This book provides an in-depth insight into the emerging paradigm of End-User Development (EUD), discussing the diversity and potential for creating effective environments for end users. Containing a unique set of contributions from a number of international researchers and institutes, many relevant issues are discussed and solutions proposed, making important aspects of end-user development research available to a broader audience. Most people are familiar with the basic functionality and interfaces of computers. However, developing new or modified applications that can effectively support users' goals still requires considerable programming expertise that cannot be expected of everyone. One of the fundamental challenges that lie ahead is the development of environments that enable users with little or no programming experience to develop and modify their own applications. The ultimate goal is to empower people to flexibly employ and personalise advanced inform ation and communication technologies.

Information technology is a discipline under constant evolution. This collection, entitled Breakthrough Discoveries in Information Technology Research: Advancing Trends, aims to inform researchers and practitioners of novel and emerging research in information science and technology, allowing for the discussion and dissemination of critical concepts that will promote further study and innovation. Selections explore all facets of the discipline, with specific contributions focusing on outsourcing, ethical concerns in research, biometrics, and information technology's role in disaster prediction and prevention.

This book covers ideas, methods, algorithms, and tools for the in-depth study of the performance and reliability of dependable fault-tolerant systems. The chapters identify the current challenges that designers and practitioners must confront to ensure the reliability, availability, and performance of systems, with special focus on their dynamic behaviors and dependencies. Topics include network calculus, workload and scheduling; simulation, sensitivity analysis and applications; queuing networks analysis; clouds, federations and big data; and tools. This collection of recent research exposes system researchers, performance analysts, and practitioners to a spectrum of issues so that they can address these challenges in their work.

This book offers readers a comprehensive guide to the evolution of the database field from its earliest stages up to the present-and from classical relational database management systems to the current Big Data metaphor. In particular, it gathers the most significant research from the Italian database community that had relevant intersections with international projects. Big Data technology is currently dominating both the market and research. The book provides readers with a broad overview of key research efforts in modelling, querying and analysing data, which, over the last few decades, have became massive and heterogeneous areas.

This volume comprises the proceedings of ICITCS 2020. It aims to provide a snapshot of the latest issues encountered in IT convergence and security. The book explores how IT convergence and security is core to most current research, industrial and commercial activities. Topics covered in this volume include machine learning & deep learning, communication and signal processing, computer vision and applications, future network technology, artificial intelligence and robotics, software engineering and knowledge engineering, intelligent vehicular networking and applications, healthcare and wellness, web technology and applications, internet of things, and security & privacy. Through this volume, readers will gain an understanding of the current state-of-the-art information strategies and technologies in IT convergence and security. The book will be of use to researchers in academia, industry and other research institutes focusing on IT convergence and security.

The amount of data shared and stored on the web and other document repositories is steadily on the rise. Unfortunately, this growth increases inefficiencies and difficulties when trying to find the most relevant and up-to-date information due to unstructured data. Advanced Metaheuristic Methods in Big Data Retrieval and Analytics examines metaheuristic techniques as an important alternative model for solving complex problems that are not treatable by deterministic methods. Recent studies suggest that IR and biomimicry can be used together for several application problems in big data and internet of things, especially when conventional methods would be too expensive or difficult to implement. Featuring coverage on a broad range of topics such as ontology, plagiarism detection, and machine learning, this book is ideally designed for engineers, graduate students, IT professionals, and academicians seeking an overview of new trends in information retrieval in big data.

Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species and globalization. Advances in Geographic Information System (GIS) technology, digitization, online data availability, historic legacy datasets, remote sensors and the ability to collect data on animal movements via satellite and GPS have given rise to large, highly complex datasets. These datasets could be utilized for making critical management decisions, but are often "messy" and difficult to interpret. Basic artificial intelligence algorithms (i.e., machine learning) are powerful tools that are shaping the world and must be taken advantage of in the life sciences. In ecology, machine learning algorithms are critical to helping resource managers synthesize information to better understand complex ecological systems. Machine Learning has a wide variety of powerful applications, with three general uses that are of particular interest to ecologists: (1) data exploration to gain system knowledge and generate new hypotheses, (2) predicting ecological patterns in space and time, and (3) pattern recognition for ecological sampling. Machine learning can be used to make predictive assessments even when relationships between variables are poorly understood. When traditional techniques fail to capture the relationship between variables, effective use of machine learning can unearth and capture previously unattainable insights into an ecosystem's complexity. Currently, many ecologists do not utilize machine learning as a part of the scientific process. This volume highlights how machine learning techniques can complement the traditional methodologies currently applied in this field.

