This book offers an in-depth and recent account of the research in Artificial Intelligence (AI) technologies and how it is impacting and shaping the field of international human resource management (IHRM). Grounded in contemporary developments in the field of technological change and the Future of Work and the fourth industrial revolution (4IR), the book lays down a solid foundation by offering a comprehensive review of the field of AI and IHRM. It includes empirical research, including case studies of global MNEs and conceptual chapters focusing on the impact of AI on IHRM practices and therefore business-level outcomes of productivity, efficiency, and effectiveness through the adoption of AI-assisted HR applications. The chapters in this volume evaluate individual IHRM practices and study how they impact employee-level outcomes of job satisfaction, personalization, employee commitment and so on. Finally, the book concludes by identifying current gaps in the literature and offers directions for future research for scholars to develop and advance future research agendas in the field. This volume will be of great use to researchers, academics and students in the fields of business and management, especially those with a particular interest in new age technologies of operating business. The chapters in this book, except for Conclusion, were originally published as a special issue of The International Journal of Human Resource Management.

The rich, multi-faceted and multi-disciplinary field of matching-based market design is an active and important one due to its highly successful applications with economic and sociological impact. Its home is economics, but with intimate connections to algorithm design and operations research. With chapters contributed by over fifty top researchers from all three disciplines, this volume is unique in its breadth and depth, while still being a cohesive and unified picture of the field, suitable for the uninitiated as well as the expert. It explains the dominant ideas from computer science and economics underlying the most important results on market design and introduces the main algorithmic questions and combinatorial structures. Methodologies and applications from both the pre-Internet and post-Internet eras are covered in detail. Key chapters discuss the basic notions of efficiency, fairness and incentives, and the way market design seeks solutions guided by normative criteria borrowed from social choice theory.

Stochastic modeling is a set of quantitative techniques for analyzing practical systems with random factors. This area is highly technical and mainly developed by mathematicians. Most existing books are for those with extensive mathematical training; this book minimizes that need and makes the topics easily understandable. Fundamentals of Stochastic Models offers many practical examples and applications and bridges the gap between elementary stochastics process theory and advanced process theory. It addresses both performance evaluation and optimization of stochastic systems and covers different modern analysis techniques such as matrix analytical methods and diffusion and fluid limit methods. It goes on to explore the linkage between stochastic models, machine learning, and artificial intelligence, and discusses how to make use of intuitive approaches instead of traditional theoretical approaches. The goal is to minimize the mathematical background of readers that is required to understand the topics covered in this book. Thus, the book is appropriate for professionals and students in industrial engineering, business and economics, computer science, and applied mathematics.

• Truly innovative book and the first of its kind to combine the emerging research areas of Industry 4 technologies or Construction 4.0 with Health, Safety and Wellbeing in the industry • Builds on the existing Construction 4.0 framework to incorporate detailed research into a sector responsible for 100,000 deaths a year

Although cryptography plays an essential part in most modern solutions, especially in payments, cryptographic algorithms remain a black box for most users of these tools. Just as a sane backend developer does not drill down into low-level disk access details of a server filesystem, payments professionals have enough things to worry about before they ever need to bother themselves with debugging an encrypted value or a message digest. However, at a certain point, an engineer faces the need to identify a problem with a particular algorithm or, perhaps, to create a testing tool that would simulate a counterpart in a protocol that involves encryption. The world of cryptography has moved on with giant leaps. Available technical standards mention acronyms and link to more standards, some of which are very large while others are not available for free. After finding the standards for the algorithm, the specific mode of operation must also be identified. Most implementations use several cryptographic primitives—for example, key derivation with a block cipher, which produces a secret that is used together with a hash function and a double padding scheme to produce a digital signature of a base64-encoded value. Understanding this requires more sifting through online sources, more reading of platform and library documents, and finally, when some code can be written, there are very few test cases to validate it. Cryptography for Payment Professionals is intended for technical people, preferably with some background in software engineering, who may need to deal with a cryptographic algorithm in the payments realm. It does not cover the payment technology in-depth, nor does it provide more than a brief overview of some regulations and security standards. Instead, it focuses on the cryptographic aspects of each field it mentions. Highlights include: Major cryptographic algorithms and the principles of their operation Cryptographic aspects of card-present (e.g., magnetic stripe, EMV) and online (e.g., e-Commerce and 3DS 2.0) transactions A detailed description of TDES DUKPT and AES DUKPT protocols, as well as an example implementation and test cases for both It is best if the reader understands programming, number and string representations in machine memory, and bit operations. Knowledge of C, Python, or Java may make the examples easier to read but this is not mandatory. Code related to the book is available at the author’s GitHub site: https://github.com/ilya-dubinsky/cfpp

