This book presents the state-of-the-arts application of digital watermarking in audio, speech, image, video, 3D mesh graph, text, software, natural language, ontology, network stream, relational database, XML, and hardware IPs. It also presents new and recent algorithms in digital watermarking for copyright protection and discusses future trends in the field. Today, the illegal manipulation of genuine digital objects and products represents a considerable problem in the digital world. Offering an effective solution, digital watermarking can be applied to protect intellectual property, as well as fingerprinting, enhance the security and proof-of-authentication through unsecured channels.

The primary aim of this volume is to provide researchers and engineers from both academia and industry with up-to-date coverage of recent advances in the fields of robotic welding, intelligent systems and automation. It gathers selected papers from the 2018 International Conference on Robotic Welding, Intelligence and Automation (RWIA 2018), held Oct 20-22, 2018 in Guangzhou, China. The contributions reveal how intelligentized welding manufacturing (IWM) is becoming an inescapable trend, just as intelligentized robotic welding is becoming a key technology. The volume is divided into four main parts: Intelligent Techniques for Robotic Welding, Sensing in Arc Welding Processing, Modeling and Intelligent Control of Welding Processing, and Intelligent Control and its Applications in Engineering.

The topic of this monograph falls within the, so-called, biologically motivated computing paradigm, in which biology provides the source of models and inspiration towards the development of computational intelligence and machine learning systems. Specifically, artificial immune systems are presented as a valid metaphor towards the creation of abstract and high level representations of biological components or functions that lay the foundations for an alternative machine learning paradigm. Therefore, focus is given on addressing the primary problems of Pattern Recognition by developing Artificial Immune System-based machine learning algorithms for the problems of Clustering, Classification and One-Class Classification. Pattern Classification, in particular, is studied within the context of the Class Imbalance Problem. The main source of inspiration stems from the fact that the Adaptive Immune System constitutes one of the most sophisticated biological systems that is exceptionally evolved in order to continuously address an extremely unbalanced pattern classification problem, namely, the self / non-self discrimination process. The experimental results presented in this monograph involve a wide range of degenerate binary classification problems where the minority class of interest is to be recognized against the vast volume of the majority class of negative patterns. In this context, Artificial Immune Systems are utilized for the development of personalized software as the core mechanism behind the implementation of Recommender Systems. The book will be useful to researchers, practitioners and graduate students dealing with Pattern Recognition and Machine Learning and their applications in Personalized Software and Recommender Systems. It is intended for both the expert/researcher in these fields, as well as for the general reader in the field of Computational Intelligence and, more generally, Computer Science who wishes to learn more about the field of Intelligent Computing Systems and its applications. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.

The collected works of Turing, including a substantial amount of unpublished material, will comprise four volumes: Mechanical Intelligence, Pure Mathematics, Morphogenesis and Mathematical Logic. Alan Mathison Turing (1912-1954) was a brilliant man who made major contributions in several areas of science. Today his name is mentioned frequently in philosophical discussions about the nature of Artificial Intelligence. Actually, he was a pioneer researcher in computer architecture and software engineering; his work in pure mathematics and mathematical logic extended considerably further and his last work, on morphogenesis in plants, is also acknowledged as being of the greatest originality and of permanent importance. He was one of the leading figures in Twentieth-century science, a fact which would have been known to the general public sooner but for the British Official Secrets Act, which prevented discussion of his wartime work. What is maybe surprising about these papers is that although they were written decades ago, they address major issues which concern researchers today.

This unique book succinctly summarizes the need to measure how ontologies (one of the building blocks of the Semantic Web) are currently being utilized, providing insights for various stakeholders. Where possible it improves and reuses terms in existing vocabularies/ontologies, as recommended by the Linked Data community. Recent advances in the Semantic Web have led to a proliferation of Resource Description Framework (RDF) data, which employ ontologies to semantically describe the information on the Web making it equally understandable for both humans and machines. However, to create a network effect, it is important that selective ontologies are used by more data publishers to improve the value of that ontology. For this to happen, it is vital to discover what is being used from an ontology to semantically annotate the information on the Web specific to a given domain. Answers to such basic but crucial questions can only be achieved by ascertaining how ontologies in the current semantic web are being utilized and adopted. The proposed frameworks to obtain such insights are explained with real-world examples to provide a clear and detailed description of ontology usage analysis. Both theoretical and practical, the book is of value to academics and professionals working in industry. Specifically, it is of primary interest to researchers, graduate students and practitioners in the area of the Semantic Web and its various real-world applications.