As information technology is rapidly progressing, an enormous amount of media can be easily exchanged through Internet and other communication networks. Increasing amounts of digital image, video, and music have created numerous information security issues and is now taken as one of the top research and development agendas for researchers, organizations, and governments worldwide. ""Multimedia Forensics and Security"" provides an in-depth treatment of advancements in the emerging field of multimedia forensics and security by tackling challenging issues such as digital watermarking for copyright protection, digital fingerprinting for transaction tracking, and digital camera source identification.

A secured system for Healthcare 4.0 is vital to all stakeholders, including patients and caregivers. Using the new Blockchain system of trusted ledgers would help guarantee authenticity in the multi-access system that is Healthcare 4.0. This is the first comprehensive book that explores how to achieve secure systems for Healthcare 4.0 using Blockchain, with emphasis on the key challenges of privacy and security. The book is organized into four sections. The first section is focused on 5G healthcare privacy and security concerns. The second section discusses healthcare architecture and emerging technologies. The third section covers the role of artificial intelligence for data security and privacy in 5G healthcare services. Finally, the last section systematically illustrates the adoption of blockchain in various applications of 5G healthcare. The book is essential reading for all involved in setting up, running, and maintaining healthcare information systems. Engineers, scientists, technologists, developers, designers, and researchers in healthcare technologies, health informatics, security, and information technology will find the content particularly useful.

The motivation of this edited book is to generate an understanding about information, related concepts and the roles they play in the modern, technology permeated world. In order to achieve our goal, we observe how information is understood in domains, such as cosmology, physics, biology, neuroscience, computer science, artificial intelligence, the Internet, big data, information society, or philosophy. Together, these observations form an integrated view so that readers can better understand this exciting building-block of modern-day society. On the surface, information is a relatively straightforward and intuitive concept. Underneath, however, information is a relatively versatile and mysterious entity. For instance, the way a physicist looks at information is not necessarily the same way as that of a biologist, a neuroscientist, a computer scientist, or a philosopher. Actually, when it comes to information, it is common that each field has its domain specific views, motivations, interpretations, definitions, methods, technologies, and challenges. With contributions by authors from a wide range of backgrounds, Understanding Information: From the Big Bang to Big Data will appeal to readers interested in the impact of 'information' on modern-day life from a variety of perspectives.

This book presents the latest research in the fields of computational intelligence, ubiquitous computing models, communication intelligence, communication security, machine learning, informatics, mobile computing, cloud computing and big data analytics. The best selected papers, presented at the International Conference on Innovative Data Communication Technologies and Application (ICIDCA 2020), are included in the book. The book focuses on the theory, design, analysis, implementation and applications of distributed systems and networks.

Online education and social interaction is on the rise. This new vehicle for human learning and communication opens the door for the latest exploration in emerging cyber fields.Evolving Psychological and Educational Perspectives on Cyber Behavior identifies learners' online behavior based on the theories in human psychology, defines online education phenomena as explained by the social and cognitive learning theories and principles, and interprets the complexity of cyber learning. This title offers a multi-disciplinary approach that incorporates the findings from brain research, biology, psychology, human cognition, developmental theory, sociology, motivation theory, and social behavior perfect for school teachers, counselors, researchers, and online designers.

This book presents a comprehensive review for Knowledge Engineering tools and techniques that can be used in Artificial Intelligence Planning and Scheduling. KE tools can be used to aid in the acquisition of knowledge and in the construction of domain models, which this book will illustrate. AI planning engines require a domain model which captures knowledge about how a particular domain works - e.g. the objects it contains and the available actions that can be used. However, encoding a planning domain model is not a straightforward task - a domain expert may be needed for their insight into the domain but this information must then be encoded in a suitable representation language. The development of such domain models is both time-consuming and error-prone. Due to these challenges, researchers have developed a number of automated tools and techniques to aid in the capture and representation of knowledge. This book targets researchers and professionals working in knowledge engineering, artificial intelligence and software engineering. Advanced-level students studying AI will also be interested in this book.

