unavailable opportunities.The need for data analytics arises in most modern scientific disciplines, including engineering; natural-, computer- and information sciences; economics; business; commerce; environment; healthcare; and life sciences.Coming as the third volume under the general title MACHINE LEARNING PARADIGMS, the book includes an editorial note (Chapter 1) and an additional 12 chapters, and is divided into five parts: (1) Data Analytics in the Medical, Biological and Signal Sciences, (2) Data Analytics in Social Studies and Social Interactions, (3) Data Analytics in Traffic, Computer and Power Networks, (4) Data Analytics for Digital Forensics, and (5) Theoretical Advances and Tools for Data Analytics.This research book is intended for both experts/researchers in the field of data analytics, and readers working in the fields of artificial and computational intelligence as well as computer science in general who wish to learn more about the field of data analytics and its applications. An extensive list of bibliographic references at the end of each chapter guides readers to probe further into the application areas of interest to them.

Rather than focusing on a single aspect of software engineering, this book provides a systematic overview of recent techniques, including requirement gathering in the form of story points in agile software, and bio-inspired techniques for estimating the effort, cost, and time required for software development.

Fuzzy Cognitive Maps for Applied Sciences and Engineering

This bookgives a start-to-finish overview of the whole Fish4Knowledge project, in 18short chapters, each describing one aspect of the project.

This volume presents a collection of research studies on sophisticated and functional computational instruments able to recognize, process, and store relevant situated interactional signals, as well as, interact with people, displaying reactions (under conditions of limited time) that show abilities of appropriately sensing and understanding environmental changes, producing suitable, autonomous, and adaptable responses to various social situations. These social robotic autonomous systems will improve the quality of life of their end-users while assisting them on several needs, ranging from educational settings, health care assistance, communicative disorders, and any disorder impairing either their physical, cognitive, or social functional activities. The multidisciplinary themes presented in the volume will be interesting for experts and students coming from different research fields and with different knowledge and backgrounds. The research reported is particularly relevant for academic centers, and Research & Development Institutions.

This volume is a collection of researchstudies on the modeling of emotions in complex autonomous systems. Severalexperts in the field are reporting their efforts and reviewing the literaturein order to shed lights on how the processes of coding and decoding emotionalstates took place in humans, which are the physiological, physical, andpsychological variables involved, invent new mathematical models and algorithmsto describe them, and motivate these investigations in the light of observablesocietal changes and needs, such as the aging population and the cost of healthcare services. The consequences are the implementation of emotionally andsocially believable machines, acting as helpers into domestic spheres, whereemotions drive behaviors and actions.The contents of the book are highlymultidisciplinary since the modeling of emotions in robotic socially believablesystems requires a holistic perspective on topics coming from differentresearch domains such as computer science, engineering, sociology, psychology,linguistic, and information communication. The book is of interest both to experts and students since last researchworks on a so complex multidisciplinary topic are described in a neat anddidactical scientific language.

This book initially reviews the major feature representation and extraction methods and effective learning and recognition approaches, which have broad applications in the context of intelligent image search and video retrieval.

This book presents emerging trends in the evolution of service-oriented and enterprise architectures. Services Oriented Architectures (SOA) and Enterprise Architectures (EA) have emerged as a useful framework for developing interoperable, large-scale systems, typically implementing various standards, like Web Services, REST, and Microservices.

This book offers a comprehensive reference guide to intelligence systems in environmental management. It provides readers with all the necessary tools for solving complex environmental problems, where classical techniques cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including ant colony, genetic algorithms, evolutionary algorithms, fuzzy multi-criteria decision making tools, particle swarm optimization, agent-based modelling, artificial neural networks, simulated annealing, Tabu search, fuzzy multi-objective optimization, fuzzy rules, support vector machines, fuzzy cognitive maps, cumulative belief degrees, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on complex environmental problems. Moreover, by extending all the main aspects of classical environmental solution techniques to its intelligent counterpart, the book presents a dynamic snapshot on the field that is expected to stimulate new directions and stimulate new ideas and developments.

This volume introduces new approaches in intelligent control area fromboth the viewpoints of theory and application. Some of the chapters introduce specific case studies of various intelligentcontrol systems and others focus on intelligent theory based control techniqueswith applications.

