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This book illustrates the benefits to be gained from digitally networked communication for health, education and transitioning economies in developing nations (Sierra Leone and Papua New Guinea) and developed nations. Growing powers of e-citizenship can help build sustainable futures. This small volume provides a collection of examples and ideas from which the authors hope will help build a wider resource. Understanding how to link everyday lives with global networks in the digital world in ways that add benefit for the world’s people, and the health of the planet, is an ongoing project. IYGU recognises the integral roles of networking and communication systems, as well as interactions between people, near and far, as fundamental for building better futures. The global penetration of digital devices means everyday life, present and future, is inextricably linked with information technologies.

Social sciences. --- Computer organization. --- Electrical engineering. --- Sustainable development. --- Communication. --- Social Sciences. --- Communication Studies. --- Sustainable Development. --- Communications Engineering, Networks. --- Computer Systems Organization and Communication Networks. --- Communication, Primitive --- Mass communication --- Sociology --- Development, Sustainable --- Ecologically sustainable development --- Economic development, Sustainable --- Economic sustainability --- ESD (Ecologically sustainable development) --- Smart growth --- Sustainable development --- Sustainable economic development --- Economic development --- Electric engineering --- Engineering --- Organization, Computer --- Electronic digital computers --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Environmental aspects --- Telecommunication. --- Computer network architectures. --- Architectures, Computer network --- Network architectures, Computer --- Computer architecture --- Electric communication --- Telecom --- Telecommunication industry --- Telecommunications --- Communication --- Information theory --- Telecommuting --- Communication Studies --- Sustainable Development --- Communications Engineering, Networks --- Computer Systems Organization and Communication Networks

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This open access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments. The Editors Prof. Dr.-Ing. Jürgen Beyerer is Professor at the Department for Interactive Real-Time Systems at the Karlsruhe Institute of Technology. In addition he manages the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB. Dr. Alexander Maier is head of group Machine Learning at Fraunhofer IOSB-INA. His focus is on the development of algorithms for big data applications in Cyber-Physical Systems (diagnostics, optimization, predictive maintenance) and the transfer of research results to industry. Prof. Oliver Niggemann got his doctorate in 2001 at the University of Paderborn with the topic "Visual Data Mining of Graph-Based Data". He then worked for almost 8 years in leading positions in the industry. From 2008-2019 he held a professorship at the Institute for Industrial Information Technologies (inIT) in Lemgo/Germany. Until 2019 Prof. Niggemann was also deputy head of the Fraunhofer IOSB-INA, which works in industrial automation. On April 1, 2019 Prof. Niggemann took over the university professorship "Computer Science in Mechanical Engineering" at the Helmut-Schmidt-University in Hamburg / Germany. There he does research at the Institute for Automation Technology IfA in the field of artificial intelligence and machine learning for cyber-physical systems.

Computer engineering. --- Internet of things. --- Embedded computer systems. --- Electrical engineering. --- Computer organization. --- Cyber-physical systems, IoT. --- Communications Engineering, Networks. --- Computer Systems Organization and Communication Networks. --- Organization, Computer --- Electronic digital computers --- Electric engineering --- Engineering --- Embedded systems (Computer systems) --- Computer systems --- Architecture Analysis and Design Language --- IoT (Computer networks) --- Things, Internet of --- Computer networks --- Embedded Internet devices --- Machine-to-machine communications --- Computers --- Design and construction --- Machine learning --- Cyber-physical systems, IoT --- Communications Engineering, Networks --- Computer Systems Organization and Communication Networks --- Cyber-Physical Systems --- Computer Engineering and Networks --- Machine Learning --- Artificial Intelligence --- Cognitive Robotics --- Internet of Things --- Computational intelligence --- Computer-based algorithms --- Smart grid --- Open Access --- Industry 4.0 --- Electrical engineering --- Cybernetics & systems theory --- Communications engineering / telecommunications --- Computer networking & communications

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This Open Access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, October 23-24, 2018. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments. The Editors Prof. Dr.-Ing. Jürgen Beyerer is Professor at the Department for Interactive Real-Time Systems at the Karlsruhe Institute of Technology. In addition he manages the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB. Dr. ChristianKühnert is a senior researcher at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB. His research interests are in the field of machine-learning, data-fusion and data-driven condition monitoring. Prof. Dr. Oliver Niggemann is Professor for Artificial Intelligence in Automation. His research interests are in the fields of machine learning and data analysis for Cyber-Physical Systems and in the fields of planning and diagnosis of distributed systems. He is a board member of the research institute inIT and deputy director at the Fraunhofer Application Center Industrial Automation INA located in Lemgo.