This book presents selected papers on Business Management and Technology, focusing on recent research in Business, Optimization, Technology, and Global Issues. Organized in four broad tracks, papers examine Management Challenges in Today's Industry, especially concerning changes in customer demands; Optimization Challenges in Today's Business, looking at efficiency and effectiveness in providing goods and services at affordable prices; Innovation in Hospitality and Tourism; and Technological Challenges in the Era of Globalization. The book covers both production systems and service systems, including the growing area of Information Technology, and also looks at the quality of work life in various sectors of business. It presents a balanced blend of theoretical and practical papers.

This book explores internet applications in which a crucial role is played by classification, such as spam filtering, recommender systems, malware detection, intrusion detection and sentiment analysis. It explains how such classification problems can be solved using various statistical and machine learning methods, including K nearest neighbours, Bayesian classifiers, the logit method, discriminant analysis, several kinds of artificial neural networks, support vector machines, classification trees and other kinds of rule-based methods, as well as random forests and other kinds of classifier ensembles. The book covers a wide range of available classification methods and their variants, not only those that have already been used in the considered kinds of applications, but also those that have the potential to be used in them in the future. The book is a valuable resource for post-graduate students and professionals alike.

This book provides a deep analysis and wide coverage of the very strong trend in computer vision and visual indexing and retrieval, covering such topics as incorporation of models of Human Visual attention into analysis and retrieval tasks. It makes the bridge between psycho-visual modelling of Human Visual System and the classical and most recent models in visual content indexing and retrieval. The large spectrum of visual tasks, such as recognition of textures in static images, of actions in video content, image retrieval, different methods of visualization of images and multimedia content based on visual saliency are presented by the authors. Furthermore, the interest in visual content is modelled with the means of the latest classification models such as Deep Neural Networks is also covered in this book. This book is an exceptional resource as a secondary text for researchers and advanced level students, who are involved in the very wide research in computer vision, visual information indexing and retrieval. Professionals working in this field will also be interested in this book as a reference.

Cryptographic Boolean Functions and Applications, Second Edition is designed to be a comprehensive reference for the use of Boolean functions in modern cryptography. While the vast majority of research on cryptographic Boolean functions has been achieved since the 1970s, when cryptography began to be widely used in everyday transactions, in particular banking, relevant material is scattered over hundreds of journal articles, conference proceedings, books, reports and notes, some of them only available online. This book follows the previous edition in sifting through this compendium and gathering the most significant information in one concise reference book. The work therefore encompasses over 600 citations, covering every aspect of the applications of cryptographic Boolean functions. Since 2008, the subject has seen a very large number of new results, and in response, the authors have prepared a new chapter on special functions. The new edition brings 100 completely new references and an expansion of 50 new pages, along with heavy revision throughout the text.

A new framework for the digital society that merges the science of degrowth with a global analysis of the high-tech economy.

The world is racing toward an irreversible ecological catastrophe. Environmental science makes clear that humans must reduce total material resource use, requiring a radical redistribution of wealth within and between countries. Yet little attention has been paid to how the digital economy fits into this equation.

Michael Kwet is a Postdoctoral researcher of the Centre for Social Change at the University of Johannesburg and a leading expert on digital colonialism, and here presents a new framework for the digital society. Merging the science of degrowth with a global analysis of the high-tech economy, he argues that digital capitalism and colonialism must be abolished quickly.

In Digital Degrowth, Kwet maps out a path to a people's tech future. He calls for direct action against Silicon Valley, US imperialism and power elites everywhere in order to realise a radically egalitarian digital society that fosters equality in harmony with nature.