Explores text mining and IoT applications for monitoring and controlling smart industrial systems Describes the key principles and techniques for Big-data analytics, security, and optimization for industrial applications. Provides context-aware insights, human-centric industry, smart computing for next-generation industry

This book is about the simulation and modeling of novel chaotic systems within the frame of fractal-fractional operators. The methods used, their convergence, stability, and error analysis are given, and this is the first book to offer mathematical modeling and simulations of chaotic problems with a wide range of fractal-fractional operators, to find solutions. Numerical Methods for Fractal-Fractional Differential Equations and Engineering: Simulations and Modeling provides details for stability, convergence, and analysis along with numerical methods and their solution procedures for fractal-fractional operators. The book offers applications to chaotic problems and simulations using multiple fractal-fractional operators and concentrates on models that display chaos. The book details how these systems can be predictable for a while and then can appear to become random. Practitioners, engineers, researchers, and senior undergraduate and graduate students from mathematics and engineering disciplines will find this book of interest._

This book is a compendium of various applications and current progress in a powerful technology known as the Internet of Things (IoT). IoT provides a system of interconnecting things such as vehicles, electrical equipment, agriculture devices, etc. Such items are allocated with the computing device so that they can use a network to transfer data to one another and automate their actions on certain events. Internet of Things: Applications for Sustainable Development will throw light on recent developments in the latest field and will be of great interest to know various application areas for sustainable development. This book mainly focuses on the current state of the art, including protocol design and low-cost sensor design, for the sustainable development of society using IoT. The sustainable development areas include climate, healthcare systems, electrical systems, and energy that can meet present and next-generation advancement using IoT. Sustainable development faces various issues, challenges, opportunities, and future enhancements with the latest technologies, hardware, and software. Features: A real-world problem-solving approach for diversified problems Potential contributors from industries/academia have been given the opportunity to publish their work Identification of various challenges in IoT for future contributions Diversified coverage of the book, including applications, securities, industrialization, automation, etc IoT for the sustainable development areas This book will offer strong support as a reference book for students, practitioners, researchers, and scientific investigators worldwide, as well as anyone who wants to set up IoT-enabled industries. It provides pertinent industries with new ideas and innovations to visionaries.

Provides a wide range of case studies of music in film scenes, allowing instructors to pick and choose examples to focus on. Each case study is accessibly written and follows the same format, breaking down elements of the scene for students in a clear manner that invites comparisons. Organized by the type of musical use, allowing instructors to readily find examples of different types of music functions, and compare across different films.

This addition to the Data Science Series introduces the principles of data science and the R language to the singular needs of water professionals. The book provides unique data and examples relevant to managing water utility and is sourced from the author’s extensive experience. Data Science for Water Utilities: Data as a Source of Value is an applied, practical guide that shows water professionals how to use data science to solve urban water management problems. Content develops through four case studies. The first looks at analysing water quality to ensure public health. The second considers customer feedback. The third case study introduces smart meter data. The guide flows easily from basic principles through code that, with each case study, increases in complexity. The last case study analyses data using basic machine learning. Readers will be familiar with analysing data but do not need coding experience to use this book. The title will be essential reading for anyone seeking a practical introduction to data science and creating value with R.

Provides background material needed to understand digital twin technology Presents computational facet of digital twin Includes physics based and surrogate model representations Addresses the problem of uncertainty in measurements and modeling Discusses practical case studies of implementation of digital twins addressing additive manufacturing, server farms, predictive maintenance, and smart cities

Cloud computing, the Internet of Things (IoT), and big data are three significant technological trends affecting the world's largest corporations. This book discusses big data, cloud computing, and the IoT, with a focus on the benefits and implementation problems. In addition, it examines the many structures and applications pertinent to these disciplines. Also, big data, cloud computing, and the IoT are proposed as possible study avenues. Features: Informs about cloud computing, IoT and big data, including theoretical foundations and the most recent empirical findings Provides essential research on the relationship between various technologies and the aggregate influence they have on solving real-world problems Ideal for academicians, developers, researchers, computer scientists, practitioners, information technology professionals, students, scholars, and engineers exploring research on the incorporation of technological innovations to address contemporary societal challenges

