This book presents best selected papers presented at the 4th International Conference on Smart Computing and Informatics (SCI 2020), held at the Department of Computer Science and Engineering, Vasavi College of Engineering (Autonomous), Hyderabad, Telangana, India. It presents advanced and multi-disciplinary research towards the design of smart computing and informatics. The theme is on a broader front which focuses on various innovation paradigms in system knowledge, intelligence and sustainability that may be applied to provide realistic solutions to varied problems in society, environment and industries. The scope is also extended towards the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and health care.

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.

This book features a selection of extended papers presented at the 8th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2021, held in Yokohama, Japan, in January 2021, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2020.*The 14 revised and extended papers presented together with an invited talk were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management and discuss methodological, technical and organizational aspects of artificial intelligence used for knowledge management. *The workshop was held virtually.

This book provides a broad introduction to search engines by integrating five different perspectives on Web search and search engines that are usually dealt with separately: the technical perspective, the user perspective, the internet-based research perspective, the economic perspective, and the societal perspective. After a general introduction to the topic, two foundational chapters present how search tools can cover the Web's content and how search engines achieve this by crawling and processing the found documents. The next chapter on user behavior covers how people phrase their search queries and interact with search engines. This knowledge builds the foundation for describing how results are ranked and presented. The following three chapters then deal with the economic side of search engines, i.e., Google and the search engine market, search engine optimization (SEO), and the intermingling of organic and sponsored search results. Next, the chapter on search skills presents techniques for improving searches through advanced search interfaces and commands. Following that, the Deep Web and how its content can be accessed is explained. The two subsequent chapters cover ways to improve the quality of search results, while the next chapter describes how to access the Deep Web. Last but not least, the following chapter deals with the societal role of search engines before the final chapter concludes the book with an outlook on the future of Web search. With this book, students and professionals in disciplines like computer science, online marketing, or library and information science will learn how search engines work, what their main shortcomings are at present, and what prospects there are for their further development. The different views presented will help them to understand not only the basic technologies but also the implications the current implementations have concerning economic exploitation and societal impact.

Exploiting the rich information found in electronic health records (EHRs) can facilitate better medical research and improve the quality of medical practice. Until now, a trivial amount of research has been published on the challenges of leveraging this information. Addressing these challenges, Information Discovery on Electronic Health Records explores the technology to unleash the data stored in EHRs.

Assembling a truly interdisciplinary team of experts, the book tackles medical privacy concerns, the lack of standardization for the representation of EHRs, missing or incorrect values, and the availability of multiple rich health ontologies. It looks at how to search the EHR collection given a user query and return relevant fragments from the EHRs. It also explains how to mine the EHR collection to extract interesting patterns, group entities to various classes, or decide whether an EHR satisfies a given property. Most of the book focuses on textual or numeric data of EHRs, where more searching and mining progress has occurred. A chapter on the processing of medical images is also included.

Maintaining a uniform style across chapters and minimizing technical jargon, this book presents the various ways to extract useful knowledge from EHRs. It skillfully discusses how EHR data can be effectively searched and mined.

This book provides practical information about web archives, offers inspiring examples for web archivists, raises new challenges, and shares recent research results about access methods to explore information from the past preserved by web archives. The book is structured in six parts. Part 1 advocates for the importance of web archives to preserve our collective memory in the digital era, demonstrates the problem of web ephemera and shows how web archiving activities have been trying to address this challenge. Part 2 then focuses on different strategies for selecting web content to be preserved and on the media types that different web archives host. It provides an overview of efforts to address the preservation of web content as well as smaller-scale but high-quality collections of social media or audiovisual content. Next, Part 3 presents examples of initiatives to improve access to archived web information and provides an overview of access mechanisms for web archives designed to be used by humans or automatically accessed by machines. Part 4 presents research use cases for web archives. It also discusses how to engage more researchers in exploiting web archives and provides inspiring research studies performed using the exploration of web archives. Subsequently, Part 5 demonstrates that web archives should become crucial infrastructures for modern connected societies. It makes the case for developing web archives as research infrastructures and presents several inspiring examples of added-value services built on web archives. Lastly, Part 6 reflects on the evolution of the web and the sustainability of web archiving activities. It debates the requirements and challenges for web archives if they are to assume the responsibility of being societal infrastructures that enable the preservation of memory. This book targets academics and advanced professionals in a broad range of research areas such as digital humanities, social sciences, history, media studies and information or computer science. It also aims to fill the need for a scholarly overview to support lecturers who would like to introduce web archiving into their courses by offering an initial reference for students.

