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This book aims to provide a new vision of how algorithms are the core of decision support systems (DSSs), which are increasingly important information systems that help to make decisions related to unstructured and semi-unstructured decision problems that do not have a simple solution from a human point of view. It begins with a discussion of how DSSs will be vital to improving the health of the population. The following article deals with how DSSs can be applied to improve the performance of people doing a specific task, like playing tennis. It continues with a work in which authors apply DSSs to insect pest management, together with an interactive platform for fitting data and carrying out spatial visualization. The next article improves how to reschedule trains whenever disturbances occur, together with an evaluation framework. The final works focus on different relevant areas of DSSs: 1) a comparison of ensemble and dimensionality reduction models based on an entropy criterion; 2) a radar emitter identification method based on semi-supervised and transfer learning; 3) design limitations, errors, and hazards in creating very large-scale DSSs; and 4) efficient rule generation for associative classification. We hope you enjoy all the contents in the book.

History of engineering & technology --- semi-supervised learning --- transfer learning --- radar emitter --- decision support systems --- population health management --- big data --- machine learning --- deep learning --- personalized patient care --- Nonlinear regression --- interactive platform --- component-based approach --- software architecture --- Eclipse-RCP (Rich Client Platform) --- spatial prediction --- rule-based expert systems --- tennis hitting technique --- computer algebra systems --- Groebner bases --- Boolean logic --- data envelopment analysis --- dimensionality reduction --- ensembles --- exhaustive state space search --- entropy --- associative classification --- class association rule --- vertical data representation --- classification --- algorithm evaluation --- parallel algorithms --- multi-objective optimization --- train rescheduling --- very large-scale decision support systems --- very large-scale data and program cores of information systems --- meta-database --- teleological meta-database --- thematic list --- indicators list --- computational methods list --- geographically dispersed systems --- external sources

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This book aims to provide a new vision of how algorithms are the core of decision support systems (DSSs), which are increasingly important information systems that help to make decisions related to unstructured and semi-unstructured decision problems that do not have a simple solution from a human point of view. It begins with a discussion of how DSSs will be vital to improving the health of the population. The following article deals with how DSSs can be applied to improve the performance of people doing a specific task, like playing tennis. It continues with a work in which authors apply DSSs to insect pest management, together with an interactive platform for fitting data and carrying out spatial visualization. The next article improves how to reschedule trains whenever disturbances occur, together with an evaluation framework. The final works focus on different relevant areas of DSSs: 1) a comparison of ensemble and dimensionality reduction models based on an entropy criterion; 2) a radar emitter identification method based on semi-supervised and transfer learning; 3) design limitations, errors, and hazards in creating very large-scale DSSs; and 4) efficient rule generation for associative classification. We hope you enjoy all the contents in the book.

History of engineering & technology --- semi-supervised learning --- transfer learning --- radar emitter --- decision support systems --- population health management --- big data --- machine learning --- deep learning --- personalized patient care --- Nonlinear regression --- interactive platform --- component-based approach --- software architecture --- Eclipse-RCP (Rich Client Platform) --- spatial prediction --- rule-based expert systems --- tennis hitting technique --- computer algebra systems --- Groebner bases --- Boolean logic --- data envelopment analysis --- dimensionality reduction --- ensembles --- exhaustive state space search --- entropy --- associative classification --- class association rule --- vertical data representation --- classification --- algorithm evaluation --- parallel algorithms --- multi-objective optimization --- train rescheduling --- very large-scale decision support systems --- very large-scale data and program cores of information systems --- meta-database --- teleological meta-database --- thematic list --- indicators list --- computational methods list --- geographically dispersed systems --- external sources --- semi-supervised learning --- transfer learning --- radar emitter --- decision support systems --- population health management --- big data --- machine learning --- deep learning --- personalized patient care --- Nonlinear regression --- interactive platform --- component-based approach --- software architecture --- Eclipse-RCP (Rich Client Platform) --- spatial prediction --- rule-based expert systems --- tennis hitting technique --- computer algebra systems --- Groebner bases --- Boolean logic --- data envelopment analysis --- dimensionality reduction --- ensembles --- exhaustive state space search --- entropy --- associative classification --- class association rule --- vertical data representation --- classification --- algorithm evaluation --- parallel algorithms --- multi-objective optimization --- train rescheduling --- very large-scale decision support systems --- very large-scale data and program cores of information systems --- meta-database --- teleological meta-database --- thematic list --- indicators list --- computational methods list --- geographically dispersed systems --- external sources

