This book presents state-of-the-art research on artificial intelligence and blockchain for future cybersecurity applications. The accepted book chapters covered many themes, including artificial intelligence and blockchain challenges, models and applications, cyber threats and intrusions analysis and detection, and many other applications for smart cyber ecosystems. It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this particular area or those interested in grasping its diverse facets and exploring the latest advances on artificial intelligence and blockchain for future cybersecurity applications.

This book provides a relatively whole view of data-driven decision-making methods for energy service innovation and energy system optimization. Through personalized energy services provision and energy efficiency improvement, the book can contribute to the green transformation of energy system and the sustainable development of the society. The book gives a new way to achieve smart energy management, based on various data mining and machine learning methods, including fuzzy clustering, shape-based clustering, ensemble clustering, deep learning, and reinforcement learning. The applications of these data-driven methods in improving energy efficiency and supporting energy service innovation are presented. Moreover, this book also investigates the role of blockchain in supporting peer-to-peer (P2P) electricity trading innovation, thus supporting smart energy management. The general scope of this book mainly includes load clustering, load forecasting, price-based demand response, incentive-based demand response, and energy blockchain-based electricity trading. The intended readership of the book includes researchers and engineers in related areas, graduate and undergraduate students in university, and some other general interested audience. The important features of the book are: (1) it introduces various data-driven methods for achieving different smart energy management tasks; (2) it investigates the role of data-driven methods in supporting various energy service innovation; and (3) it explores energy blockchain in P2P electricity trading, and thus supporting smart energy management.

This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.

This comprehensive Guide to Web Development with Java introduces the readers to the three-tiered, Model-View-Controller architecture by using Spring JPA, JSPs, and Spring MVC controllers. These three technologies use Java, so that a student with a background in programming will be able to master them with ease, with the end result of being able to create web applications that use MVC, validate user input,and save data to a database. Topics and features: * Presents web development topics in an accessible, easy-to-follow style, focusing on core information first, and allowing the reader to gain basic understanding before moving forwards * Contains many helpful pedagogical tools for students and lecturers, such as questions and exercises at the end of each chapter, detailed illustrations, chapter summaries, and a glossary * Uses existing powerful technologies that are freely available on the web to speed up web development, such as Spring Boot, Spring MVC, Spring JPA, Hibernate, JSP, JSTL, and Java 1.8 * Discusses HTML, HTML forms, and Cascading Style Sheets * Starts with the simplest technology for web development (JSP) and gradually introduces the reader to more complex topics * Introduces core technologies from the outset, such as the Model-View-Controller architecture * Includes examples for accessing common web services * Provides supplementary examples and tutorials

We are living in a multilingual world and the diversity in languages which are used to interact with information access systems has generated a wide variety of challenges to be addressed by computer and information scientists. The growing amount of non-English information accessible globally and the increased worldwide exposure of enterprises also necessitates the adaptation of Information Retrieval (IR) methods to new, multilingual settings.

Peters, Braschler and Clough present a comprehensive description of the technologies involved in designing and developing systems for Multilingual Information Retrieval (MLIR). They provide readers with broad coverage of the various issues involved in creating systems to make accessible digitally stored materials regardless of the language(s) they are written in. Details on Cross-Language Information Retrieval (CLIR) are also covered that help readers to understand how to develop retrieval systems that cross language boundaries. Their work is divided into six chapters and accompanies the reader step-by-step through the various stages involved in building, using and evaluating MLIR systems. The book concludes with some examples of recent applications that utilise MLIR technologies. Some of the techniques described have recently started to appear in commercial search systems, while others have the potential to be part of future incarnations.

The book is intended for graduate students, scholars, and practitioners with a basic understanding of classical text retrieval methods. It offers guidelines and information on all aspects that need to be taken into consideration when building MLIR systems, while avoiding too many 'hands-on details' that could rapidly become obsolete. Thus it bridges the gap between the material covered by most of the classical IR textbooks and the novel requirements related to the acquisition and dissemination of information in whatever language it is stored.

