This book discusses the design and implementation of, as well as experimentation on, an open cross-layer framework and associated methodology to provide voluntary interoperability among heterogeneous Internet of Things (IoT) platforms. It allows readers to effectively and efficiently develop smart IoT applications for various heterogeneous IoT platforms, spanning single and/or multiple application domains. To do so, it provides an interoperable framework architecture for the seamless integration of different IoT architectures present in different application domains. In this regard, interoperability is pursued at various levels: device, network, middleware, services and data.

This book presents selected research papers from CISC'17, held in MudanJiang, China. The topics covered include Multi-agent system, Evolutionary Computation, Artificial Intelligence, Complex systems, Computation intelligence and soft computing, Intelligent control, Advanced control technology, Robotics and applications, Intelligent information processing, Iterative learning control, Machine Learning, and etc. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.

This proceedings book presents selected peer-reviewed papers from the 9th International Workshop on 'Service Oriented, Holonic and Multi-agent Manufacturing Systems for the Industry of the Future' organized by Universitat Politecnica de Valencia, Spain, and held on October 3-4, 2019. The SOHOMA 2019 Workshop aimed to foster innovation in the digital transformation of manufacturing and logistics by promoting new concepts and methods and solutions through service orientation in holonic and agent-based control with distributed intelligence. The book provides insights into the theme of the SOHOMA'19 Workshop - 'Smart anything everywhere - the vertical and horizontal manufacturing integration, ' addressing 'Industry of the Future' (IoF), a term used to describe the 4th industrial revolution initiated by a new generation of adaptive, fully connected, analytical and highly efficient robotized manufacturing systems. This global IoF model describes a new stage of manufacturing, that is fully automatized and uses advanced information, communication and control technologies such as industrial IoT, cyber-physical production systems, cloud manufacturing, resource virtualization, product intelligence, and digital twin, edge and fog computing. It presents the IoF interconnection of distributed manufacturing entities using a 'system-of-systems' approach, discussing new types of highly interconnected and self-organizing production resources in the entire value chain; and new types of intelligent decision-making support based on from real-time production data collected from resources, products and machine learning processing. This book is intended for researchers and engineers working in the manufacturing value chain, and specialists developing computer-based control and robotics solutions for the 'Industry of the Future'. It is also a valuable resource for master's and Ph.D. students in engineering sciences programs.

Economists are increasingly using computer simulations to understand the implications of their theoretical models and to make policy recommendations. New model solution techniques are required to deal with the increasingly important role of dynamics and uncertainty in macroeconomics. This book consists of articles by leading contributors in the field showing how to use these techniques in the context of standard macroeconomic models.

This book provides insights into smart ways of computer log data analysis, with the goal of spotting adversarial actions. It is organized into 3 major parts with a total of 8 chapters that include a detailed view on existing solutions, as well as novel techniques that go far beyond state of the art. The first part of this book motivates the entire topic and highlights major challenges, trends and design criteria for log data analysis approaches, and further surveys and compares the state of the art. The second part of this book introduces concepts that apply character-based, rather than token-based, approaches and thus work on a more fine-grained level. Furthermore, these solutions were designed for "online use", not only forensic analysis, but also process new log lines as they arrive in an efficient single pass manner. An advanced method for time series analysis aims at detecting changes in the overall behavior profile of an observed system and spotting trends and periodicities through log analysis. The third part of this book introduces the design of the AMiner, which is an advanced open source component for log data anomaly mining. The AMiner comes with several detectors to spot new events, new parameters, new correlations, new values and unknown value combinations and can run as stand-alone solution or as sensor with connection to a SIEM solution. More advanced detectors help to determines the characteristics of variable parts of log lines, specifically the properties of numerical and categorical fields. Detailed examples throughout this book allow the reader to better understand and apply the introduced techniques with open source software. Step-by-step instructions help to get familiar with the concepts and to better comprehend their inner mechanisms. A log test data set is available as free download and enables the reader to get the system up and running in no time. This book is designed for researchers working in the field of cyber security, and specifically system monitoring, anomaly detection and intrusion detection. The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, and information systems. Forward-thinking practitioners, who would benefit from becoming familiar with the advanced anomaly detection methods, will also be interested in this book.

