Designed to offer an accessible set of case studies and analyses of ethical dilemmas in data science. This book will be suitable for technical readers in data science who want to understand diverse ethical approaches to AI.

Rough Sets and Data Mining: Analysis of Imprecise Data is an edited collection of research chapters on the most recent developments in rough set theory and data mining. The chapters in this work cover a range of topics that focus on discovering dependencies among data, and reasoning about vague, uncertain and imprecise information. The authors of these chapters have been careful to include fundamental research with explanations as well as coverage of rough set tools that can be used for mining data bases. The contributing authors consist of some of the leading scholars in the fields of rough sets, data mining, machine learning and other areas of artificial intelligence. Among the list of contributors are Z. Pawlak, J Grzymala-Busse, K. Slowinski, and others. Rough Sets and Data Mining: Analysis of Imprecise Data will be a useful reference work for rough set researchers, data base designers and developers, and for researchers new to the areas of data mining and rough sets.

While most discoverability evaluation studies in the Library and Information Science field discuss the intersection of discovery layers and library systems, this book looks specifically at digital repositories, examining discoverability from the lenses of system structure, user searches, and external discovery avenues. Discoverability, the ease with which information can be found by a user, is the cornerstone of all successful digital information platforms. Yet, most digital repository practitioners and researchers lack a holistic and comprehensive understanding of how and where discoverability happens. This book brings together current understandings of user needs and behaviors and poses them alongside a deeper examination of digital repositories around the theme of discoverability. It examines discoverability in digital repositories from both user and system perspectives by exploring how users access content (including their search patterns and habits, need for digital content, effects of outreach, or integration with Wikipedia and other web-based tools) and how systems support or prevent discoverability through the structure or quality of metadata, system interfaces, exposure to search engines or lack thereof, and integration with library discovery tools. Discoverability in Digital Repositories will be particularly useful to digital repository managers, practitioners, and researchers, metadata librarians, systems librarians, and user studies, usability and user experience librarians. Additionally, and perhaps most prominently, this book is composed with the emerging practitioner in mind. Instructors and students in Library and Information Science and Information Management programs will benefit from this book that specifically addresses discoverability in digital repository systems and services.

Every day we need to solve large problems for which supercomputers are needed. High performance computing (HPC) is a paradigm that allows to efficiently implement large-scale computational tasks on powerful supercomputers unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many challenging real world problems arising in engineering, economics, medicine and other areas can be formulated as large-scale computational tasks. The volume is a comprehensive collection of extended contributions from the High performance computing conference held in Borovets, Bulgaria, September 2019. This book presents recent advances in high performance computing. The topics of interest included into this volume are: HP software tools, Parallel Algorithms and Scalability, HPC in Big Data analytics, Modelling, Simulation & Optimization in a Data Rich Environment, Advanced numerical methods for HPC, Hybrid parallel or distributed algorithms. The volume is focused on important large-scale applications like Environmental and Climate Modeling, Computational Chemistry and Heuristic Algorithms.

This book introduces novel methods for leak and blockage detection in pipelines. The leak happens as a result of ageing pipelines or extreme pressure forced by operational error or valve rapid variation. Many factors influence blockage formation in pipes like wax deposition that leads to the formation and eventual growth of solid layers and deposition of suspended solid particles in the fluids. In this book, initially, different categories of leak detection are overviewed. Afterwards, the observability and controllability of pipeline systems are analysed. Control variables can be usually presented by pressure and flow rates at the start and end points of the pipe. Different cases are considered based on the selection of control variables to model the system. Several theorems are presented to test the observability and controllability of the system. In this book, the leakage flow in the pipelines is studied numerically to find the relationship between leakage flow and pressure difference. Removing leakage completely is almost impossible; hence, the development of a formal systematic leakage control policy is the most reliable approach to reducing leakage rates.

This book addresses the need for materials which can help the IS researcher determine which qualitative methods are most appropriate for addressing their particular research questions. It draws on the collective expertise of distinguished scholars to explore concrete issues they have encountered in the use of a particular qualitative method.

This book consists of 35 chapters presenting different theoretical and practical aspects of Intelligent Information and Database Systems. Nowadays both Intelligent and Database Systems are applied in most of the areas of human activities which necessitates further research in these areas. In this book various interesting issues related to the intelligent information models and methods as well as their advanced applications, database systems applications, data models and their analysis and digital multimedia methods and applications are presented and discussed both from the practical and theoretical points of view. The book is organized in four parts devoted to intelligent systems models and methods, intelligent systems advanced applications, database systems methods and applications and multimedia systems methods and applications. The book will be interesting forpractitioners and researchers, especially graduate and PhD students of information technology and computer science, as well more experienced academics and specialists interested in developing and verification of intelligent information, database and multimedia systems models, methods and applications. The readers of this volume are enabled to find many inspiring ideas and motivating practical examples that will help them in the current and future work."

