The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.

This book presents 3D3C platforms - three-dimensional systems for community, creation and commerce. It discusses tools including bots in social networks, team creativity, privacy, and virtual currencies & micropayments as well as their applications in areas like healthcare, energy, collaboration, and art. More than 20 authors from 10 countries share their experiences, research fi ndings and perspectives, off ering a comprehensive resource on the emerging fi eld of 3D3C worlds. The book is designed for both the novice and the expert as a way to unleash the emerging opportunities in 3D3C worlds. This Handbook maps with breadth and insight the exciting frontier of building virtual worlds with digital technologies. David Perkins, Research Professor, Harvard Graduate School of Education This book is from one of the most adventurous and energetic persons I have ever met. Yesha takes us into new undiscovered spaces and provides insight into phenomena of social interaction and immersive experiences that transform our lives. Cees de Bont, Dean of School of Design & Chair Professor of Design, School of Design of the Hong Kong Polytechnic University When you read 3D3C Platforms you realize what a domain like ours -- 3D printing -- can and should do for the world. Clearly we are just starting. Inspiring.David Reis, CEO, Stratasys Ltd This book provides a stunning overview regarding how virtual worlds are reshaping possibilities for identity and community. Th e range of topics addressed by the authors- from privacy and taxation to fashion and health care-provide a powerful roadmap for addressing the emerging potential of these online environments. Tom Boellstorff , Professor, Department of Anthropology, University of California, Irvine Handbook on 3D3C Platforms amassed a unique collection of multidisciplinary academic thinking. A primer on innovations that will touch every aspect of the human community in the 21st century. Eli Talmor, Professor, London Business School

Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use. This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations. Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies.

This comprehensive book focuses on better big-data security for healthcare organizations. Following an extensive introduction to the Internet of Things (IoT) in healthcare including challenging topics and scenarios, it offers an in-depth analysis of medical body area networks with the 5th generation of IoT communication technology along with its nanotechnology. It also describes a novel strategic framework and computationally intelligent model to measure possible security vulnerabilities in the context of e-health. Moreover, the book addresses healthcare systems that handle large volumes of data driven by patients' records and health/personal information, including big-data-based knowledge management systems to support clinical decisions. Several of the issues faced in storing/processing big data are presented along with the available tools, technologies and algorithms to deal with those problems as well as a case study in healthcare analytics. Addressing trust, privacy, and security issues as well as the IoT and big-data challenges, the book highlights the advances in the field to guide engineers developing different IoT devices and evaluating the performance of different IoT techniques. Additionally, it explores the impact of such technologies on public, private, community, and hybrid scenarios in healthcare. This book offers professionals, scientists and engineers the latest technologies, techniques, and strategies for IoT and big data.

A modern information retrieval system must have the capability to find, organize and present very different manifestations of information - such as text, pictures, videos or database records - any of which may be of relevance to the user. However, the concept of relevance, while seemingly intuitive, is actually hard to define, and it's even harder to model in a formal way.

Lavrenko does not attempt to bring forth a new definition of relevance, nor provide arguments as to why any particular definition might be theoretically superior or more complete. Instead, he takes a widely accepted, albeit somewhat conservative definition, makes several assumptions, and from them develops a new probabilistic model that explicitly captures that notion of relevance. With this book, he makes two major contributions to the field of information retrieval: first, a new way to look at topical relevance, complementing the two dominant models, i.e., the classical probabilistic model and the language modeling approach, and which explicitly combines documents, queries, and relevance in a single formalism; second, a new method for modeling exchangeable sequences of discrete random variables which does not make any structural assumptions about the data and which can also handle rare events.

Thus his book is of major interest to researchers and graduate students in information retrieval who specialize in relevance modeling, ranking algorithms, and language modeling.

This book presents the outcomes of the Third National Conference on Communication, Cloud and Big Data (CCB) held on November 2-3, 2018, at Sikkim Manipal Institute of Technology, Majitar, Sikkim. Featuring a number of papers from the conference, it explores various aspects of communication, computation, cloud, and big data, including routing in cognitive radio wireless sensor networks, big data security issues, routing in ad hoc networks, routing protocol for Internet of things (IoT), and algorithm for imaging quality enhancement.