Research on ontology is becoming increasingly widespread in the computer science community. While this term has been rather confined to the philosophical sphere in the past, it is now gaining a specific role in areas such as Artificial Intelligence, Computational Linguistics, and Databases. Its importance has been recognized in fields as diverse as knowledge engineering, knowledge representation, qualitative modeling, language engineering, database design, information integration, object-oriented analysis, information retrieval and extraction, knowledge management and organization, agent-based systems design. Current applications areas are disparate, including enterprise integration, natural language translation, medicine, mechanical engineering, electronic commerce, geographic information systems, legal information systems, and biological information systems. Various workshops addressing the engineering aspects of ontology have been held in the recent years. However, ontology by 'its very nature' ought to be a unifying discipline. Insights in this field have potential impact on the whole area of information systems (taking this term in its broadest sense), as testified by the interest recently shown by international standards organizations. In order to provide a solid general foundation for this work, it is therefore important to focus on the common scientific principles and open problems arising from current tools, methodologies, and applications of ontology.

This book features a collection of high-quality research papers presented at the International Conference on Tourism, Technology & Systems (ICOTTS 2020), held at the University of Cartagena, in Cartagena de Indias, Colombia, from 29th to 31st October 2020. The book is divided into two volumes, and it covers the areas of technology in tourism and the tourist experience, generations and technology in tourism, digital marketing applied to tourism and travel, mobile technologies applied to sustainable tourism, information technologies in tourism, digital transformation of tourism business, e-tourism and tourism 2.0, big data and management for travel and tourism, geotagging and tourist mobility, smart destinations, robotics in tourism, and information systems and technologies.

Whether searching, shopping, or socializing, Web users leave behind a great deal of data revealing their information needs, mindset, and approaches used, creating vast opportunities for Web service providers as well as a host of security and privacy concerns for consumers. The Handbook of Research on Web Log Analysis reflects on the multifaceted themes of Web use and presents various approaches to log analysis. This expansive collection reviews the history of Web log analysis and examines new trends including the issues of privacy, social interaction and community building. Over XX research contributions from XX international experts comprehensively cover the latest user-behavior analytic and log analysis methodologies, and consider new research directions and novel applications. An essential holding for library reference collections, this Handbook of Research will benefit academics, researchers, and students in a variety of fields, as well as technology professionals interested in the opportunities and challenges presented by the massive collection of Web usage data.

This book presents the breakthrough and cutting-edge progress for collaborative perception and mapping by proposing a novel framework of multimodal perception-relative localization-collaborative mapping for collaborative robot systems. The organization of the book allows the readers to analyze, model and design collaborative perception technology for autonomous robots. It presents the basic foundation in the field of collaborative robot systems and the fundamental theory and technical guidelines for collaborative perception and mapping. The book significantly promotes the development of autonomous systems from individual intelligence to collaborative intelligence by providing extensive simulations and real experiments results in the different chapters. This book caters to engineers, graduate students and researchers in the fields of autonomous systems, robotics, computer vision and collaborative perception.

This book presents a range of current research topics in biological network modeling, as well as its application in studies on human hosts, pathogens, and diseases. Systems biology is a rapidly expanding field that involves the study of biological systems through the mathematical modeling and analysis of large volumes of biological data. Gathering contributions from renowned experts in the field, some of the topics discussed in depth here include networks in systems biology, the computational modeling of multidrug-resistant bacteria, and systems biology of cancer. Given its scope, the book is intended for researchers, advanced students, and practitioners of systems biology. The chapters are research-oriented, and present some of the latest findings on their respective topics.