This book constitutes the refereed proceedings of six International Workshops held as parallel events of the 17th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2021, virtually and in Hersonissos, Crete, Greece, in June 2021: the 6th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2021; Artificial Intelligence in Biomedical Engineering and Informatics Workshop, AI-BIO 2021; Workshop on Defense Applications of AI, DAAI 2021; Distributed AI for Resource-Constrained Platforms Workshop, DARE 2021; Energy Efficiency and Artificial Intelligence Workshop, EEAI 2021; and the 10th Mining Humanistic Data Workshop, MHDW 2021. The 24 full papers and 16 short papers presented at these workshops were carefully reviewed and selected from 72 submissions. The papers presented at 5G-PINE focus on the latest AI applications in the telecommunication industry and AI in modern 5G-oriented telecommunications infrastructures. The papers chosen for AI-BIO 2021 present research on the subject of AI, in its broadest sense, in biomedical engineering and health informatics. The DAAI 2021 papers aim at presenting recent evolutions in artificial intelligence applicable to defense and security applications. The papers selected for DARE 2021 address a variety of pertinent and challenging topics within the scope of distributed AI for resource-constrained platforms. The papers presented at EEAI 2021 aim to bring together interdisciplinary approaches that focus on the application of AI-driven solutions for increasing and improving energy efficiency of residential and tertiary buildings and of occupant behavior. The MHDW papers focus on topics such as recommendation systems, sentiment analysis, pattern recognition, data mining, and time series.

Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available. This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms. Applications of data-driven optimization ranging from aerodynamic design, optimization of industrial processes, to deep neural architecture search are included.

Exploring fundamental research questions, Conceptual Structures in Practice takes you through the basic yet nontrivial task of establishing conceptual relations as the foundation for research in knowledge representation and knowledge mining. It includes contributions from leading researchers in both the conceptual graph and formal concept analysis (FCA) communities. This accessible, self-contained book begins by providing the formal background in FCA and conceptual graphs. It then describes various software tools for analysis and computation, including the ToscanaJ suite. Written by the original visionaries of the field, the next section discusses the history and future directions of conceptual structures. The final chapters explore prominent application areas in computer science, including text analysis, web semantics, and intelligent systems. An unprecedented, state-of-the-art overview from innovators in the field, this volume discusses how FCA and conceptual graphs can be used in many computer science areas. It serves as a benchmark of research on conceptual structures, inspiring further exploration in this discipline.

Maintaining compatibility among all affected network and application interfaces of modern enterprise systems can quickly become costly and overwhelming. This handbook presents the knowledge and practical experience of a global group of experts from varying disciplines to help you plan and implement enterprise integration projects that respond to business needs quickly and are seamless to business users. The Handbook of Enterprise Integration brings together the latest research and application results to provide infrastructure engineers, software engineers, software developers, system designers, and project managers with a clear and comprehensive understanding of systems integration technologies, architectures, applications, and project management techniques involved in enterprise system integration. The text includes coverage of mobile communications, standards for integrated manufacturing and e-commerce, RFID, Web-based systems, and complete service-oriented enterprise modeling and analysis. Practitioners will benefit from insights on managing virtual teams as well as techniques for introducing complex technology into businesses. Covering best practices in enterprise systems integration, the text highlights applications across various business enterprises to help you: Bring together existing systems for business processes improvement Design and implement systems that can be reconfigured quickly and easily in response to evolving operational needs Establish procedures for achieving smooth migrations from legacy systems-with minimal disruption to existing operations Complete with case studies, this book illustrates the current state of the art in the context of user requirements and integration and provides the up-to-date understanding required to manage today's complex and interconnected systems.