By presenting the latest advances in fuzzy sets and computing with words from around the globe, this book disseminates recent innovations in advanced intelligent technologies and systems. From intelligent control and intuitionistic fuzzy quantifiers to various data science and industrial applications, it includes a wide range of valuable lessons learned and ideas for future intelligent products and systems.

Intelligent prediction and decision support systems are based on signal processing, computer vision (CV), machine learning (ML), software engineering (SE), knowledge based systems (KBS), data mining, artificial intelligence (AI) and include several systems developed from the study of expert systems (ES), genetic algorithms (GA), artificial neural networks (ANN) and fuzzy-logic systems The use of automatic decision support systems in design and manufacturing industry, healthcare and commercial software development systems has the following benifits: Cost savings in companies, due to employment of expert system technology. Fast decision making, completion of projects in time and development of new products. Improvement in decision making capability and quality. Usage of Knowledge database and Preservation of expertise of individuals Eases complex decision problems. Ex: Diagnosis in Healthcare To address the issues and challenges related to development, implementation and application of automatic and intelligent prediction and decision support systems in domains such as manufacturing, healthcare and software product design, development and optimization, this book aims to collect and publish wide ranges of quality articles such as original research contributions, methodological reviews, survey papers, case studies and/or reports covering intelligent systems, expert prediction systems, evaluation models, decision support systems and Computer Aided Diagnosis (CAD).

This book contains some selected papers from the International Conference on Extreme Learning Machine 2015, which was held in Hangzhou, China, December 15-17, 2015. This conference brought together researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the Extreme Learning Machine (ELM) technique and brain learning. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.

A state-of-the-art guide for the implementation of distributed simulation technology.

The rapid expansion of the Internet and commodity parallel computers has made parallel and distributed simulation (PADS) a hot technology indeed. Applications abound not only in the analysis of complex systems such as transportation or the next-generation Internet, but also in computer-generated virtual worlds for military and professional training, interactive computer games, and the entertainment industry.

In this book, PADS expert Richard M. Fujimoto provides software developers with cutting-edge techniques for speeding up the execution of simulations across multiple processors and dealing with data distribution over wide area networks ,including the Internet. With an emphasis on parallel and distributed discrete event simulation technologies, Dr. Fujimoto compiles and consolidates research results in the field spanning the last twenty years, discussing the use of parallel and distributed computers in both the modeling and analysis of system behavior and the creation of distributed virtual environments.

While other books on PADS concentrate on applications, Parallel and Distributed Simulation Systems clearly shows how to implement the technology. It explains in detail the synchronization algorithms needed to properly realize the simulations, including an in-depth discussion of time warp and advanced optimistic techniques. Finally, the book is richly supplemented with references, tables and illustrations, and examples of contemporary systems such as the Department of Defense's High Level Architecture (HLA), which has become the standard architecture for defense programs in the United States.

While high quality library and information services continue to thrive and strengthen economic and social development, much of the knowledge that exists on user's needs and behaviours is fundamentally based on the results of users in English-speaking, western developed countries. Information Access and Library User Needs in Developing Countries highlights the struggles that developing countries face in terms of information gaps and information-seeking user behaviour. The publication highlights ways in which users in developing countries can benefit from properly implementing LIS services. Researchers, academics, and practitioners interested in the design and delivery of information services will benefit from this collection of research.

Graphic displays such as charts, graphs, diagrams, and maps play in important role today in the design and presentation of instructional materials education. There is also a strong need in scientific, technical and administrative fields to visually present facts, laws, principles etc. The increasing use of computer-based learning environments has also become an important field where the visual presentation of information plays a central role. Despite the importance of graphical displays as a means of communication and the fact that research about learning and cognition has advanced rapidly in the past two decades, the comprehension of graphics is still a rather unexplored area.

The comprehension of graphics is not only a stimulating topic in the fields of science and instructional psychology, but also in related disciplines such as semiotics, and artificial intelligence. Research on the comprehension of graphics complements the scientific investigation of cognitive processes in text comprehension, which has contributed much to our understanding of human cognition and learning. Ultimately, a better understanding of the cognitive processes involved in the comprehension of graphics will have an impact not only on cognitive theory, but also on educational practice.

