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This book contains the works connected with the key advances in Intelligent Information Technologies for Industry presented in the main track of IITI 2022, the Sixth International Scientific Conference on Intelligent Information Technologies for Industry held on October 31 - November 6, 2022, in Istanbul, Turkey. The works were written by the experts in the field of artificial intelligence including topics such as machine learning, decision making intelligent systems, fuzzy logic, bioinspired systems and Bayesian networks. The following industrial application domains were touched: railway automation, intelligent medical systems, flexible socio-technical systems, navigation systems and energetic systems. The editors believe that this book will be helpful for all scientists and engineers interested in the modern state of applied artificial intelligence.
This book contains the works connected with the key advances in Industrial Artificial Intelligence presented at IITI 2023, the Seventh International Scientific Conference on Intelligent Information Technologies for Industry held on September 25-30, 2023 in St. Petersburg, Russia. The works were written by the experts in the field of applied artificial intelligence including topics such as Machine Learning, Explainable AI, Decision-Making, Fuzzy Logic, Multi-Agent and Bioinspired Systems. The following industrial application domains were touched: railway automation, cyber security, intelligent medical systems, navigation and energetic systems. The editors believe that this book will be helpful for all scientists and engineers interested in the modern state of applied artificial intelligence.
This book contains the works connected with the key advances in Intelligent Information Technologies for Industry presented in the main track of IITI 2022, the Sixth International Scientific Conference on Intelligent Information Technologies for Industry held on October 31 - November 6, 2022, in Istanbul, Turkey. The works were written by the experts in the field of artificial intelligence including topics such as machine learning, decision making intelligent systems, fuzzy logic, bioinspired systems and Bayesian networks. The following industrial application domains were touched: railway automation, intelligent medical systems, flexible socio-technical systems, navigation systems and energetic systems. The editors believe that this book will be helpful for all scientists and engineers interested in the modern state of applied artificial intelligence.
This book’s main goals are to bring together in a concise way all the methodologies, standards and recommendations related to Data, Queries, Links, Semantics, Validation and other issues concerning machine-readable data on the Web, to describe them in detail, to provide examples of their use, and to discuss how they contribute to – and how they have been used thus far on – the “Web of Data”. As the content of the Web becomes increasingly machine readable, increasingly complex tasks can be automated, yielding more and more powerful Web applications that are capable of discovering, cross-referencing, filtering, and organizing data from numerous websites in a matter of seconds. The book is divided into nine chapters, the first of which introduces the topic by discussing the shortcomings of the current Web and illustrating the need for a Web of Data. Next, “Web of Data” provides an overview of the fundamental concepts involved, and discusses some current use-cases on the Web where such concepts are already being employed. “Resource Description Framework (RDF)” describes the graph-structured data model proposed by the Semantic Web community as a common data model for the Web. The chapter on “RDF Schema (RDFS) and Semantics” presents a lightweight ontology language used to define an initial semantics for terms used in RDF graphs. In turn, the chapter “Web Ontology Language (OWL)” elaborates on a more expressive ontology language built upon RDFS that offers much more powerful ontological features. In “SPARQL Query Language” a language for querying and updating RDF graphs is described, with examples of the features it supports, supplemented by a detailed definition of its semantics. “Shape Constraints and Expressions (SHACL/ShEx)” introduces two languages for describing the expected structure of – and expressing constraints on – RDF graphs for the purposes of validation. “Linked Data” discusses the principles and best practices proposed by the Linked Data community for publishing interlinked (RDF) data on the Web, and how these techniques have been adopted. The final chapter highlights open problems and rounds out the coverage with a more general discussion on the future of the Web of Data. The book is intended for students, researchers and advanced practitioners interested in learning more about the Web of Data, and about closely related topics such as the Semantic Web, Knowledge Graphs, Linked Data, Graph Databases, Ontologies, etc. Offering a range of accessible examples and exercises, it can be used as a textbook for students and other newcomers to the field. It can also serve as a reference handbook for researchers and developers, as it offers up-to-date details on key standards (RDF, RDFS, OWL, SPARQL, SHACL, ShEx, RDB2RDF, LDP), along with formal definitions and references to further literature. The associated website webofdatabook.org offers a wealth of complementary material, including solutions to the exercises, slides for classes, raw data for examples, and a section for comments and questions.