Artificial intelligence is changing the world of work. How can HR professionals understand the variety of opportunities AI has created for the HR function and how best to implement these in their organization? This book provides the answers. From using natural language processing to ensure job adverts are free from bias and gendered language to implementing chatbots to enhance the employee experience, artificial intelligence can add value throughout the work of HR professionals. Artificial Intelligence for HR demonstrates how to leverage this potential and use AI to improve efficiency and develop a talented and productive workforce. Outlining the current technology landscape as well as the latest AI developments, this book ensures that HR professionals fully understand what AI is and what it means for HR in practice. Alongside coverage of employee engagement and recruitment, this second edition features new material on applications of AI for virtual work, reskilling and data integrity. Packed with practical advice, research and new and updated case studies from global organizations including Uber, IBM and Unilever, the second edition of Artificial Intelligence for HR will equip HR professionals with the knowledge they need to improve people operational efficiencies, and allow AI solutions to become enhancements for driving business success.

Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplinary data mining researchers who cover state-of-the-art biological topics. The first section of the book discusses challenges and opportunities in analyzing and mining biological sequences and structures to gain insight into molecular functions. The second section addresses emerging computational challenges in interpreting high-throughput Omics data. The book then describes the relationships between data mining and related areas of computing, including knowledge representation, information retrieval, and data integration for structured and unstructured biological data. The last part explores emerging data mining opportunities for biomedical applications. This volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques to the rapidly growing field of genome biology. By studying the concepts and case studies presented, readers will gain significant insight and develop practical solutions for similar biological data mining projects in the future.

This book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details.

This book contributes to an improved understanding of knowledge-intensive business services and knowledge management issues. It offers a complex overview of literature devoted to these topics and introduces the concept of 'knowledge flows', which constitutes a missing link in the previous knowledge management theories. The book provides a detailed analysis of knowledge flows, with their types, relations and factors influencing them. It offers a novel approach to understand the aspects of knowledge and its management not only inside the organization, but also outside, in its environment.

This book presents best selected research papers presented at the International Conference on Computer Networks, Big Data and IoT (ICCBI 2020), organized by Vaigai College Engineering, Madurai, Tamil Nadu, India, during 15-16 December 2020. The book covers original papers on computer networks, network protocols and wireless networks, data communication technologies and network security. The book is a valuable resource and reference for researchers, instructors, students, scientists, engineers, managers and industry practitioners in those important areas.

This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA models for optimization. Afterward, the research areas related to LA and optimization are addressed as bibliometric network analysis. Then, LA's application in behavior control in evolutionary computation, and memetic models of object migration automata and cellular learning automata for solving NP hard problems are considered. Next, an overview of multi-population methods for DOPs, LA's application in dynamic optimization problems (DOPs), and the function evaluation management in evolutionary multi-population for DOPs are discussed. Highlighted benefits * Presents the latest advances in learning automata-based optimization approaches. * Addresses the memetic models of learning automata for solving NP-hard problems. * Discusses the application of learning automata for behavior control in evolutionary computation in detail. * Gives the fundamental principles and analyses of the different concepts associated with multi-population methods for dynamic optimization problems.

This book brings together two major trends: data science and blockchains. It is one of the first books to systematically cover the analytics aspects of blockchains, with the goal of linking traditional data mining research communities with novel data sources. Data science and big data technologies can be considered cornerstones of the data-driven digital transformation of organizations and society. The concept of blockchain is predicted to enable and spark transformation on par with that associated with the invention of the Internet. Cryptocurrencies are the first successful use case of highly distributed blockchains, like the world wide web was to the Internet. The book takes the reader through basic data exploration topics, proceeding systematically, method by method, through supervised and unsupervised learning approaches and information visualization techniques, all the way to understanding the blockchain data from the network science perspective. Chapters introduce the cryptocurrency blockchain data model and methods to explore it using structured query language, association rules, clustering, classification, visualization, and network science. Each chapter introduces basic concepts, presents examples with real cryptocurrency blockchain data and offers exercises and questions for further discussion. Such an approach intends to serve as a good starting point for undergraduate and graduate students to learn data science topics using cryptocurrency blockchain examples. It is also aimed at researchers and analysts who already possess good analytical and data skills, but who do not yet have the specific knowledge to tackle analytic questions about blockchain transactions. The readers improve their knowledge about the essential data science techniques in order to turn mere transactional information into social, economic, and business insights.