From the Foreword: "...the presentation of real-time scheduling is probably the best in terms of clarity I have ever read in the professional literature. Easy to understand, which is important for busy professionals keen to acquire (or refresh) new knowledge without being bogged down in a convoluted narrative and an excessive detail overload. The authors managed to largely avoid theoretical-only presentation of the subject, which frequently affects books on operating systems. ... an indispensable [resource] to gain a thorough understanding of the real-time systems from the operating systems perspective, and to stay up to date with the recent trends and actual developments of the open-source real-time operating systems." -Richard Zurawski, ISA Group, San Francisco, California, USA Real-time embedded systems are integral to the global technological and social space, but references still rarely offer professionals the sufficient mix of theory and practical examples required to meet intensive economic, safety, and other demands on system development. Similarly, instructors have lacked a resource to help students fully understand the field. The information was out there, though often at the abstract level, fragmented and scattered throughout literature from different engineering disciplines and computing sciences. Accounting for readers' varying practical needs and experience levels, Real Time Embedded Systems: Open-Source Operating Systems Perspective offers a holistic overview from the operating-systems perspective. It provides a long-awaited reference on real-time operating systems and their almost boundless application potential in the embedded system domain. Balancing the already abundant coverage of operating systems with the largely ignored real-time aspects, or "physicality," the authors analyze several realistic case studies to introduce vital theoretical material. They also discuss popular open-source operating systems-Linux and FreRTOS, in particular-to help embedded-system designers identify the benefits and weaknesses in deciding whether or not to adopt more traditional, less powerful, techniques for a project.

The convergence of Artificial Intelligence (AI) in blockchain creates one of the world's most reliable technology-enabled decision-making systems that is virtually tamper-proof and provides solid insights and decisions. The integration of AI and Blockchain affects many aspects from food supply chain logistics and healthcare record sharing to media royalties and financial security. It is imperative that regulatory standards are emphasized in order to support positive outcomes from the integration of AI in blockchain technology. Regulatory Aspects of Artificial Intelligence on Blockchain provides relevant legal and security frameworks and the latest empirical research findings in blockchain and AI. Through the latest research and standards, the book identifies and offers solutions for overcoming legal consequences that pertain to the application of AI into the blockchain system, especially concerning the usage of smart contracts. The chapters, while investigating the legal and security issues associated with these applications, also include topics such as smart contacts, network vulnerability, cryptocurrency, machine learning, and more. This book is essential for technologists, security analysts, legal specialists, privacy and data security practitioners, IT consultants, standardization professionals, researchers, academicians, and students interested in blockchain and AI from a legal and security viewpoint.

This book gathers the proceedings of the Fourth International Conference on Computational Science and Technology 2017 (ICCST2017), held in Kuala Lumpur, Malaysia, on 29-30 November 2017. These proceedings offer practitioners and researchers the opportunity to present exciting advances in computational techniques and solutions in this area. They also identify emerging issues, help to shape future research directions, and will enable industrial users to apply cutting-edge, large-scale and high-performance computational methods.

Technology has impacted how many teachers develop methods of instruction in their classroom settings. The Continuous Practice Improvement (CPI) professional development program introduces teachers to infusing computers into the curriculum and classroom activities seamlessly. ""Infusing Technology into the Classroom: Continuous Practice Improvement"" retells compelling stories of a successful computer-related professional development program that was implemented into Kindergarten through eighth grade classrooms of a Philadelphia school. Through an analysis of the study, a theoretical model to guide technology infused professional development for teachers is discovered.

In the modern age of the 4th Industrial Revolution, advancements in communication and connectivity are transforming the professional world as new technologies are being embedded into society. These innovations have triggered the development of a digitally driven world where adaptation is necessary. This is no different in the architectural field, where the changing paradigm has opened new methods and advancements that have yet to be researched. Impact of Industry 4.0 on Architecture and Cultural Heritage is a pivotal reference source that provides vital research on the application of new technological tools, such as digital modeling, within architectural design, and improves the understanding of the strategic role of Industry 4.0 as a tool to empower the role of architecture and cultural heritage in society. Moreover, the book provides insights and support concerned with advances in communication and connectivity among digital environments in different types of research and industry communities. While highlighting topics such as semantic processing, crowdsourcing, and interactive environments, this publication is ideally designed for architects, engineers, construction professionals, cultural researchers, academicians, and students.