This monograph presents new theories and methods for fixed-time cooperative control of multi-agent systems. Fundamental concepts of fixed-time stability and stabilization are introduced with insightful understanding. This book presents solutions for several problems of fixed-time cooperative control using systematic design methods. The book compares fixed-time cooperative control with asymptotic cooperative control, demonstrating how the former can achieve better closed-loop performance and disturbance rejection properties. It also discusses the differences from finite-time control, and shows how fixed-time cooperative control can produce the faster rate of convergence and provide an explicit estimate of the settling time independent of initial conditions. This monograph presents multiple applications of fixed-time control schemes, including to distributed optimization of multi-agent systems, making it useful to students, researchers and engineers alike.

The book introduces readers to some of the latest advances in and approaches to decision-making methods based on thermodynamic characters and hesitant fuzzy linguistic preference relations. By investigating the decision-making methods with thermodynamic parameters based on different information representatives, the book offers readers a novel perspective for solving problems under uncertainty. By exploring the consistency and consensus of hesitant fuzzy linguistic preference relations, the book gives readers efficient ways for preference analysis under uncertainty, chiefly intended for researchers and practitioners working in operations research, multi-attribute decision making, preference analysis, etc. The book can also be used as supplementary material for postgraduate and senior-year undergraduate students of the relevant professional institutions.

This book provides both a broad overview of the forecasting process, covering technological and human aspects alike, and deep insights into algorithms and platform functionalities in the IBP toolbox required to maximize forecast accuracy. Rich in technical and business explanations, it addresses short-, medium- and long-term forecasting processes using functionalities available in demand planning and demand sensing. There are also several theoretical concepts underpinning the algorithms discussed; these are explained with numerical examples to help demystify the IBP forecasting toolbox. Beyond standard procedures, the book also discusses custom approaches (e.g. new segmentation criteria, new outlier detection and correction methods) and new methods (e.g. the use of Markov chains for forecasting sporadic demands), etc. It subsequently benchmarks common practices using these innovative approaches and discusses the results. As measurement is an important precondition for improvement, an entire chapter is devoted to discussing process improvement and value using the Six Sigma methodology. In closing, the book provides several useful tips and tricks that should come in handy during project implementation.

To sustain and stay at the top of the market and give absolute comfort to the consumers, industries are using different strategies and technologies. Natural language processing (NLP) is a technology widely penetrating the market, irrespective of the industry and domains. It is extensively applied in businesses today, and it is the buzzword in every engineer's life. NLP can be implemented in all those areas where artificial intelligence is applicable either by simplifying the communication process or by refining and analyzing information. Neural machine translation has improved the imitation of professional translations over the years. When applied in neural machine translation, NLP helps educate neural machine networks. This can be used by industries to translate low-impact content including emails, regulatory texts, etc. Such machine translation tools speed up communication with partners while enriching other business interactions. Deep Natural Language Processing and AI Applications for Industry 5.0 provides innovative research on the latest findings, ideas, and applications in fields of interest that fall under the scope of NLP including computational linguistics, deep NLP, web analysis, sentiments analysis for business, and industry perspective. This book covers a wide range of topics such as deep learning, deepfakes, text mining, blockchain technology, and more, making it a crucial text for anyone interested in NLP and artificial intelligence, including academicians, researchers, professionals, industry experts, business analysts, data scientists, data analysts, healthcare system designers, intelligent system designers, practitioners, and students.

This book presents recent methodological, technological, and experimental developments concerning human-friendly robots and their introduction into everyday life. The book contains a selection of 10 papers presented at the 13th edition of the International Workshop on Human-Friendly Robotics (HFR). The International Workshop on Human-Friendly Robotics (HFR) is an annual meeting that brings together academic scientists, researchers, and research scholars to present their latest, original findings on all aspects concerning human-friendly robotics where safe and dependable machines operate in close proximity to humans or directly interact with them in a wide range of contexts. The 13th edition was organized by the University of Innsbruck and took place in Innsbruck, Austria. The book is primarily intended for robotics researchers and postgraduates which are doing or willing to do research in fields related to human-friendly robotics, including human-robot interaction, robot control, robot learning, and intuitive interfaces. .