This book presents the first broad reflection on the challenges, opportunities, and implications of Artificial Intelligence (AI) in the Gulf Cooperation Council (GCC). Unique results and insights are derived through case studies from diverse disciplines, including engineering, economics, data science, policy-making, governance, and humanscience. Particularly related to these 'softer' disciplines, we make some unexplored yet topical contributions to the literature, with a focus on the GCC (but by no means limited to it), including AI and implications for women, Islamic schools of thought on AI, and the power of AI to help deliver wellbeing and happiness in cities and urban spaces. Finally, the readers are provided with a synthesis of ideas, lessons learned, and a path forward based on the diverse content of the chapters. The book caters to the educated non specialist with interest in AI, targeting a wide audience including professionals, academics, government officials, policymakers, entrepreneurs, and non-governmental organizations.

This collection of articles is the first attempt by academics and professional writers to delve into the world of content management systems. The knowledge economy's greatest asset and primary problem is information management: finding it, validating it, re-purposing it, keeping it current, and keeping it safe. In the last few years content management software has become as common as word-processing software was five years ago. But unlike word processors, which are designed for single authorization and local storage, content management systems are designed to accommodate large-scale information production, with many authors providing many different pieces of information kept in a web-accessible database, any piece of which might find its way into electronic documents that the author doesn't even know exist. These software systems are complex, to say the least, and their impact on the field of writing will be immense.

This book contains selected papers presented at the 15th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School on Privacy and Identity Management, held in Maribor, Slovenia, in September 2020.*The 13 full papers included in this volume were carefully reviewed and selected from 21 submissions. Also included is a summary paper of a tutorial. As in previous years, one of the goals of the IFIP Summer School was to encourage the publication of thorough research papers by students and emerging scholars. The papers combine interdisciplinary approaches to bring together a host of perspectives, such as technical, legal, regulatory, socio-economic, social or societal, political, ethical, anthropological, philosophical, or psychological perspectives. *The summer school was held virtually.

This book is your comprehensive guide to understanding Blockchain and Blockchain consensus algorithms. It covers distributed systems, distributed consensus, and relevant system models. And you'll explore how classical and modern consensus algorithms work. The book also covers quantum consensus and explains the role that quantum computing plays in distributed systems. Consensus protocols allow participants in distributed systems to agree on a common value, despite faults. It's a fundamentally important construct in distributed systems. As a result of rigorous and ground-breaking research over the last four decades, many consensus mechanisms have been developed and are used in the industry today. However, with the advent of Blockchain technology, a renewed interest has arisen in this area, resulting in more research and innovation. The first Blockchain, Bitcoin, was invented in 2008 and introduced a novel consensus protocol called Nakamoto consensus, a solution to the Byzantine General's problem formulated almost 30 years ago. Since the introduction of Bitcoin, the interest in Blockchain and consensus protocols has risen exponentially. As a result, researchers from academia and industry have proposed many new consensus mechanisms. While fundamental goals and some techniques remain the same as established classical protocols, these modern protocols introduce innovative methods to achieve consensus in Blockchain. Some classical algorithms have been modified to make them suitable for Blockchain and some new protocols have been developed. This book is a detailed account of classical distributed consensus and Blockchain consensus algorithms. It explains why and how cryptocurrencies and Blockchain remain secure and decentralized without depending on a trusted third party. In addition, you'll learn how Blockchain can endure, even with hundreds or thousands of participants, out of which some might be malicious. The book introduces quantum consensus, which deals with the problem of reaching agreement in quantum networks and how to enhance classical results. What You Will Learn Understand distributed systems, distributed consensus, and relevant system models and protocols Understand Blockchain and Blockchain consensus algorithms Know how classical and modern consensus algorithms work Know the inner workings of Paxos, RAFT, PBFT, HotStuff, proof of work, proof of stake, GRANDPA, Casper, proof of history, and other consensus protocols Understand quantum Byzantine agreement and quantum consensus Who This Book Is For Distributed systems and Blockchain students and researchers, Blockchain practitioners, architects, designers, product managers, and developers This book targets many audiences as well as those with curious minds. It explains the classical consensus mechanisms, Blockchain age consensus protocols, and the latest developments in distributed consensus. The book does not assume any advanced knowledge of Blockchain or distributed systems, but a general understanding of computing and appreciation of Blockchain technology is helpful. Early chapters provide the necessary background to read and understanding consensus-related content quickly. Readers who already understand classical consensus protocols and distributed systems but want to learn about Blockchain consensus will find the book helpful as it covers Blockchain age protocols in detail. Readers who have come to the Blockchain world without any, or with little, background in distributed systems or classical consensus protocols will find this book equally helpful as it provides a solid understanding of classical consensus protocols. If you have no experience in Blockchain or don't understand distributed computing in general, this book will give you a solid understanding of both subjects and enable you to conduct further research in this exciting area of distributed computing.

Focusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Mainly based on the authors' own research work, the book takes a practical approach to the subject. The first part of the book reviews data mining techniques, such as artificial neural networks and support vector machines, as well as data mining applications. The second section covers the design and implementation of data mining tools for intrusion detection. It examines various designs and performance results, along with the strengths and weaknesses of the approaches. The third part presents techniques to solve the WWW prediction problem. The final part describes models that the authors have developed for image classification. Showing step by step how data mining tools are developed, this hands-on guide discusses the performance results, limitations, and unique contributions of data mining systems. It provides essential information for technologists to decide on the tools to select for a particular application, for developers to focus on alternative designs if an approach is unsuitable, and for managers to choose whether to proceed with a data mining project.

This book constitutes the refereed proceedings of the 36th IFIP TC 11 International Conference on Information Security and Privacy Protection, SEC 2021, held in Oslo, Norway, in June 2021.*The 28 full papers presented were carefully reviewed and selected from 112 submissions. The papers present novel research on theoretical and practical aspects of security and privacy protection in ICT systems. They are organized in topical sections on digital signatures; vulnerability management; covert channels and cryptography; application and system security; privacy; network security; machine learning for security; and security management. *The conference was held virtually.

This book constitutes the refereed proceedings of the 17th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2021, held virtually and in Hersonissos, Crete, Greece, in June 2021. The 50 full papers and 11 short papers presented were carefully reviewed and selected from 113 submissions. They cover a broad range of topics related to technical, legal, and ethical aspects of artificial intelligence systems and their applications and are organized in the following sections: adaptive modeling/ neuroscience; AI in biomedical applications; AI impacts/ big data; automated machine learning; autonomous agents; clustering; convolutional NN; data mining/ word counts; deep learning; fuzzy modeling; hyperdimensional computing; Internet of Things/ Internet of energy; machine learning; multi-agent systems; natural language; recommendation systems; sentiment analysis; and smart blockchain applications/ cybersecurity. Chapter "Improving the Flexibility of Production Scheduling in Flat Steel Production Through Standard and AI-based Approaches: Challenges and Perspective" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book, the second volume, highlights 7 out of a total of about 36 megacities in the World which by definition have 10 million inhabitants. The cities/chapters presented in this book are based on recent advance such as the wide use of ICT, IOT, e-Governance, e-Democracy, smart economy and flattening and acceleration of the world that is taking place in recent times as reported by 3 times Pulitzer Prize Winner Thomas Friedman. It therefor departs from other ideologies where only a certain megacity qualifies for the title of smart global megacities while in reality every megacity can, and presents how smart global megacities can be created.