This book focuses on the core question of the necessary architectural support provided by hardware to efficiently run virtual machines, and of the corresponding design of the hypervisors that run them. Virtualization is still possible when the instruction set architecture lacks such support, but the hypervisor remains more complex and must rely on additional techniques. Despite the focus on architectural support in current architectures, some historical perspective is necessary to appropriately frame the problem. The first half of the book provides the historical perspective of the theoretical framework developed four decades ago by Popek and Goldberg. It also describes earlier systems that enabled virtualization despite the lack of architectural support in hardware. As is often the case, theory defines a necessary—but not sufficient—set of features, and modern architectures are the result of the combination of the theoretical framework with insights derived from practical systems. The second half of the book describes state-of-the-art support for virtualization in both x86-64 and ARM processors. This book includes an in-depth description of the CPU, memory, and I/O virtualization of these two processor architectures, as well as case studies on the Linux/KVM, VMware, and Xen hypervisors. It concludes with a performance comparison of virtualization on current-generation x86- and ARM-based systems across multiple hypervisors.
This book presents an introduction to the classical theories of continuum mechanics; in particular, to the theories of ideal, compressible, and viscous fluids, and to the linear and nonlinear theories of elasticity. These theories are important, not only because they are applicable to a majority of the problems in continuum mechanics arising in practice, but because they form a solid base upon which one can readily construct more complex theories of material behavior. Further, although attention is limited to the classical theories, the treatment is modern with a major emphasis on foundations and structure
This volume of Advances in Intelligent Systems and Computing highlights key scientific achievements and innovations in all areas of automation, informatization, computer science, and artificial intelligence. It gathers papers presented at the IITI 2017, the Second International Conference on Intelligent Information Technologies for Industry, which was held in Varna, Bulgaria on September 14–16, 2017. The conference was jointly co-organized by Technical University of Varna (Bulgaria), Technical University of Sofia (Bulgaria), VSB Technical University of Ostrava (Czech Republic) and Rostov State Transport University (Russia). The IITI 2017 brought together international researchers and industrial practitioners interested in the development and implementation of modern technologies for automation, informatization, computer science, artificial intelligence, transport and power electrical engineering. In addition to advancing both fundamental research and innovative applications, the conference is intended to establish a new dissemination platform and an international network of researchers in these fields.
This book gathers papers presented in the main track of IITI 2019, the Fourth International Scientific Conference on Intelligent Information Technologies for Industry, held in Ostrava–Prague, Czech Republic on December 2–7, 2019. The conference was jointly organized by Rostov State Transport University (Russia) and VŠB – Technical University of Ostrava (Czech Republic) with the participation of the Russian Association for Artificial Intelligence (RAAI). IITI 2019 was devoted to practical models and industrial applications of intelligent information systems. Though chiefly intended to promote the implementation of advanced information technologies in various industries, topics such as the state of the art in intelligent systems and soft computing were also discussed.
With the rapid evolution of cyberspace, computing, communications and sensing technologies, organizations and individuals rely more and more on new applications such as fog and cloud computing, smart cities, Internet of Things (IoT), collaborative computing, and virtual and mixed reality environments. Maintaining their security, trustworthiness and resilience to cyber-attacks has become crucial which requires innovative and creative cyber security and resiliency solutions. Computing algorithms have been developed to mimic the operation of natural processes, phenomena and organisms such as artificial neural networks, swarm intelligence, deep learning systems, biomimicry, and more. The amazing characteristics of these systems offer a plethora of novel methodologies and opportunities to cope with emerging cyber challenges.