PRO TOOLS 101 OFFICIAL COURSEWARE takes a comprehensive approach to learning the fundamentals of Pro Tools systems. Now updated for Pro Tools 9 software, this new edition from the definitive authority on Pro Tools covers everything you need to know to complete a Pro Tools project. Learn to build sessions that include multitrack recordings of live instruments, MIDI sequences, software synthesizers, and virtual instruments. Through hands-on tutorials, develop essential techniques for recording, editing, and mixing. The included DVD-ROM offers tutorial files and videos, additional documentation, and Pro Tools sessions to accompany the projects in the text. Developed as the foundation course of the official Avid Pro Tools Certification program, the guide can be used to learn on your own or to pursue formal Pro Tools certification through a an Avid Authorized Training Partner. Join the ranks of audio professionals around the world as you unleash the creative power of your Pro Tools system.

This unique volume reviews the latest advances in domain adaptation in the training of machine learning algorithms for visual understanding, offering valuable insights from an international selection of experts in the field. The text presents a diverse selection of novel techniques, covering applications of object recognition, face recognition, and action and event recognition. Topics and features: reviews the domain adaptation-based machine learning algorithms available for visual understanding, and provides a deep metric learning approach; introduces a novel unsupervised method for image-to-image translation, and a video segment retrieval model that utilizes ensemble learning; proposes a unique way to determine which dataset is most useful in the base training, in order to improve the transferability of deep neural networks; describes a quantitative method for estimating the discrepancy between the source and target data to enhance image classification performance; presents a technique for multi-modal fusion that enhances facial action recognition, and a framework for intuition learning in domain adaptation; examines an original interpolation-based approach to address the issue of tracking model degradation in correlation filter-based methods. This authoritative work will serve as an invaluable reference for researchers and practitioners interested in machine learning-based visual recognition and understanding.

It seems that only a short time ago, numerous academics and practitioners in the field were somewhat blinded by the successes of the dot-com developments in the private sector, and some of them enthusiastically claimed that public administration was to be revolutionized. But that did not happen, and also the dot-com soap bubble burst. This suggests that there is much yet to be learned about innovation in public administration, especially about innovations at the cornerstones of technological and institutional transformations. New and more fully developed formulations of theory into practice are needed. The goal of the editors of this book is to contribute to some aspects of the understanding of e-government. In order to understand electronic government, one has to scrutinize the various environments and contexts in which e-government is developed and implemented. As such, it builds upon the biological and environmental lines of reasoning that have been suggested by authors like Bonnie Nardi and Vicky O'Day, and Thomas Davenport and Laurence Prusak.

With the diversification of Internet services and the increase in mobile users, efficient management of network resources has become an extremely important issue in the field of wireless communication networks (WCNs). Adaptive resource management is an effective tool for improving the economic efficiency of WCN systems as well as network design and construction, especially in view of the surge in mobile device demands. This book presents modelling methods based on queueing theory and Markov processes for a wide variety of WCN systems, as well as precise and approximate analytical solution methods for the numerical evaluation of the system performance. This is the first book to provide an overview of the numerical analyses that can be gleaned by applying queueing theory, traffic theory and other analytical methods to various WCN systems. It also discusses the recent advances in the resource management of WCNs, such as broadband wireless access networks, cognitive radio networks, and green cloud computing. It assumes a basic understanding of computer networks and queueing theory, and familiarity with stochastic processes is also recommended. The analysis methods presented in this book are useful for first-year-graduate or senior computer science and communication engineering students. Providing information on network design and management, performance evaluation, queueing theory, game theory, intelligent optimization, and operations research for researchers and engineers, the book is also a valuable reference resource for students, analysts, managers and anyone in the industry interested in WCN system modelling, performance analysis and numerical evaluation.

