Bücher der Reihe Studies in Computational Intelligence

This book gathers extended versions of papers presented at DoSIER 2021 (the 2021 Third Doctoral Symposium on Intelligence Enabled Research, held at Cooch Behar Government Engineering College, West Bengal, India, during November 12-13, 2021). The papers address the rapidly expanding research area of computational intelligence, which, no longer limited to specific computational fields, has since made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design, to name but a few. Presenting chapters written by experts active in these areas, the book offers a valuable reference guide for researchers and industrial practitioners alike and inspires future studies.

This book includes an extended version of selected papers presented at the 11th Industry Symposium 2021 held during January 7-10, 2021. The book covers contributions ranging from theoretical and foundation research, platforms, methods, applications, and tools in all areas. It provides theory and practices in the area of data science, which add a social, geographical, and temporal dimension to data science research. It also includes application-oriented papers that prepare and use data in discovery research. This book contains chapters from academia as well as practitioners on big data technologies, artificial intelligence, machine learning, deep learning, data representation and visualization, business analytics, healthcare analytics, bioinformatics, etc. This book is helpful for the students, practitioners, researchers as well as industry professional.

If controversies were to arise, there would be no more need of disputation between two philosophers than between two accountants. For it would su?ce to take their pencils in their hands, and say to each other: ¿Let us calculate¿. Gottfried Wilhelm Leibniz (1646¿1716) Dissertio de Arte Combinatoria (Leipzig, 1666) GottfriedWilhelm Leibniz, oneofthe greatestmathematicians,discussedcalculi ofthoughts. Onlymuchlater,did it becomeevidentthat newtools arenecessary for developing such calculi, e. g. , due to the necessity of reasoning under unc- tainty about objects and (vague) concepts. Fuzzy set theory (Lot? A. Zadeh, 1965) and rough set theory (Zdzisla w Pawlak, 1982) represent two di?erent - proaches to vagueness. Fuzzy set theory addresses gradualness of knowledge, expressed by the fuzzy membership, whereas rough set theory addresses gra- larity of knowledge, expressed by the indiscernibility relation. Granular comp- ing (Zadeh,1973,1998)iscurrentlyregardedasa uni?edframeworkfor theories, methodologies and techniques for modeling calculi of thoughts, based on objects called granules. The book ¿Rough¿Granular Computing in Knowledge Discovery and Data Mining¿ written by ProfessorJaroslawStepaniuk is dedicated to methods based on a combination of the following three closely related and rapidly growing - eas: granular computing, rough sets, and knowledge discovery and data mining (KDD). In the book, the KDD foundations based on the rough set approach and granular computing are discussed together with illustrative applications. In searching for relevant patterns or in inducing (constructing) classi?ers in KDD, di?erent kinds of granulesaremodeled. In this modeling process, granulescalled approximation spaces play a special rule.

This volume comprises carefully selected and reviewed outcomes of the 12th International Workshop on Automated Negotiations (ACAN) held in Macao, 2019, in conjunction with International Joint Conference on Artificial Intelligence (IJCAI) 2019. It focuses on human aspects of automated negotiation and the recent advances in negotiation frameworks and strategies. Written by leading academic and industrial researchers, it is a valuable resource for professionals and scholars working on complex automated negotiations.

This book is focused on an emerging area, i.e. combination of IoT and semantic technologies, which should enable breaking the silos of local and/or domain-specific IoT deployments. Taking into account the way that IoT ecosystems are realized, several challenges can be identified. Among them of definite importance are (this list is, obviously, not exhaustive): (i) How to provide common representation and/or shared understanding of data that will enable analysis across (systematically growing) ecosystems? (ii) How to build ecosystems based on data flows? (iii) How to track data provenance? (iv) How to ensure/manage trust? (v) How to search for things/data within ecosystems? (vi) How to store data and assure its quality?Semantic technologies are often considered among the possible ways of addressing these (and other, related) questions. More precisely, in academic research and in industrial practice, semantic technologies materialize in the following contexts (this list is, also, not exhaustive, but indicates the breadth of scope of semantic technology usability): (i) representation of artefacts in IoT ecosystems and IoT networks, (ii) providing interoperability between heterogeneous IoT artefacts, (ii) representation of provenance information, enabling provenance tracking, trust establishment, and quality assessment, (iv) semantic search, enabling flexible access to data originating in different places across the ecosystem, (v) flexible storage of heterogeneous data. Finally, Semantic Web, Web of Things, and Linked Open Data are architectural paradigms, with which the aforementioned solutions are to be integrated, to provide production-ready deployments.