This volume constitutes the refereed and revised post-conference proceedings of the 5th IFIP WG 5.15 International Conference on Information Technology in Disaster Risk Reduction, ITDRR 2020, in Sofia, Bulgaria, in December 2020.* The 18 full papers and 6 short papers presented were carefully reviewed and selected from 52 submissions. The papers focus on various aspects and challenges of coping with disaster risk reduction. The main topics include areas such as natural disasters, remote sensing, big data, cloud computing, Internet of Things, mobile computing, emergency management, disaster information processing, disaster risk assessment and management. *The conference was held virtually.

This open access book presents a new generation multi-criteria, multi-stake holder, decision aide, called an "institutional compass". Based on hard data, the compass tells us what quality-direction we are heading in as an institution, region, system or organisation. The quality is not chosen from the usual scalar qualities of: good, neutral and bad. Instead, it is a quality chosen between: harmony, discipline and excitement. None is good in and of itself. We need some of each. The compass marks a new generation in four respects. 1. The representation of the data is intuitive and simple to understand, and therefore can be used to communicate and justify policy decisions. 2. Any data can be included, i.e., none is excluded. This makes the compass tailored to particular situations, voices and contexts. 3. The data includes different time horizons and different types of value: monetary, use, social, sentimental, religious, intrinsic, existential... 4. The process of compass construction can be made inclusive at several junctions. An institutional compass can be extended to evaluate products, add normativity to a systems analysis, reflect world-views such as that of ecological economists or function as an accounting system to manage scarce resources. There are four parts to the book. The first part introduces the general ideas behind the compass. In the second part, the author presents the method for constructing the compass. This includes data collection, data analysis and a mathematical formula to aggregate the data into a single holistic reading. In the third part, the author extends the methodology: to incorporate it into systems science, adding a normative and quality-direction dimension, to use it as a non-linear accounting method and more thoroughly to reflect the philosophy of ecological economists to give a real measure of sustainability. In the fourth part, we see three case studies: one for the World Health Organisation, a second is the use of the compass to label products in a shop and the third is as a regional compass for Hauts-de-France. The book ends with philosophical conclusions. Throughout the book, we see tight arguments, refreshing ideas and a thorough treatment of objectivity in decision making.

This revised textbook presents updated material on its core content: an end-to-end IoT architecture that is comprised of devices, network, compute, storage, platform, applications along with management and security components. As with the second edition, it is organized into six main parts: an IoT reference model; fog computing and the drivers; IoT management and applications; smart services in IoT; IoT standards; and case studies. This edition's features include overhaul of the IoT Protocols (Chapter 5) to include an expanded treatment of low-power wide area networks including narrow band IoT (NB-IoT) protocol, updated IoT platforms and capabilities (Chapter 7) to include comparison of commercially available platforms (e.g. AWS IoT Platform, Google Cloud IoT Platform, Microsoft Azure IoT Platform, and PTC ThinkWorx), updated security (Chapter 8) to include approaches for securing IoT devices with examples of IoT devices used in security attacks and associated solutions including MUD and DICE, and finally new Appendix B to include six IoT project detailed for students.