This volume is focused on the emerging concept of Collaborative Innovation Networks (COINs). COINs are at the core of collaborative knowledge networks, distributed communities taking advantage of the wide connectivity and the support of communication technologies, spanning beyond the organizational perimeter of companies on a global scale. It includes the refereed conference papers from the 6th International Conference on COINs, June 8-11, 2016, in Rome, Italy. It includes papers for both application areas of COINs, (1) optimizing organizational creativity and performance, and (2) discovering and predicting new trends by identifying COINs on the Web through online social media analysis. Papers at COINs16 combine a wide range of interdisciplinary fields such as social network analysis, group dynamics, design and visualization, information systems and the psychology and sociality of collaboration, and intercultural analysis through the lens of online social media. They will cover most recent advances in areas from leadership and collaboration, trend prediction and data mining, to social competence and Internet communication.

This book collects selected papers from the 6th Conference on Signal and Information Processing, Networking and Computers, held in Guiyang, China, on August 13 - 16, 2019. Focusing on the latest advances in information theory, communication systems, computer science, aerospace technologies, big data and other related technologies, it offers a valuable resource for researchers and industrial practitioners alike.

This book presents the design of delay-efficient packet schedulers for heterogeneous M2M uplink traffic classified into several classes, based on packet delay requirements, payload size, arrival process, etc. Specifically, the authors use tools from queuing theory to determine the delay-optimal scheduling policy. The proposed packet schedulers are designed for a generic M2M architecture and thus equally applicable to any M2M application. Additionally, due to their low implementation complexity and excellent delay-performance, they authors show how they are also well-suited for practical M2M systems. The book pertains primarily to real-time process scheduler experts in industry/academia and graduate students whose research deals with designing Quality-of-Service-aware packet schedulers for M2M packet schedulers over existing and future cellular infrastructure. Presents queuing theoretic analysis and optimization techniques used to design proposed packet scheduling strategies; Provides utility functions to precisely model diverse delay requirements, which lends itself to formulation of utility-maximization problems for determining the delay- or utility-optimal packet scheduler; Includes detail on low implementation complexity of the proposed scheduler by using iterative and distributed optimization techniques.

This book contributes a basic framework for and specific insights into interdisciplinary connections between production, logistics, and traffic subsystems. The book is divided into two parts, the first of which presents an overview of interdisciplinarity in value-added networks and freight traffic. This includes an introduction to the topic and a description of an integrated framework of production, logistics, and traffic. Furthermore, it describes the barriers and challenges of interdisciplinary decision-making and project management. In turn, the second part presents domain-specific perspectives on interdisciplinary decision support, exploring domain-specific challenges of interdisciplinary interfaces and requirements for management methods and instruments from the standpoint of production management, logistics management, traffic management, and information technologies.

Intelligent Computing for Interactive System Design provides a comprehensive resource on what has become the dominant paradigm in designing novel interaction methods, involving gestures, speech, text, touch and brain-controlled interaction, embedded in innovative and emerging human-computer interfaces. These interfaces support ubiquitous interaction with applications and services running on smartphones, wearables, in-vehicle systems, virtual and augmented reality, robotic systems, the Internet of Things (IoT), and many other domains that are now highly competitive, both in commercial and in research contexts. This book presents the crucial theoretical foundations needed by any student, researcher, or practitioner working on novel interface design, with chapters on statistical methods, digital signal processing (DSP), and machine learning (ML). These foundations are followed by chapters that discuss case studies on smart cities, brain-computer interfaces, probabilistic mobile text entry, secure gestures, personal context from mobile phones, adaptive touch interfaces, and automotive user interfaces. The case studies chapters also highlight an in-depth look at the practical application of DSP and ML methods used for processing of touch, gesture, biometric, or embedded sensor inputs. A common theme throughout the case studies is ubiquitous support for humans in their daily professional or personal activities. In addition, the book provides walk-through examples of different DSP and ML techniques and their use in interactive systems. Common terms are defined, and information on practical resources is provided (e.g., software tools, data resources) for hands-on project work to develop and evaluate multimodal and multi-sensor systems. In a series of in-chapter commentary boxes, an expert on the legal and ethical issues explores the emergent deep concerns of the professional community, on how DSP and ML should be adopted and used in socially appropriate ways, to most effectively advance human performance during ubiquitous interaction with omnipresent computers. This carefully edited collection is written by international experts and pioneers in the fields of DSP and ML. It provides a textbook for students and a reference and technology roadmap for developers and professionals working on interaction design on emerging platforms.