This book conceptualises and develops crowdsourcing as an organisational business process. It argues that although for many organisations crowdsourcing still implies an immature one-off endeavour, when developed to a more repeatable business process it can harness innovation and agility. The book offers a process model to guide organisations towards the establishment of business process crowdsourcing (BPC), and empirically showcases and evaluates the model using two current major crowdsourcing projects. In order to consolidate the domain knowledge, the BPC model is turned into a heavyweight ontology capturing the concepts, hierarchical relationships and decision-making relationships necessary to establish crowdsourcing as a business process in an organisation. Lastly, based on the ontology it presents a decision tool that provides advice on making informed decisions about the performance of business process crowdsourcing activities.

The ability to communicate with anyone at anytime, anywhere, necessitates a need to provide reliable, resilient, and sustainable applications to support the evolving uses of mobile technologies. Movement-Aware Applications for Sustainable Mobility: Technologies and Approaches focuses on the use of location sensing technology and its wider applicability in supporting sustainable mobility, and presents current research on developing innovative approaches for gathering, representing, storing and analyzing movement data sets being generated from location sensing technology. Offering a unique opportunity for learning about how different techniques are being used to develop new movement-aware applications, this reference work gives students, researchers and practitioners the opportunity to acquire new concepts in the production, awareness and use of sensors, data, and information products for supporting sustainable mobility.

This book describes the recent innovation of deep in-memory architectures for realizing AI systems that operate at the edge of energy-latency-accuracy trade-offs. From first principles to lab prototypes, this book provides a comprehensive view of this emerging topic for both the practicing engineer in industry and the researcher in academia. The book is a journey into the exciting world of AI systems in hardware.

This book is related to the educational networking (EN) domain, an incipient but disrupting trend engaged in extending and improving formal and informal academic practices by means of the support given by online social networks (OSNs) and Web 2.0 technologies. With the aim of contributing to spread the knowledge and development of the arena, this volume introduces ten recent works, whose content meets the quality criteria of formal scientific labor that is worthy to be published according to following five categories: * Reviews: gather three overviews that focus on K-12 EN practice, mixed methods approaches using social network analysis for learning and education, and a broad landscape of the recent accomplished labor. * Conceptual: presents a work where a theoretical framework is proposed to overcome barriers that constrain the use of OSNs for educational purposes by means of a Platform Adoption Model. * Projects: inform a couple of initiatives, where one fosters groups and networks for teachers involved in distance education, and the other encourages students the author academic videos to improve motivation and engagement. * Approaches: offer three experiences related to: Wiki and Blog usage for assessment affairs, application of a method that encourages OSNs users to actively post and repost valuable information for the learning community, and the recreation of learning spaces in context-aware to boost EN. * Study: applies an own method to ranking Mexican universities based on maximal clique, giving as a result a series of complex visual networks that characterize the tides among diverse features that describe academic institutions practice. In resume, this volume offers a fresh reference of an emergent field that contributes to spreading and enhancing the provision of education in classrooms and online settings through social constructivism and collaboration policy. Thus, it is expected the published content encourages researchers, practitioners, professors, and postgraduate students to consider their future contribution to extent the scope and impact of EN in formal and informal teaching and learning endeavors.

Recent advancements in technology have influenced major change within many industries. Because of such advancements, businesses and organizations are adapting to a more technology based work environment in order achieve a higher rate of production, output, and accuracy. Methodological Advancements in Intelligent Information Technologies: Evolutionary Trends brings together research from international authors detailing developments in intelligent information technologies and their impact on organizational environments. This esteemed reference publication covers topics on agent-based approaches to process management, semantic Web services, data mining techniques, engineering software technologies, and scalable and adaptive Web search engines, in order to provide current research for practitioners, educators, and students interested in the implementation of innovative technologies in a variety of work environments.