The classic guide to cryptography and network security - now fully updated! "Alice and Bob are back!" Widely regarded as the most comprehensive yet comprehensible guide to network security and cryptography, the previous editions of Network Security received critical acclaim for lucid and witty explanations of the inner workings of cryptography and network security protocols. In this edition, the authors have significantly updated and revised the previous content, and added new topics that have become important. This book explains sophisticated concepts in a friendly and intuitive manner. For protocol standards, it explains the various constraints and committee decisions that led to the current designs. For cryptographic algorithms, it explains the intuition behind the designs, as well as the types of attacks the algorithms are designed to avoid. It explains implementation techniques that can cause vulnerabilities even if the cryptography itself is sound. Homework problems deepen your understanding of concepts and technologies, and an updated glossary demystifies the field's jargon. Network Security, Third Edition will appeal to a wide range of professionals, from those who design and evaluate security systems to system administrators and programmers who want a better understanding of this important field. It can also be used as a textbook at the graduate or advanced undergraduate level. Coverage includes Network security protocol and cryptography basics Design considerations and techniques for secret key and hash algorithms (AES, DES, SHA-1, SHA-2, SHA-3) First-generation public key algorithms (RSA, Diffie-Hellman, ECC) How quantum computers work, and why they threaten the first-generation public key algorithms Quantum-safe public key algorithms: how they are constructed, and optimizations to make them practical Multi-factor authentication of people Real-time communication (SSL/TLS, SSH, IPsec) New applications (electronic money, blockchains) New cryptographic techniques (homomorphic encryption, secure multiparty computation)

This volume gathers the latest advances, innovations, and applications in the field of intelligent systems such as robots, cyber-physical and embedded systems, as presented by leading international researchers and engineers at the International Conference on Intelligent Technologies in Robotics (ITR), held in Moscow, Russia on October 21-23, 2019. It covers highly diverse topics, including robotics, design and machining, control and dynamics, bio-inspired systems, Internet of Thing, Big Data, RFID technology, blockchain, trusted software, cyber-physical systems (CFS) security, development of CFS in manufacturing, protection of information in CFS, cybersecurity of CFS. The contributions, which were selected by means of a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaboration among different specialists, demonstrating that intelligent systems will drive the technological and societal change in the coming decades.

This proceedings volume highlights cutting-edge approaches for contemporary issues evolved in strategic marketing and the integration of theory and practice. It focuses on strategic research and innovative activities in marketing that can be used in everyday operations. The contributions have been divided into eight sections, grouping emerging marketing technologies together in a close examination of practices, problems and trends. The first section examines management challenges which influence societies, cultures, networks, organizations, teams, and individuals. It emphasizes ways business processes foster innovation and facilitate management transitions from dominant structures to more evolutionary, developmental paradigms. The second section discusses the benefits and guidelines to implementation of green marketing strategies. The following section pursues new perspectives of the role of location in marketing and its impact on consumer well-being. The next section explores the impacts of user generated content (UGC) on marketing theories and practice, which is followed by a section identifying how market-based assets can contribute to a sustainable competitive advantage. The sixth section covers understanding consumer perception to make marketing decisions. The final sections promote the use of business informatics and modeling in marketing and also the development of integrating information management in ways that change how people use information to engage in knowledge focused activities. The papers from the proceedings of the 6th International Conference on Strategic Innovative Marketing (IC-SIM 2017) have been written by scientists, researchers, practitioners and students that demonstrate a special orientation in strategic marketing, all of whom aspire to be ahead of the curve based on the pillars of innovation. This proceedings volume shares their recent contributions to the field and showcases their exchange of insights on strategic issues in the science of innovation marketing.

This book explores the employment of market mechanisms for data-interactive innovations. Based on the concept of innovators' marketplaces the book introduces a new concept of 'data jackets' to enable analysis of what kind of data exist, where they are located, and what kind of information they hold, even if the contents of data cannot be made publicly available.The book presents the concept of a marketplace for data in the case of data-interactive innovations. It introduces the marketplace as a platform for value-based exchange of data and - based on the idea of the innovators' marketplace - explains how data jackets can be utilized independently from the actual contents of the data. Specific chapters deepen the understanding of variables, constraints and intentions as constituent parts of data jackets, and the extension to variable quest, a process towards the design of data. A number of case studies showcases how the methods and processes presented can be employed in real-life contexts. Finally the authors present some extensions of the concept for web-based IMDJ and connections to business information system and an outlook.

This book focuses on AI and data-driven technical and management innovations in logistics, informatics and services. The respective papers analyze in detail the latest fundamental advances in the state of the art and practice of logistics, informatics, service operations and service science. The book gathers the outcomes of the "9th International Conference on Logistics, Informatics and Service Sciences," which was held at the University of Maryland, USA.