In the last ten years, a true explosion of investigations into fuzzy modeling and its applications in control, diagnostics, decision making, optimization, pattern recognition, robotics, etc. has been observed. The attraction of fuzzy modeling results from its intelligibility and the high effectiveness of the models obtained. Owing to this the modeling can be applied for the solution of problems which could not be solved till now with any known conventional methods. The book provides the reader with an advanced introduction to the problems of fuzzy modeling and to one of its most important applications: fuzzy control. It is based on the latest and most significant knowledge of the subject and can be used not only by control specialists but also by specialists working in any field requiring plant modeling, process modeling, and systems modeling, e.g. economics, business, medicine, agriculture,and meteorology.

This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.

The present economic and social environment has given rise to new situations within which companies must operate. As a first example, the globalization of the economy and the need for performance has led companies to outsource and then to operate inside networks of enterprises such as supply chains or virtual enterprises. A second instance is related to environmental issues. The statement about the impact of ind- trial activities on the environment has led companies to revise processes, to save - ergy, to optimize transportation.... A last example relates to knowledge. Knowledge is considered today to be one of the main assets of a company. How to capitalize, to manage, to reuse it for the benefit of the company is an important current issue. The three examples above have no direct links. However, each of them constitutes a challenge that companies have to face today. This book brings together the opinions of several leading researchers from all around the world. Together they try to develop new approaches and find answers to those challenges. Through the individual ch- ters of this book, the authors present their understanding of the different challenges, the concepts on which they are working, the approaches they are developing and the tools they propose. The book is composed of six parts; each one focuses on a specific theme and is subdivided into subtopics.

The Engineering of Complex Real-Time Computer Control Systems brings together in one place important contributions and up-to-date research results in this important area. The Engineering of Complex Real-Time Computer Control Systems serves as an excellent reference, providing insight into some of the most important research issues in the field.

In the course of fuzzy technological development, fuzzy graph theory was identified quite early on for its importance in making things work. Two very important and useful concepts are those of granularity and of nonlinear ap proximations. The concept of granularity has evolved as a cornerstone of Lotfi A.Zadeh's theory of perception, while the concept of nonlinear approx imation is the driving force behind the success of the consumer electronics products manufacturing. It is fair to say fuzzy graph theory paved the way for engineers to build many rule-based expert systems. In the open literature, there are many papers written on the subject of fuzzy graph theory. However, there are relatively books available on the very same topic. Professors' Mordeson and Nair have made a real contribution in putting together a very com prehensive book on fuzzy graphs and fuzzy hypergraphs. In particular, the discussion on hypergraphs certainly is an innovative idea. For an experienced engineer who has spent a great deal of time in the lab oratory, it is usually a good idea to revisit the theory. Professors Mordeson and Nair have created such a volume which enables engineers and design ers to benefit from referencing in one place. In addition, this volume is a testament to the numerous contributions Professor John N. Mordeson and his associates have made to the mathematical studies in so many different topics of fuzzy mathematics."

A comprehensive, systematic approach to multimedia database management systems. It presents methods for managing the increasing demands of multimedia databases and their inherent design and architecture issues, and covers how to create an effective multimedia database by integrating the various information indexing and retrieval methods available. It also addresses how to measure multimedia database performance that is based on similarity to queries and routinely affected by human judgement. The book concludes with a discussion of networking and operating system support for multimedia databases and a look at research and development in this dynamic field.

This informative text/reference presents a detailed review of the state of the art in industrial sensor and control networks. The book examines a broad range of applications, along with their design objectives and technical challenges. The coverage includes fieldbus technologies, wireless communication technologies, network architectures, and resource management and optimization for industrial networks. Discussions are also provided on industrial communication standards for both wired and wireless technologies, as well as for the Industrial Internet of Things (IIoT). Topics and features: describes the FlexRay, CAN, and Modbus fieldbus protocols for industrial control networks, as well as the MIL-STD-1553 standard; proposes a dual fieldbus approach, incorporating both CAN and ModBus fieldbus technologies, for a ship engine distributed control system; reviews a range of industrial wireless sensor network (IWSN) applications, from environmental sensing and condition monitoring, to process automation; examines the wireless networking performance, design requirements, and technical limitations of IWSN applications; presents a survey of IWSN commercial solutions and service providers, and summarizes the emerging trends in this area; discusses the latest technologies and open challenges in realizing the vision of the IIoT, highlighting various applications of the IIoT in industrial domains; introduces a logistics paradigm for adopting IIoT technology on the Physical Internet. This unique work will be of great value to all researchers involved in industrial sensor and control networks, wireless networking, and the Internet of Things.