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.

This book constitutes the refereed post-conference proceedings of the IFIP TC 3 Open Conference on Computers in Education, OCCE 2020, held in Mumbai, India, in January 2020. The 11 full papers and 4 short papers included in this volume were carefully reviewed and selected from 57 submissions. The papers discuss key emerging topics and evolving practices in the area of educational computing research. They are organized in the following topical sections: computing education; learners' and teachers' perspectives; teacher professional development; the industry perspective; and further aspects.

This book gathers the outcomes of the second ECCOMAS CM3 Conference series on transport, which addressed the main challenges and opportunities that computation and big data represent for transport and mobility in the automotive, logistics, aeronautics and marine-maritime fields. Through a series of plenary lectures and mini-forums with lectures followed by question-and-answer sessions, the conference explored potential solutions and innovations to improve transport and mobility in surface and air applications. The book seeks to answer the question of how computational research in transport can provide innovative solutions to Green Transportation challenges identified in the ambitious Horizon 2020 program. In particular, the respective papers present the state of the art in transport modeling, simulation and optimization in the fields of maritime, aeronautics, automotive and logistics research. In addition, the content includes two white papers on transport challenges and prospects. Given its scope, the book will be of interest to students, researchers, engineers and practitioners whose work involves the implementation of Intelligent Transport Systems (ITS) software for the optimal use of roads, including safety and security, traffic and travel data, surface and air traffic management, and freight logistics.

Web Semantics Ontology provides an excellent overview of current research and development activities, while covering an extensive range of topics including ontological modeling, enterprise systems, querying and knowledge discovery, and a wide range of applications. Each chapter contains a thorough study of the topic, systematic proposed work, and a comprehensive list of references. The theoretical and practical aspects of Web semantics and ontology development combine to bring a unique perspective to this book. Researchers, software developers, and IT students who want to enhance their knowledge of issues relating to modeling, adopting, querying, discovering knowledge, and building ontologies and Web semantics will benefit from ""Web Semantics Ontology.

This book introduces the field of Health Web Science and presents methods for information gathering from written social media data. It explores the availability and utility of the personal medical information shared on social media platforms and determines ways to apply this largely untapped information source to healthcare systems and public health monitoring. Introducing an innovative concept for integrating social media data with clinical data, it addresses the crucial aspect of combining experiential data from social media with clinical evidence, and explores how the variety of available social media content can be analyzed and implemented. The book tackles a range of topics including social media's role in healthcare, the gathering of shared information, and the integration of clinical and social media data. Application examples of social media for health monitoring, along with its usage in patient treatment are also provided. The book also considers the ethical and legal issues of gathering and utilizing social media data, along with the risks and challenges that must be considered when integrating social media data into healthcare choices. With an increased interest internationally in E-Health, Health 2.0, Medicine 2.0 and the recent birth of the discipline of Web Science, this book will be a valuable resource for researchers and practitioners investigating this emerging topic.

This work provides an assessment of the current state of near field communication (NFC) security, it reports on new attack scenarios, and offers concepts and solutions to overcome any unresolved issues. The work describes application-specific security aspects of NFC based on exemplary use-case scenarios and uses these to focus on the interaction with NFC tags and on card emulation. The current security architectures of NFC-enabled cellular phones are evaluated with regard to the identified security aspects.

Focuses on the Internet of Healthcare Things and innovative solutions developed for use in the application of healthcare services Discusses artificial intelligence applications, experiments, core concepts, and cutting-edge themes Demonstrates new approaches to analysing medical data and identifying ailments using AI to improve overall quality of life Introduces fundamental concepts for designing the Internet of Healthcare Things solutions Includes pertinent case studies and applications

This book constitutes the refereed proceedings of the 40th International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2014, held in Novy Smokovec, Slovakia, in January 2014. The 40 revised full papers presented in this volume were carefully reviewed and selected from 104 submissions. The book also contains 6 invited talks. The contributions covers topics as: Foundations of Computer Science, Software and Web Engineering, as well as Data, Information and Knowledge Engineering and Cryptography, Security and Verification."

Includes case studies illustrating the business processes that underlines the use of big data and health analytics to improve healthcare delivery Discusses AI based smart paradigms for reliable predictions of infectious disease dynamics which can help or prevent disease transmission Highlights the different aspects of using extended reality for diverse healthcare applications and aggregates the current state of research Offers intelligent models of the smart recommender system for personal well-being services and computer-aided drug discovery and design methods Presents novel innovative techniques for extracting user social behavior known as sentiment analysis for healthcare related purposes

Blockchain Supply Chain Use Cases. Distributed Ledger Technology Supply Chain Use Cases. Blockchain-Enabled Digital Transformation Use Cases. Blockchain Supply Chain Diffusion/Innovation Use Cases.