This book contributes to the progress towards intelligent transportation. It emphasizes new data management and machine learning approaches such as big data, deep learning and reinforcement learning. Deep learning and big data are very energetic and vital research topics of today's technology. Road sensors, UAVs, GPS, CCTV and incident reports are sources of massive amount of data which are crucial to make serious traffic decisions. Herewith this substantial volume and velocity of data, it is challenging to build reliable prediction models based on machine learning methods and traditional relational database. Therefore, this book includes recent research works on big data, deep convolution networks and IoT-based smart solutions to limit the vehicle's speed in a particular region, to support autonomous safe driving and to detect animals on roads for mitigating animal-vehicle accidents. This book serves broad readers including researchers, academicians, students and working professional in vehicles manufacturing, health and transportation departments and networking companies.

Current Biomedical Databases are independently administered in geographically distinct locations, lending them almost ideally to adoption of intelligent data management approaches. This book focuses on research issues, problems and opportunities in Biomedical Data Infrastructure identifying new issues and directions for future research in Biomedical Data and Information Retrieval, Semantics in Biomedicine, and Biomedical Data Modeling and Analysis. The book will be a useful guide for researchers, practitioners, and graduate-level students interested in learning state-of-the-art development in biomedical data management.

This book presents advanced software development tools for construction, deployment and governance of Service Oriented Architecture (SOA) applications. Novel technical concepts and paradigms, formulated during the research stage and during development of such tools are presented and illustrated by practical usage examples. Hence this book will be of interest not only to theoreticians but also to engineers who cope with real-life problems. Additionally, each chapter contains an overview of related work, enabling comparison of the proposed concepts with exiting solutions in various areas of the SOA development process. This makes the book interesting also for students and scientists who investigate similar issues.

The purpose of the 10th ACIS International Conference on Software Engineering Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD rd 2009), held in Daegu, Korea on May 27-29, 2009, the 3 International Workshop st on e-Activity (IWEA 2009) and the 1 International Workshop on Enterprise Architecture Challenges and Responses (WEACR 2009) is to aim at bringing together researchers and scientist, businessmen and entrepreneurs, teachers and students to discuss the numerous fields of computer science, and to share ideas and information in a meaningful way. Our conference officers selected the best 24 papers from those papers accepted for presentation at the conference in order to publish them in this volume. The papers were chosen based on review scores submitted by members of the program committee, and underwent further rounds of rigorous review. In chapter 1, Igor Crk and Chris Gniady propose a network-aware energy m- agement mechanism that provides a low-cost solution that can significantly reduce energy consumption in the entire system while maintaining responsiveness of local interactive workloads. Their dynamic mechanisms reduce the decision delay before the disk is spun-up, reduce the number of erroneous spin-ups in local wo- stations, decrease the network bandwidth, and reduce the energy consumption of individual drives. In chapter 2, Yoshihito Saito and Tokuro Matsuo describe a task allocation mechanism and its performance concerning with software developing. They run simulations and discuss the results in terms of effective strategies of task allocation.

"e;Brain-inspired information technology"e; is one of key concepts for the development of information technology in the next generation. Explosive progress of computer technology has been continuing based on a simple principle called "e;if-then rule"e;. This means that the programmer of software have to direct every action of the computer programs in response to various inputs. There inherently is a limitation of complexity because we human have a limited capacity for managing complex systems. Actually, many bugs, mistakes of programming, exist in computer software, and it is quite difficult to extinguish them. The parts of computer programs where computer viruses attack are also a kind of programming mistakes, called security hole. Of course, human body or nervous system is not perfect. No creator or director, however, exists for us. The function of our brain is equipped by learning, self-organization, natural selection, and etc, resulting in adaptive and flexible information system. Brain-inspired information technology is aiming to realize such nature-made information processing system by using present computer system or specific hardware. To do so, researchers in various research fields are getting together to inspire each other and challenge cooperatively for the same goal.