Engineering. --- Computer network architectures. --- Telecommunication. --- Data mining. --- Computational Intelligence. --- Computer Systems Organization and Communication Networks. --- Communications Engineering, Networks. --- Data Mining and Knowledge Discovery. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Telecommunications --- Communication --- Information theory --- Telecommuting --- Architectures, Computer network --- Network architectures, Computer --- Computer architecture --- Construction --- Industrial arts --- Technology --- Computational intelligence. --- Computer organization. --- Electrical engineering. --- Electric engineering --- Engineering --- Organization, Computer --- Electronic digital computers --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Computational intelligence --- Computer organization --- Electrical engineering --- Data mining --- Computer engineering. --- Computer networks. --- Computer Engineering and Networks.

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This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation.

Database management. --- Data mining. --- Computers. --- Machine learning. --- Computer organization. --- Database Management. --- Data Mining and Knowledge Discovery. --- Computing Milieux. --- Machine Learning. --- Computer Systems Organization and Communication Networks. --- Organization, Computer --- Electronic digital computers --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Electronic data processing --- Learning, Machine --- Artificial intelligence --- Machine theory --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Database Management --- Data Mining and Knowledge Discovery --- Computing Milieux --- Machine Learning --- Computer Systems Organization and Communication Networks --- open access --- data mining --- learning systems --- classification --- clustering --- semantics --- learning algorithms --- supervised learning --- association rules --- social networks --- graphic methods --- neural networks --- artificial intelligence --- computer vision --- correlation analysis --- databases --- education --- engineering --- graph theory --- image analysis --- Databases --- Database programming --- Data mining --- Expert systems / knowledge-based systems --- Information technology: general issues --- Machine learning --- Computer networking & communications

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The open access two-volume set LNCS 12224 and 12225 constitutes the refereed proceedings of the 32st International Conference on Computer Aided Verification, CAV 2020, held in Los Angeles, CA, USA, in July 2020.* The 43 full papers presented together with 18 tool papers and 4 case studies, were carefully reviewed and selected from 240 submissions. The papers were organized in the following topical sections: Part I: AI verification; blockchain and Security; Concurrency; hardware verification and decision procedures; and hybrid and dynamic systems. Part II: model checking; software verification; stochastic systems; and synthesis. *The conference was held virtually due to the COVID-19 pandemic.

Software engineering. --- Computers. --- Artificial intelligence. --- Computer organization. --- Computer hardware. --- Computer simulation. --- Software Engineering. --- Theory of Computation. --- Artificial Intelligence. --- Computer Systems Organization and Communication Networks. --- Computer Hardware. --- Simulation and Modeling. --- Computer modeling --- Computer models --- Modeling, Computer --- Models, Computer --- Simulation, Computer --- Electromechanical analogies --- Mathematical models --- Simulation methods --- Model-integrated computing --- Organization, Computer --- Electronic digital computers --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Fifth generation computers --- Neural computers --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Computer software engineering --- Engineering --- Software Engineering --- Theory of Computation --- Artificial Intelligence --- Computer Systems Organization and Communication Networks --- Computer Hardware --- Simulation and Modeling --- Computer Engineering and Networks --- Computer Science --- architecture verification and validation --- artificial intelligence --- automata theory --- computer systems --- correlation analysis --- distributed computer systems --- embedded systems --- formal languages --- formal logic --- linguistics --- model checking --- programming languages --- semantics --- software architecture --- software design --- software quality --- verification and validation --- Open Access --- Computer science --- Mathematical theory of computation --- Artificial intelligence --- Computer networking & communications --- Computer modelling & simulation --- Computer science. --- Computer engineering. --- Computer networks. --- Computer Engineering and Networks. --- Computer Science. --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Computers --- Informatics --- Science --- Distributed processing --- Design and construction