This book provides a general introduction to Sequential Monte Carlo (SMC) methods, also known as particle filters. These methods have become a staple for the sequential analysis of data in such diverse fields as signal processing, epidemiology, machine learning, population ecology, quantitative finance, and robotics. The coverage is comprehensive, ranging from the underlying theory to computational implementation, methodology, and diverse applications in various areas of science. This is achieved by describing SMC algorithms as particular cases of a general framework, which involves concepts such as Feynman-Kac distributions, and tools such as importance sampling and resampling. This general framework is used consistently throughout the book. Extensive coverage is provided on sequential learning (filtering, smoothing) of state-space (hidden Markov) models, as this remains an important application of SMC methods. More recent applications, such as parameter estimation of these models (through e.g. particle Markov chain Monte Carlo techniques) and the simulation of challenging probability distributions (in e.g. Bayesian inference or rare-event problems), are also discussed. The book may be used either as a graduate text on Sequential Monte Carlo methods and state-space modeling, or as a general reference work on the area. Each chapter includes a set of exercises for self-study, a comprehensive bibliography, and a "Python corner," which discusses the practical implementation of the methods covered. In addition, the book comes with an open source Python library, which implements all the algorithms described in the book, and contains all the programs that were used to perform the numerical experiments.

Big Data in History introduces a project to create a world-historical archive that will trace the last four centuries of historical dynamics and change. The archive will link research on social, economic, and political affairs, plus health and climate, for societies throughout the world. The care, detail, and advanced technology that go into building such an archive are outlined in this book, and the benefits of gathering and disseminating data from our long history are clearly mapped out. Chapters address the archive's overall plan, how to interpret the past through a global archive, how to organize historical research on five continents, and the missions of gathering widespread records, linking local data into global patterns, and exploring the results. The concluding chapters summarize project plans and compare it with two major and successful projects in worldwide data: the modelling of climate and documenting the human genome.

Discusses the efficiency measurement of online education Presents the environmental impact of online education Offers a parametric evaluation and categorization of online learning systems Covers big data ecosystems in cloud computing Provides analytical methods to find solutions for big data challenges

Digital Image Processing with C++ presents the theory of digital image processing, and implementations of algorithms using a dedicated library. Processing a digital image means transforming its content (denoising, stylizing, etc.), or extracting information to solve a given problem (object recognition, measurement, motion estimation, etc.). This book presents the mathematical theories underlying digital image processing, as well as their practical implementation through examples of algorithms implemented in the C++ language, using the free and easy-to-use CImg library. Chapters cover in a broad way the field of digital image processing and proposes practical and functional implementations of each method theoretically described. The main topics covered include filtering in spatial and frequency domains, mathematical morphology, feature extraction and applications to segmentation, motion estimation, multispectral image processing and 3D visualization. Students or developers wishing to discover or specialize in this discipline, teachers and researchers wishing to quickly prototype new algorithms, or develop courses, will all find in this book material to discover image processing or deepen their knowledge in this field.

This book treats intellectual capital, smart technologies, and digitalization processes as levers of corporate competitiveness and global value creation. This book is based on theoretical and practical research output from the STEDIC SIDREA Group. It uses several methodologies to discover features and pillars on intellectual capital such as human capital, relational capital, and structural capital as well as smart technologies such as artificial intelligence, Internet of Things, big data, and digitalization.

This book is a collection of selected papers presented at the First International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC), held as an online conference due to COVID-19 (initially to be held in Macao, Special Administration Region (SAR) of China), during September 15-17, 2020. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and industry. It brings multi-disciplines together on IIoT, data science, cloud computing, software engineering approaches to design, development, testing and quality of products and services.

The book aims at presenting a multidisciplinary view meant to illustrate several significant efforts and results about the contribution of information technologies to make available new resources and enable rationally usage the existing ones in the context of the ever-growing trends to use ever more resources. Authors from various countries have been invited to contribute so that a rather broad and balanced image about the current trends and recent results obtained could result. The proposed book addresses methodologies and information technology-based tools and systems designed for the efficient use of diverse resources such as manpower and human knowledge, natural resources including water, raw materials and end of life products, financial assets, datasets, and even cultural goods. The book is organized in ten chapters. It is intended to be insightful for researchers, instructors, and planers from various domains. It can also be used as an auxiliary material for postgraduate studies in applied informatics, business administration, industrial engineering, engineering and management, computer, and digital humanities.