Intelligent Information Systems (IIS) can be defined as the next generation of Information Systems (IS) developed as a result of integration of AI and database (DB) technologies. IIS embody knowledge that allows them to exhibit intelligent behavior, allows them to cooperate with users and other systems in problem solving, discovery, retrieval, and manipulation of data and knowledge. For any IIS to serve its purpose, the information must be available when it is needed. This means that the computing systems used to store data and process the information, and the security controls used to protect it must be functioning correctly. This book covers some of the above topics and it is divided into four sections: Classification, Approximation and Data Security, Knowledge Management, and Application of IIS to medical and music domains.

When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case.In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees.This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, control, and finance.

Evolutionary design of intelligent systems is gaining much popularity due to its capabilities in handling several real world problems involving optimization, complexity, noisy and non-stationary environment, imprecision, uncertainty and vagueness. This edited volume 'Engineering Evolutionary Intelligent Systems' deals with the theoretical and methodological aspects, as well as various evolutionary algorithm applications to many real world problems originating from science, technology, business or commerce. This volume comprises of 15 chapters including an introductory chapter which covers the fundamental definitions and outlines some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.

Negotiation mechanisms have been studied widely in the ?eld of multi-agent systems. They possess a variety of features that enable agents be negotiate with each other even in open environments. However, mainly because of l- ited computational power, there are several assumptions that traditionally limit the degree of openness. Recent studies have tended to focus on c- pletely open and highly uncertain environments that apply agent systems to the real world. For example, in emergency rescue domains, we cannot expect to know when and where a ?re starts and when humans are likely to be - jured. Also, in Internet auctions, there can be shill bids since there are many unauthenticated participants. Nowadays, we can employ machines with large computational power to compute an optimal way for agents to negotiate, even incompletelyopenandhighlyuncertainenvironments. Forthepracticaluseof multi-agent systems in the real world, the reliability of each agent's behavior is essentially required. Concretely, agents must obtain the most appropriate solution/solutions based on rational, robust, and secure negotiation among multiple agents even if the environment is intractable. We solicit papers on all aspects of such negotiation mechanisms in multi-agent systems, including multi-issue negotiations, concurrent negotiations, strategy-proof mechanisms, rational argumentation, auctions and voting, and so on. These issues are - ing explored by researchers from di?erent communities in multi-agent s- tems. They are, for instance, being studied in agent negotiation, multi-issue negotiations, auctions, mechanism design, electronic commerce, voting, - cure protocols, matchmaking and brokering, argumentation, and co-operation mechanisms.

Computational Intelligence: A Compendium presents a well structured overview about this rapidly growing field with contributions of leading experts in Computational Intelligence. The main focus of the compendium is on applied methods tired-and-proven effective to realworld problems, which is especially useful for practitioners, researchers, students and also newcomers to the field. The 25 chapters are grouped into the following themes: I. Overview and Background II. Data Preprocessing and Systems Integration III. Artificial Intelligence IV. Logic and Reasoning V. Ontology VI. Agents VII. Fuzzy Systems VIII. Artificial Neural Networks IX. Evolutionary Approaches X. DNA and Immune-based Computing.

This book shows digital economy has become one of the most sought out solutions to sustainable development and economic growth of nations. This book discusses the implications of both artificial intelligence and computational intelligence in the digital economy providing a holistic view on AI education, economics, finance, sustainability, ethics, governance, cybersecurity, blockchain, and knowledge management. Unlike other books, this book brings together two important areas, intelligence systems and big data in the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations. The chapters hereby focus on how societies can take advantage and manage data, as well as the limitations they face due to the complexity of resources in the form of digital data and the intelligence which will support economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers,regulators, researchers, academics, students, economic development strategies, and the efforts made by the UN towards achieving their sustainability goals.