It is over 20 years since the functional data model and functional programming languages were first introduced to the computing community. Although developed by separate research communities, recent work, presented in this book, suggests there is powerful synergy in their integration. As database technology emerges as central to yet more complex and demanding applications in areas such as bioinformatics, national security, criminal investigations and advanced engineering, more sophisticated approaches like those presented here, are needed. A tutorial introduction by the editors prepares the reader for the chapters that follow, written by leading researchers, including some of the early pioneers. They provide a comprehensive treatment showing how the functional approach provides for modeling, analyzis and optimization in databases, and also data integration and interoperation in heterogeneous environments. Several chapters deal with mathematical results on the transformation of expressions, fundamental to the functional approach. The book also aims to show how the approach relates to the Internet and current work on semistructured data, XML and RDF. The book presents a comprehensive view of the functional approach to data management, bringing together important material hitherto widely scattered, some new research, and a comprehensive set of references. It will serve as a valuable resource for researchers, faculty and graduate students, as well as those in industry responsible for new systems development.

As the use of digital technology has grown, so necessarily has the body of research into its effects at the personal, group and organizational levels, but there is no one book that looks at how digital technology has specifically influenced creativity. Digital Creativity: Individuals, Groups, and Organizations discusses all spectrums of influence that digital technologies have on creativity from the individual, team, and organization level. This book offers a new kind of creativity model encompassing all three levels of creativity. It combines each level into a unified creativity framework in which organizations regardless of their industry types could benefit in reengineering their business processes as well as strategies. For this purpose, the book considers various factors that would affect creativity- individuals' digital efficacy, heterogeneity among members (i.e., age, gender, races, tenure, education, and culture, etc), CMC (Computer-Mediated Communication), task complexity, exploitation, exploration, culture, organizational learning capability, and knowledge networks among members. This book introduces a theorized and systematic glimpse into the exciting realm of digital creativity. It is organized with contents starting from individuals to teams and ultimately to organizations, each with various techniques and cases. Each chapter shows how individuals, teams, and organizations can become more creative through use of digital technologies.

Advanced Topics in Database Research is a series of books on the fields of database, software engineering, and systems analysis and design. They feature the latest research ideas and topics on how to enhance current database systems, improve information storage, refine existing database models, and develop advanced applications. ""Advanced Topics in Database Research, Volume 5"" is a part of this series. ""Advanced Topics in Database Research, Volume 5"" presents the latest research ideas and topics on database systems and applications, and provides insights into important developments in the field of database and database management. This book describes the capabilities and features of new technologies and methodologies, and presents state-of-the-art research ideas, with an emphasis on theoretical issues regarding databases and database management.

Information intermediation is the foundation stone of some of the most successful Internet companies, and is perhaps second only to the Internet Infrastructure companies. On the heels of information integration and interoperability, this book on information brokering discusses the next step in information interoperability and integration. The emerging Internet economy based on burgeoning B2B and B2C trading will soon demand semantics-based information intermediation for its feasibility and success. B2B ventures are involved in the rationalization' of new vertical markets and construction of domain specific product catalogs. This book provides approaches for re-use of existing vocabularies and domain ontologies as a basis for this rationalization and provides a framework based on inter-ontology interoperation. Infrastructural trade-offs that identify optimizations in performance and scalability of web sites will soon give way to information based trade-offs as alternate rationalization schemes come into play and the necessity of interoperating across these schemes is realized. Information Brokering Across Heterogeneous Digital Data's intended readers are researchers, software architects and CTOs, advanced product developers dealing with information intermediation issues in the context of e-commerce (B2B and B2C), information technology professionals in various vertical markets (e.g., geo-spatial information, medicine, auto), and all librarians interested in information brokering.

Information fusion is becoming a major requirement in data mining and knowledge discovery in databases. This book presents some recent fusion techniques that are currently in use in data mining, as well as data mining applications that use information fusion. Special focus of the book is on information fusion in preprocessing, model building and information extraction with various applications.

What will business software look like in the future? And how will it be developed?

