Bücher der Reihe Intelligent Systems Reference Library

This book provides a pioneering approach to modeling the human diabetic patient using a software agent. It is based on two MASc (Master of Applied Science) theses: one looking at the evolution of the patient agent in time, and another looking the interaction of the patient agent with the healthcare system.

This book demonstrates how to apply modern approaches to complex system control in practical applications involving knowledge-based systems. Moreover, specialised forms of knowledge-based systems (like e-learning, social network, and production systems) are introduced with a new formal approach to knowledge system modelling.

The research book is a continuation of the authors¿ previous works, which are focused on recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms.The book gathers selected contributions addressing a number of real-life applications including the identification of handwritten texts, watermarking techniques, simultaneous localization and mapping for mobile robots, motion control systems for mobile robots, analysis of indoor human activity, facial image quality assessment, android device controlling, processing medical images, clinical decision-making and foot progression angle detection.Given the tremendous interest among researchers in the development and applications of computer vision paradigms in the field of business, engineering, medicine, security and aviation, the book offers a timely guide for all PhD students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies.

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.

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.

This book provides a platform for exploring nature-inspired optimization techniques in the context of imaging applications. Optimization has become part and parcel of all computational vision applications, and since the amount of data used in these applications is vast, the need for optimization techniques has increased exponentially.

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.

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.

The book covers all the important aspects of research methodology, and addresses the specific requirements of engineering students, such as methods and tools, in detail.

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, drawing on recent literature, highlights several methodologies for the detection of outliers and explains how to apply them to solve several interesting real-life problems. The detection of objects that deviate from the norm in a data set is an essential task in data mining due to its significance in many contemporary applications.

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.

This book offers valuable new insights into the design of culturally-aware systems. In its first part, it is devoted to presenting selected Culturally-Aware Intelligent Systems devised in the field of Artificial Intelligence and its second part consists of two sub-parts that offer a source of inspiration for building modelizations of Culture and of its influence on the human mind and behavior, to be used in new Culturally-Aware Intelligent Systems. Those sub-parts present the results of experiments conducted in two fields that study Culture and its influence on the human mind's functions: Cultural Neuroscience and Cross-Cultural Psychology. In this era of globalization, people from different countries and cultures have the opportunity to interact directly or indirectly in a wide variety of contexts. Despite differences in their ways of thinking and reasoning, their behaviors, their values, lifestyles, customs and habits, languages, religions - in a word, their cultures - they must be able to collaborate on projects, to understand each other's views, to communicate in such a way that they don't offend each other, to anticipate the effects of their actions on others, and so on. As such, it is of primary importance to understand how culture affects people's mental activities, such as perception, interpretation, reasoning, emotion and behavior, in order to anticipate possible misunderstandings due to differences in handling the same situation, and to try and resolve them. Artificial Intelligence, and more specifically, the field of Intelligent Systems design, aims at building systems that mimic the behavior of human beings in order to complete tasks more efficiently than humans could by themselves. Consequently, in the last decade, experts and scholars in the field of Intelligent Systems have been increasingly tackling the notion of cultural awareness. A Culturally-Aware Intelligent System can be defined as a system where Culture-related or, more generally, socio-cultural information is modeled and used to design the human-machine interface, or to provide support with the task carried out by the system, be it reasoning, simulation or any other task involving cultural knowledge.

This book presents authoritative recent research on Biomedical Informatics, bringing together contributions from some of the most respected researchers in this field.Biomedical Informatics represents a growing area of interest and innovation in the management of health-related data, and is essential to the development of focused computational models. Outlining the direction of current research, the book will be of considerable interest to theoreticians and application scientists alike. Further, as all chapters are self-contained, it also provides a valuable sourcebook for graduate students.

The research book is a continuation of the authors' previous works, which are focused on recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The book gathers selected contributions addressing aerial and satellite image processing and related fields.

This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances. The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications.

The research book is a continuation of the authors' previous works, which are focused on recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms.The book gathers selected contributions addressing a number of real-life applications including the identification of handwritten texts, watermarking techniques, simultaneous localization and mapping for mobile robots, motion control systems for mobile robots, analysis of indoor human activity, facial image quality assessment, android device controlling, processing medical images, clinical decision-making and foot progression angle detection.Given the tremendous interest among researchers in the development and applications of computer vision paradigms in the field of business, engineering, medicine, security and aviation, the book offers a timely guide for all PhD students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies.

This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators¿ and learners¿ data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including:¿ Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation;¿ Using learning analytics to predict student performance;¿ Using learning analytics to create learning materials and educational courses; and¿ Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.

In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods.

This book discusses emerging technologies in the field of the Internet of Things and big data, an area that will be scaled in next two decades. Written by a team of leading experts, it is the only book focusing on the broad areas of both the Internet of things and big data. The thirteen chapters present real-time experimental methods and theoretical explanations, as well as the implementation of these technologies through various applications. Offering a blend of theory and hands-on practices, the book enables graduate, postgraduate and research students who are involved in real-time project scaling techniques to understand projects and their execution. It is also useful for senior computer students, researchers and industry workers who are involved in experimenting with the Internet of Things and big data technologies, helping them to solve the real-time problem. Moreover, the chapters covering cutting-edge technologies help multidisciplinary researchers who are bridging the gap of two different outset real-time problems.

This book offers the first comprehensive overview of artificial intelligence (AI) technologies in decision support systems for diagnosis based on medical images, presenting cutting-edge insights from thirteen leading research groups around the world.

This book addresses the usefulness of knowledge discovery through data mining. With this aim, contributors from different fields propose concrete problems and applications showing how data mining and discovering embedded knowledge from raw data can be beneficial to social organizations, domestic spheres, and ICT markets.Data mining or knowledge discovery in databases (KDD) has received increasing interest due to its focus on transforming large amounts of data into novel, valid, useful, and structured knowledge by detecting concealed patterns and relationships.The concept of knowledge is broad and speculative and has promoted epistemological debates in western philosophies. The intensified interest in knowledge management and data mining stems from the difficulty in identifying computational models able to approximate human behaviors and abilities in resolving organizational, social, and physical problems. Current ICT interfaces are not yet adequately advanced to support and simulate the abilities of physicians, teachers, assistants or housekeepers in domestic spheres. And unlike in industrial contexts where abilities are routinely applied, the domestic world is continuously changing and unpredictable. There are challenging questions in this field: Can knowledge locked in conventions, rules of conduct, common sense, ethics, emotions, laws, cultures, and experiences be mined from data? Is it acceptable for automatic systems displaying emotional behaviors to govern complex interactions based solely on the mining of large volumes of data?Discussing multidisciplinary themes, the book proposes computational models able to approximate, to a certain degree, human behaviors and abilities in resolving organizational, social, and physical problems.The innovations presented are of primary importance for:a. The academic research communityb. The ICT marketc. Ph.D. students and early stage researchersd. Schools, hospitals, rehabilitation and assisted-living centerse. Representatives from multimedia industries and standardization bodies

This book addresses a range of solutions and effective control techniques for Microbial Fuel Cells (MFCs), intended as a response to the increased energy consumption and wastewater production stemming from globalization.

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.