This book presents the latest research of the field of optimization, modeling and algorithms, discussing the real-world application problems associated with new innovative methodologies. The requirements and demands of problem solving have been increasing exponentially and new computer science and engineering technologies have reduced the scope of data coverage worldwide. The recent advances in information communication technology (ICT) have contributed to reducing the gaps in the coverage of domains around the globe. The book is a valuable reference work for researchers in the fields of computer science and engineering with a particular focus on modeling, simulation and optimization as well as for postgraduates, managers, economists and decision makers

In information technology, unlike many other fields, the need to support the unique perspective of technologically advanced students and deliver technology-rich content presents unique challenges. Today's IT students need the ability to interact with their instructor in near-real time, interact with their peers and project team members, and access and manipulate technology tools in the pursuit of their educational objectives.""Handbook of Distance Learning for Real-Time and Asynchronous Information Technology Education"" delves deep into the construct of real-time, asynchronous education through information technology, pooling experiences from seasoned researchers and educators to detail their past successes and failures, discussing their techniques, hardships, and triumphs in the search for innovative and effective distance learning education for IT programs. This Premier Reference Source answers the increasing demand for a fundamental, decisive source on this cutting-edge issue facing all institutions, covering topics such as asynchronous communication, real-time instruction, multimedia content, content delivery, and distance education technologies.

When researchers in computer-mediated communications discuss digital textuality, they rarely venture beyond the now commonplace notion that computer textuality embodies contemporary post-structuralist theories. Written for students and faculty of contemporary literature and composition theories, this book is the first to move from general to specific considerations. Advancing from general considerations of how computers are changing literacy, Digital Fictions moves on to a specific consideration of how computers are altering one particular set of literature practices: reading and writing fiction. Suffused through the sensibility of a creative writer, this book includes an historical overview of writing stories on computers. In addition, Sloane conducts interviews with the makers of hypertext fictions (including Stuart Moulthrop, Michael Joyce, and Carolyn Guyer) and offers close reading of digital fictions. Making careful analyses of the meaning-making activities of both readers and writers of this emerging genre, this work is embedded in a perspective both feminist and semiotic. Digital Fictions explores and distinguishes among four distinct iterations of text-based digital fictions; text adventures, Carnegie Mellon University Oz Project, hypertext fictions, and MUDs. Ultimately, Sloane revises the rhetorical triangle and proposes a new rhetorical theory, one that attends to the materials, processes, and locations of stories told on-line.

Sequential data from Web server logs, online transaction logs, and performance measurements is collected each day. This sequential data is a valuable source of information, as it allows individuals to search for a particular value or event and also facilitates analysis of the frequency of certain events or sets of related events. Finding patterns in sequences is of utmost importance in many areas of science, engineering, and business scenarios. Pattern Discovery Using Sequence Data Mining: Applications and Studies provides a comprehensive view of sequence mining techniques and presents current research and case studies in pattern discovery in sequential data by researchers and practitioners. This research identifies industry applications introduced by various sequence mining approaches.

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.

Video Data Management and Information Retrieval combines the two important areas of research within computer technology and presents them in comprehensive, easy to understand manner. Video Data Management and Information Retrieval is ideal for graduates and under-graduates, as well as researchers working in either video data management or information retrieval. It takes an in depth look at many relevant topics within both video data management and information retrieval. In addition to dissecting those issues, the book also provides a ""big picture"" view of each topic. This shows the relevance of each issue and how those areas affect every one today.

This volume presents the peer-reviewed proceedings of the international conference Imaging, Vision and Learning Based on Optimization and PDEs (IVLOPDE), held in Bergen, Norway, in August/September 2016. The contributions cover state-of-the-art research on mathematical techniques for image processing, computer vision and machine learning based on optimization and partial differential equations (PDEs). It has become an established paradigm to formulate problems within image processing and computer vision as PDEs, variational problems or finite dimensional optimization problems. This compact yet expressive framework makes it possible to incorporate a range of desired properties of the solutions and to design algorithms based on well-founded mathematical theory. A growing body of research has also approached more general problems within data analysis and machine learning from the same perspective, and demonstrated the advantages over earlier, more established algorithms. This volume will appeal to all mathematicians and computer scientists interested in novel techniques and analytical results for optimization, variational models and PDEs, together with experimental results on applications ranging from early image formation to high-level image and data analysis.