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This book covers a variety of smart IoT applications for industry and research. For industry, the book is a guide for considering the real-time aspects of automation of application domains. The main topics covered in the industry section include real-time tracking and navigation, smart transport systems and application for GPS domains, modern electric grid control for the electricity industry, IoT prospectives for modern society, IoT for modern medical science, and IoT automation for Industry 4.0. The book then provides a summary of existing IoT research that underlines enabling technologies, such as fog computing, wireless sensor networks, data mining, context awareness, real-time analytics, virtual reality, and cellular communications. The book pertains to researchers, outcome-based academic leaders, as well as industry leaders. Covers real-time problems for industry along with unique research methodologies for furthering the field; Includes authentic research datasets for simulated applications in IoT; Features topics such as IoT for retail and supply chain management, smart health, and smart electricity & energy management.

Economic production --- Telecommunication technology --- Engineering sciences. Technology --- Mass communications --- Programming --- Computer architecture. Operating systems --- Computer. Automation --- innovatiemanagement --- applicatiebeheer --- apps --- technologie --- technologische innovatie --- innovaties --- tekstverwerking --- algoritmen --- computernetwerken --- architectuur (informatica) --- communicatietechnologie

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This book discusses reliability applications for power systems, renewable energy and smart grids and highlights trends in reliable communication, fault-tolerant systems, VLSI system design and embedded systems. Further, it includes chapters on software reliability and other computer engineering and software management-related disciplines, and also examines areas such as big data analytics and ubiquitous computing. Outlining novel, innovative concepts in applied areas of reliability in electrical, electronics and computer engineering disciplines, it is a valuable resource for researchers and practitioners of reliability theory in circuit-based engineering domains.

System safety. --- Operating systems (Computers). --- Systems engineering. --- Quality Control, Reliability, Safety and Risk. --- Performance and Reliability. --- Circuits and Systems. --- Operations Research, Management Science. --- Engineering systems --- System engineering --- Engineering --- Industrial engineering --- System analysis --- Computer operating systems --- Computers --- Disk operating systems --- Systems software --- Safety, System --- Safety of systems --- Systems safety --- Accidents --- Industrial safety --- Systems engineering --- Design and construction --- Operating systems --- Prevention --- Quality control. --- Reliability. --- Industrial safety. --- Computer software—Reusability. --- Electronic circuits. --- Operations research. --- Management science. --- Quantitative business analysis --- Management --- Problem solving --- Operations research --- Statistical decision --- Operational analysis --- Operational research --- Management science --- Research --- System theory --- Electron-tube circuits --- Electric circuits --- Electron tubes --- Electronics --- Industrial accidents --- Industries --- Job safety --- Occupational hazards, Prevention of --- Occupational health and safety --- Occupational safety and health --- Prevention of industrial accidents --- Prevention of occupational hazards --- Safety, Industrial --- Safety engineering --- Safety measures --- Safety of workers --- System safety --- Dependability --- Trustworthiness --- Conduct of life --- Factory management --- Reliability (Engineering) --- Sampling (Statistics) --- Standardization --- Quality assurance --- Quality of products

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This two-volume set constitutes the refereed proceedings of the First EAI International Conference on Intelligent Systems and Machine Learning, ICISML 2022, held in Hyderabad, India, in December 16-17,2022. The 75 full papers presented were carefully reviewed and selected from 209 submissions. The conference focuses on Intelligent Systems and Machine Learning Applications in Health care; Digital Forensic & Network Security; Intelligent Communication Wireless Networks; Internet of Things (IoT) Applications; Social Informatics; and Emerging Applications.

Machine learning --- Artificial intelligence. --- Artificial Intelligence. --- 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 --- Simulation methods --- Fifth generation computers --- Neural computers