This book elaborates fuzzy machine and deep learning models for single class mapping from multi-sensor, multi-temporal remote sensing images while handling mixed pixels and noise. It also covers the ways of pre-processing and spectral dimensionality reduction of temporal data. Further, it discusses the ‘individual sample as mean’ training approach to handle heterogeneity within a class. The appendix section of the book includes case studies such as mapping crop type, forest species, and stubble burnt paddy fields. Key features: Focuses on use of multi-sensor, multi-temporal data while handling spectral overlap between classes Discusses range of fuzzy/deep learning models capable to extract specific single class and separates noise Describes pre-processing while using spectral, textural, CBSI indices, and back scatter coefficient/Radar Vegetation Index (RVI) Discusses the role of training data to handle the heterogeneity within a class Supports multi-sensor and multi-temporal data processing through in-house SMIC software Includes case studies and practical applications for single class mapping This book is intended for graduate/postgraduate students, research scholars, and professionals working in environmental, geography, computer sciences, remote sensing, geoinformatics, forestry, agriculture, post-disaster, urban transition studies, and other related areas.

This textbook is a comprehensive introduction to computational mathematics and scientific computing suitable for undergraduate and postgraduate courses. It presents both practical and theoretical aspects of the subject, as well as advantages and pitfalls of classical numerical methods alongside with computer code and experiments in Python. Each chapter closes with modern applications in physics, engineering, and computer science. No previous experience in Python is required Simplified computer code for fast-paced learning and transferable skills development Includes practical problems ideal for project assignments and distance learning Presents both intuitive and rigorous faces of modern scientific computing Provides an introduction to neural networks and machine learning

Video has rich information including meta-data, visual, audio, spatial and temporal data which can be analysed to extract a variety of low and high-level features to build predictive computational models using machine-learning algorithms to discover interesting patterns, concepts, relations, and associations. This book includes a review of essential topics and discussion of emerging methods and potential applications of video data mining and analytics. It integrates areas like intelligent systems, data mining and knowledge discovery, big data analytics, machine learning, neural network, and deep learning with focus on multimodality video analytics and recent advances in research/applications. Features: Provides up-to-date coverage of the state-of-the-art techniques in intelligent video analytics. Explores important applications that require techniques from both artificial intelligence and computer vision. Describes multimodality video analytics for different applications. Examines issues related to multimodality data fusion and highlights research challenges. Integrates various techniques from video processing, data mining and machine learning which has many emerging indoors and outdoors applications of smart cameras in smart environments, smart homes, and smart cities. This book aims at researchers, professionals and graduate students in image processing, video analytics, computer science and engineering, signal processing, machine learning, and electrical engineering.

With the advent of advanced hand-held technology and the widespread nature of the Internet, the world of animated filmmaking is more exciting and accessible than ever. Due to this cultural and technological development, the success of independent animated film makers is on the rise. Independent Animation: Developing, Producing and Distributing Your Animated Films, Second Edition showcases some of the greatest, most innovative giants in the field and helps guide readers through the artistic process and production techniques. Story development, casting, color theory, distribution and the intimidating aspects of production are elucidated using various examples of acclaimed, viral and award-winning animated films from all over the world. Readers will also explore the changing nature of audiences, festivals and distributors’ relationships with animation and be granted first-hand guidance in navigating the diverse fields of animated filmmaking. Key Features: Covers the entire process of creating an independent animated film from story development and casting to editing and distribution Presents a comprehensive array of classic and contemporary case studies covering all manner of production methods from traditional pipelines to avant-garde, auteur and experimental approaches Features input and exclusive insight into the working processes of some of the industry’s most noteworthy indie animation talents, including Signe Baumane, Adam Elliot, Don Hertzfeldt, Kirsten Lepore, Robert Morgan, David OReilly, PES, Bill Plympton, Rosto, Chris Shepherd and dozens more Additional resources and interviews are available through a special section of Skwigly Online Animation Magazine.