This book covers the proceedings of the first international conference on Future Business Software - a new think tank discussing the trends in enterprise software with speakers from Europe's most successful software companies and the leading research institutions. The articles focus on two of the most prominent trends in the field: emergent software and agile development processes.

"Emergent Software" is a new paradigm of software development that addresses the highly complex requirements of tomorrow's business software and aims at dynamically and flexibly combining a business software solution's different components in order to fulfill customers' needs with a minimum of effort. Agile development processes are the response of software technology to the implementation of diverse and rapidly changing software requirements. A major focus is on the minimization of project risks, e.g. through short, iterative development cycles, test-driven development and an intensive culture of communication."

Parallel and Distributed Information Systems brings together in one place important contributions and up-to-date research results in this fast moving area. Parallel and Distributed Information Systems serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

This book proposes representations of multicast rate regions in wireless networks based on the mathematical concept of submodular functions, e.g., the submodular cut model and the polymatroid broadcast model. These models subsume and generalize the graph and hypergraph models. The submodular structure facilitates a dual decomposition approach to network utility maximization problems, which exploits the greedy algorithm for linear programming on submodular polyhedra. This approach yields computationally efficient characterizations of inner and outer bounds on the multicast capacity regions for various classes of wireless networks.

This book presents important applications of soft computing and fuzziness to the growing field of web planning. A new method of using fuzzy numbers to model uncertain probabilities and how these can be used to model a fuzzy queuing system is demonstrated, as well as a method of modeling fuzzy queuing systems employing fuzzy arrival rates and fuzzy service rates. All the computations needed to get to the fuzzy numbers for system performance are described starting for the one server case to more than three servers. A variety of optimization models are discussed with applications to the average response times, server utilization, server and queue costs, as well as to phenomena identified with web sites such as "burstiness" and "long tailed distributions".

This book comprises the refereed papers together with the invited keynote papers, presented at the Second International Conference on Enterprise Information Systems. The conference was organised by the School of Computing at Staffordshire University, UK, and the Escola Superior de Tecnologia of Setubal, Portugal, in cooperation with the British Computer Society and the International Federation for Information Processing, Working Group 8.1. The purpose of this 2nd International Conference was to bring together researchers, engineers and practitioners interested in the advances in and business applications of information systems. The papers demonstrate the vitality and vibrancy of the field of Enterprise Information Systems. The research papers included here were selected from among 143 submissions from 32 countries in the following four areas: Enterprise Database Applications, Artificial Intelligence Applications and Decision Support Systems, Systems Analysis and Specification, and Internet and Electronic Commerce. Every paper had at least two reVIewers drawn from 10 countries. The papers included in this book were recommended by the reviewers. On behalf of the conference organising committee we would like to thank all the members of the Programme Committee for their work in reviewing and selecting the papers that appear in this volume. We would also like to thank all the authors who have submitted their papers to this conference, and would like to apologise to the authors that we were unable to include and wish them success next year.

In two parts, the book focusses on materials science developments in the area of 1) Materials Data and Informatics: - Materials data quality and infrastructure - Materials databases - Materials data mining, image analysis, data driven materials discovery, data visualization. 2) Materials for Tomorrow's Energy Infrastructure: - Pipeline, transport and storage materials for future fuels: biofuels, hydrogen, natural gas, ethanol, etc. -Materials for renewable energy technologies This book presents selected contributions of exceptional young postdoctoral scientists to the 4th WMRIF Workshop for Young Scientists, hosted by the National Institute of Standards and Technology, at the NIST site in Boulder, Colorado, USA, September 8 to September 10, 2014.

This book provides a comprehensive set of optimization and prediction techniques for an enterprise information system. Readers with a background in operations research, system engineering, statistics, or data analytics can use this book as a reference to derive insight from data and use this knowledge as guidance for production management. The authors identify the key challenges in enterprise information management and present results that have emerged from leading-edge research in this domain. Coverage includes topics ranging from task scheduling and resource allocation, to workflow optimization, process time and status prediction, order admission policies optimization, and enterprise service-level performance analysis and prediction. With its emphasis on the above topics, this book provides an in-depth look at enterprise information management solutions that are needed for greater automation and reconfigurability-based fault tolerance, as well as to obtain data-driven recommendations for effective decision-making.