This book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks. Various deep architecture models and their components are discussed in detail, and subsequently illustrated by algorithms and selected applications. In addition, the book explains in detail the transfer learning approach for faster training of deep models; the approach is also demonstrated on large volumes of fingerprint and face image datasets. In closing, it discusses the unique set of problems and challenges associated with these models.

This book examines the recent evolution of the concept of data as an economic and managerial phenomenon. The author first describes and discusses open data and then introduces the concept of linked data, with a focus on assets for reuse. Furthermore, he addresses the main challenges of big data. Value is identified as the main incentive for the adoption of linked data; accordingly, the next two chapters study sources of data value from a macroeconomic and micro economic perspective, respectively. This contributes to the systematization of important issues at the crossroads of enterprise data and data sharing: data ownership, personal data, and data privacy. In turn, the book reveals the role of innovation as a main vehicle for creating value by unifying big, open, and linked data. It studies the ways in which value can be created, transferred, and captured in the form of business models, before the closing chapter verifies the data unification model by combining open and linked geographical data with big data from a major telecom company.

This book presents machine learning as a set of pre-requisites, co-requisites, and post-requisites, focusing on mathematical concepts and engineering applications in advanced welding and cutting processes. It describes a number of advanced welding and cutting processes and then assesses the parametrical interdependencies of two entities, namely the data analysis and data visualization techniques, which form the core of machine learning. Subsequently, it discusses supervised learning, highlighting Python libraries such as NumPy, Pandas and Scikit Learn programming. It also includes case studies that employ machine learning for manufacturing processes in the engineering domain. The book not only provides beginners with an introduction to machine learning for applied sciences, enabling them to address global competitiveness and work on real-time technical challenges, it is also a valuable resource for scholars with domain knowledge.

This book aims to present a survey of a large class of nonlinear dynamical systems exhibiting mixed-mode oscillations (MMOs). It is a sort of a guide to systems related to MMOs that features material from original research papers, including the author's own studies. The material is presented in seven chapters divided into sections. Usually, the first sections are of an introductory nature, explain phenomena, and exhibit numerical results. More advanced investigations are presented in the subsequent sections. Coverage includes * Dynamic behavior of nonlinear systems, * Fundamentals of processes exhibiting MMOs,* Mechanism and function of an structure of MMOs patterns, * Analysis of MMOs in electric circuits and systems, * MMOs in chemistry, biology, and medicine, * MMOs in mechanics and transport vehicles, * MMOs in fractional order systems. This is the first extensive description of these topics and the interpretation of analytical results and those obtained from computer simulations with the MATLAB environment. The book provides the readers with better understanding of the nature of MMOs, richness of their behaviors, and interesting applications.

Temporal databases have been an active research topic for at least fifteen years. During this time, several dozen temporal query languages have been proposed. Many within the temporal database research community perceived that the time had come to consolidate approaches to temporal data models and calculus based query languages, to achieve a consensus query language and associated data model upon which future research can be based. While there were many query language proposals, with a diversity of language and modeling constructs, common themes kept resurfacing. However, the community was quite frag mented, with each research project being based on a particular and different set of assumptions and approaches. Often these assumptions were not germane to the research per se, but were made simply because the research required a data model or query language with certain characteristics, with the partic ular one chosen rather arbitrarily. It would be better in such circumstances for research projects to choose the same language. Unfortunately, no existing language had attracted a following large enough to become the one of choice. In April, 1992 Richard Snodgrass circulated a white paper that proposed that a temporal extension to SQL be produced by the research community. Shortly thereafter, the temporal database community organized the "ARPA/NSF In ternational Workshop on an Infrastructure for Temporal Databases," which was held in Arlington, TX, in June, 1993."