This book presents an Introduction and 11 independent chapters, whichare devoted to various new approaches of intelligent image processing andanalysis. The book also presents new methods, algorithms and applied systemsfor intelligent image processing, on the following basic topics:Methods for Hierarchical Image Decomposition;Intelligent Digital Signal Processing and Feature Extraction;Data Clustering and Visualization via Echo State Networks;Clustering of Natural Images in Automatic Image Annotation Systems;Control System for Remote Sensing Image Processing;Tissue Segmentation of MR Brain Images Sequence;Kidney Cysts Segmentation in CT Images;Audio Visual Attention Models in Mobile Robots Navigation;Local Adaptive Image Processing;Learning Techniques for Intelligent Access Control;Resolution Improvement in Acoustic Maps.Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the analysis of the modeling of the developed algorithms in different application areas.

This book presents a collection of contributions from related logics to applied paraconsistency. The book includes important contributions on foundations and applications of paraconsistent logics in connection with engineering, mathematical logic, philosophical logic, computer science, physics, economics, and biology.

This book presents recent applications and approaches as well as challenges in digital forensic science.

Complex problems usually cannot be solved by individual methods or techniques and require the synergism of more than one of them to be solved.

This book presents current innovative, alternative and creative approaches that challenge traditional mechanisms in and across disciplines and industries targeting societal impact.

This book provides a state-of-the-art perspective on intelligent process-aware information systems and presents chapters on specific facets and approaches applicable to such systems. Further, it highlights novel advances and developments in various aspects of intelligent process-aware information systems and business process management systems.Intelligence capabilities are increasingly being integrated into or created in many of today's software products and services. Process-aware information systems provide critical computing infrastructure to support the various processes involved in the creation and delivery of business products and services. Yet the integration of intelligence capabilities into process-aware information systems is a non-trivial yet necessary evolution of these complex systems. The book's individual chapters address adaptive process management, case management processes, autonomically-capable processes, process-oriented information logistics, process recommendations, reasoning over process models, process portability, and business process intelligence. The primary target groups are researchers and PhD/Master students in the field of information systems.

This book presents a collection of state-of-the-art AI approaches to cybersecurity and cyberthreat intelligence, offering strategic defense mechanisms for malware, addressing cybercrime, and assessing vulnerabilities to yield proactive rather than reactive countermeasures.

Last, Chapter 7 presents simulation methodologies for modeling maritime traffic. The intended readership of the book spans both an academic audience and professionals in the areas of Operational Research, Transportation Science, and Maritime Science interested in applying IT methodologies in their areas of expertise.

This book presents cutting-edge research on various ways to bridge the semantic gap in image and video analysis. The respective chapters address different stages of image processing, revealing that the first step is a future extraction, the second is a segmentation process, the third is object recognition, and the fourth and last involve the semantic interpretation of the image. The semantic gap is a challenging area of research, and describes the difference between low-level features extracted from the image and the high-level semantic meanings that people can derive from the image. The result greatly depends on lower level vision techniques, such as feature selection, segmentation, object recognition, and so on. The use of deep models has freed humans from manually selecting and extracting the set of features. Deep learning does this automatically, developing more abstract features at the successive levels. The book offers a valuable resource for researchers, practitioners, students and professors in Computer Engineering, Computer Science and related fields whose work involves images, video analysis, image interpretation and so on.

Dynamic programming is an efficient technique for solving optimization problems. and multi-stage optimization for such classic combinatorial optimization problems as matrix chain multiplication, binary search trees, global sequence alignment, and shortest paths.

This book offers a comprehensive overview of ensemble learning in the field of feature selection (FS), which consists of combining the output of multiple methods to obtain better results than any single method.

Special emphasis is placed on three specific kinds of complex networks of high technological and scientific importance: software networks extracted from the source code of computer programs, ontology networks describing semantic web ontologies, and co-authorship networks reflecting collaboration in science.

This book presents the latest developments concerning techniques, tools, and methodologies in supply chain ecosystems. The book is chiefly intended to meet the needs of two sectors: firstly, the academic sector, so as to familiarize students, professors, and researchers with the tools that are now being used to optimize supply chains;

This book applies novel theories to improve algorithms in complex data analysis in various fields, including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. It is intended for Ph.D.

The Formal Representation of Cyberthreats for Automated Reasoning.- A Logic Programming Approach to Predict Enterprise-Targeted Cyberattacks.- Discovering Malicious URLs Using Machine Learning Techniques.- Machine Learning and Big Data Processing for Cybersecurity Data Analysis.- Systematic Analysis of Security Implementation for Internet of Health Things in Mobile Health Networks.- Seven Pitfalls of Using Data Science in Cybersecurity.