• Utilizes case studies from different disciplines and sectors within engineering and other related technical areas to demonstrate how to go from data, to insight, and to decision making • Introduces various approaches to build models that exploits different algorithms • Discusses predictive models that can be built through machine learning and used to mine patterns from large datasets • Explores the augmentation of technical and mathematical materials with explanatory worked examples • Includes a glossary, lecture notes, self-assessments, and worked-out practice exercises

*A practical guide to Machine Learning and its applications in translation, in the specific context of translator/localizer training and education * written to be equally useful for both students on translation studies courses and professionals in the area of localization *Unlike existing titles, it focuses on bridging the gap between machine learning technology in the humanities and translation practice and takes a bottom-up, relevancy approach to Machine Learning in Translation

Introduces different optimization algorithms together to solve complex combinatorial optimization problems related to hospital management system or healthcare Applies machine learning-based analytics such as GAN networks, autoencoders, computational imaging, and quantum computing to authentic hospital management problems Discusses metaheuristic algorithms such as evolutionary algorithms to cope with the fundamental steps of image processing, image analysis, and computer vision pipeline (e.g., restoration, segmentation, registration, classification, reconstruction, or tracking) Creates a bridge between Computational Intelligence and Industrial Engineering towards designing complex and convoluted hospital management problems

Unique selling point: Comprehensive tome on developing and implementing parallel and distributed systems Core audience: Computer science title for systems developers and designers Place in the market: Professional title for a niche segment of developers and programmers

1. Discusses the concept of Social IoT beyond the combinations of Social media and IoT 2. Stimulates research on the topic of the Social Internet of Things 3. Pays special attention to a human centric perspective 4. Provides several characteristics of social, network, and physical security associated with social information networks

This textbook offers an accessible introduction to the historical, technical, and strategic context of global cyber conflict. The second edition has been revised and updated throughout, with three new chapters. Cyber warfare involves issues of doctrine, strategy, policy, international relations (IR) and operational practice associated with computer network attack, computer network exploitation and computer network defense. However, it is conducted within complex sociopolitical settings alongside related forms of digital contestation. This book provides students with a comprehensive perspective on the technical, strategic and policy issues associated with cyber conflict, as well as an introduction to key state and non-state actors. Specifically, the book provides a comprehensive overview of several key issue areas: The historical context of the emergence and evolution of cyber warfare, including the basic characteristics and methods of computer network attack, exploitation and defense An interdisciplinary set of theoretical perspectives on conflict in the digital age from the point of view of the fields of IR, security studies, psychology and science, technology and society (STS) studies Current national perspectives, policies, doctrines and strategies relevant to cyber warfare An examination of key challenges in international law, norm development and deterrence; and The role of emerging information technologies like artificial intelligence and quantum computing in shaping the dynamics of global cyber conflict This textbook will be essential reading for students of cybersecurity/cyber conflict and information warfare, and highly recommended for students of intelligence studies, security and strategic studies, defense policy, and IR in general.

This book focuses on key challenges related to conducting research on mediatisation, presenting the most current theoretical, empirical, and methodological challenges and problems, addressing ignored and less frequently discussed topics, critical and controversial themes, and defining niches and directions of development in mediatisation. With a focus on the under-representation of certain topics and aspects, as well as methodological, technological, and ethical dilemmas, the chapters consider the main critical objections formulated against mediatisation studies and exchange critical positions. Moving beyond areas of common focus – culture, sport, and religion – to emerging areas of study such as fashion, the military, business, and the environment, the book then offers a critical assessment of the transformation of fields and the relevance of new and dynamic (meta)processes including datafication, counter-mediatisation, and platformisation. Charting new paths of development in mediatisation, this book will be of interest to scholars and students of mediatisation, media studies, media literacy, communication studies, and research methods.

This book focuses on key challenges related to conducting research on mediatisation, presenting the most current theoretical, empirical, and methodological challenges and problems, addressing ignored and less frequently discussed topics, critical and controversial themes, and defining niches and directions of development in mediatisation. With a focus on the under-representation of certain topics and aspects, as well as methodological, technological, and ethical dilemmas, the chapters consider the main critical objections formulated against mediatisation studies and exchange critical positions. Moving beyond areas of common focus – culture, sport, and religion – to emerging areas of study such as fashion, the military, business, and the environment, the book then offers a critical assessment of the transformation of fields and the relevance of new and dynamic (meta)processes including datafication, counter-mediatisation, and platformisation. Charting new paths of development in mediatisation, this book will be of interest to scholars and students of mediatisation, media studies, media literacy, communication studies, and research methods.