This edited book provides a platform to bring together researchers, academia and industry collaborators to exchange their knowledge and work to develop better understanding about the scope of blockchain technology in business management applications of different sectors such as retail sector, supply chain and logistics, healthcare sector, manufacturing sector, judiciary, finance and government sector in terms of data quality and timeliness. The book presents original unpublished research papers on blockchain technology and business management on novel architectures, prototypes and case studies.

This book contains selected papers from the KES-IDT-2021 conference, being held as a virtual conference in June 14-16, 2021. The KES-IDT is an interdisciplinary conference with opportunities for the presentation of new research results and discussion about them under the common title "Intelligent Decision Technologies". The conference has been creating for years a platform for knowledge transfer and the generation of new ideas in the field of intelligent decision making. The range of topics discussed during the conference covered methods of classification, prediction, data analysis, big data, decision support, knowledge engineering, modeling, social networks and many more in areas such as finance, economy, management and transportation. The discussed topics covered also decision making for problems regarding the electric vehicle industry. The book contains also several sections devoted to specific topics, such as Advances in intelligent data processing and its applications Multi-criteria decision analysis methods Knowledge engineering in large-scale systems High-dimensional data analysis Spatial data analysis and sparse estimation Innovative technologies and applications in computer intelligence Intelligent diagnosis and monitoring of systems Decision making theory for economics.

The overall mission of this book is to provide a comprehensive understanding and coverage of the various theories and models used in IS research. Specifically, it aims to focus on the following key objectives: To describe the various theories and models applicable to studying IS/IT management issues. To outline and describe, for each of the various theories and models, independent and dependent constructs, reference discipline/originating area, originating author(s), seminal articles, level of analysis (i.e. firm, individual, industry) and links with other theories. To provide a critical review/meta-analysis of IS/IT management articles that have used a particular theory/model.To discuss how a theory can be used to better understand how information systems can be effectively deployed in today's digital world.

This book contributes to our understanding of a number of theories and models. The theoretical contribution of this book is that it analyzes and synthesizes the relevant literature in order to enhance knowledge of IS theories and models from various perspectives. To cater to the information needs of a diverse spectrum of readers, this book is structured into two volumes, with each volume further broken down into two sections.

The first section of Volume 1 presents detailed descriptions of a set of theories centered around the IS lifecycle, including the Success Model, Technology Acceptance Model, User Resistance Theories, and four others. The second section of Volume 1 contains strategic and economic theories, including a Resource-Based View, Theory of Slack Resources, Portfolio Theory, Discrepancy Theory Models, and eleven others.

The first section of Volume 2 concerns socio-psychological theories. These include Personal Construct Theory, Psychological Ownership, Transactive Memory, Language-Action Approach, and nine others. The second section of Volume 2 deals with methodological theories, including Critical Realism, Grounded Theory, Narrative Inquiry, Work System Method, and four others.

Together, these theories provide a rich tapestry of knowledge around the use of theory in IS research. Since most of these theories are from contributing disciplines, they provide a window into the world of external thought leadership."

This book's main goals are to bring together in a concise way all the methodologies, standards and recommendations related to Data, Queries, Links, Semantics, Validation and other issues concerning machine-readable data on the Web, to describe them in detail, to provide examples of their use, and to discuss how they contribute to - and how they have been used thus far on - the "Web of Data". As the content of the Web becomes increasingly machine readable, increasingly complex tasks can be automated, yielding more and more powerful Web applications that are capable of discovering, cross-referencing, filtering, and organizing data from numerous websites in a matter of seconds. The book is divided into nine chapters, the first of which introduces the topic by discussing the shortcomings of the current Web and illustrating the need for a Web of Data. Next, "Web of Data" provides an overview of the fundamental concepts involved, and discusses some current use-cases on the Web where such concepts are already being employed. "Resource Description Framework (RDF)" describes the graph-structured data model proposed by the Semantic Web community as a common data model for the Web. The chapter on "RDF Schema (RDFS) and Semantics" presents a lightweight ontology language used to define an initial semantics for terms used in RDF graphs. In turn, the chapter "Web Ontology Language (OWL)" elaborates on a more expressive ontology language built upon RDFS that offers much more powerful ontological features. In "SPARQL Query Language" a language for querying and updating RDF graphs is described, with examples of the features it supports, supplemented by a detailed definition of its semantics. "Shape Constraints and Expressions (SHACL/ShEx)" introduces two languages for describing the expected structure of - and expressing constraints on - RDF graphs for the purposes of validation. "Linked Data" discusses the principles and best practices proposed by the Linked Data community for publishing interlinked (RDF) data on the Web, and how these techniques have been adopted. The final chapter highlights open problems and rounds out the coverage with a more general discussion on the future of the Web of Data. The book is intended for students, researchers and advanced practitioners interested in learning more about the Web of Data, and about closely related topics such as the Semantic Web, Knowledge Graphs, Linked Data, Graph Databases, Ontologies, etc. Offering a range of accessible examples and exercises, it can be used as a textbook for students and other newcomers to the field. It can also serve as a reference handbook for researchers and developers, as it offers up-to-date details on key standards (RDF, RDFS, OWL, SPARQL, SHACL, ShEx, RDB2RDF, LDP), along with formal definitions and references to further literature. The associated website webofdatabook.org offers a wealth of complementary material, including solutions to the exercises, slides for classes, raw data for examples, and a section for comments and questions.

This book presents a collection of state-of-the-art approaches to utilizing machine learning, formal knowledge bases and rule sets, and semantic reasoning to detect attacks on communication networks, including IoT infrastructures, to automate malicious code detection, to efficiently predict cyberattacks in enterprises, to identify malicious URLs and DGA-generated domain names, and to improve the security of mHealth wearables. This book details how analyzing the likelihood of vulnerability exploitation using machine learning classifiers can offer an alternative to traditional penetration testing solutions. In addition, the book describes a range of techniques that support data aggregation and data fusion to automate data-driven analytics in cyberthreat intelligence, allowing complex and previously unknown cyberthreats to be identified and classified, and countermeasures to be incorporated in novel incident response and intrusion detection mechanisms.

Today, Information and Communication Technologies (ICT) have a pervasive presence in almost every aspect of the management of water. There is no question that the collection of big data from sensing and the insights gained by smart analytics can bring massive benefits. This book focuses on new perspectives for the monitoring, assessment and control of water systems, based on tools and concepts originating from the ICT sector. It presents a portrait of up-to-date sensing techniques for water, and introduces concepts and implications with the analysis of the acquired data. Particular attention is given to the advancements in developing novel devices and data processing approaches. The chapters guide the reader through multiple disciplinary contexts, without aiming to be exhaustive, but with the effort to present relevant topics in such a highly multi-disciplinary framework. This book will be of interest to advanced students, researchers and stakeholders at various levels.

One of the main uses of computer systems is the management of large amounts of symbolic information representing the state of some application domain, such as information about all the people I communicate with in my personal address database, or relevant parts of the outer space in the knowledge base of a NASA space mission. While database management systems offer only the basic services of information storage and retrieval, more powerful knowledge systems offer, in addition, a number of advanced services such as deductive and abductive reasoning for the purpose of finding explanations and diagnoses, or generating plans. In order to design and understand database and knowledge-based applications it is important to build upon well-established conceptual and mathematical foundations. What are the principles behind database and knowledge systems? What are their major components? Which are the important cases of knowledge systems? What are their limitations? Addressing these questions, and discussing the fundamental issues of information update, knowledge assimilation, integrity maintenance, and inference-based query answering, is the purpose of this book. Foundations of Databases and Knowledge Systems covers both basic and advanced topics. It may be used as the textbook of a course offering a broad introduction to databases and knowledge bases, or it may be used as an additional textbook in a course on databases or Artificial Intelligence. Professionals and researchers interested in learning about new developments will benefit from the encyclopedic character of the book, which provides organized access to many advanced concepts in the theory of databases and knowledge bases.