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This book provides a conceptual ‘Flexibility in Resource Management’ framework supported by research/case applications in various related areas. It links and integrates the flexibility aspect with resource management to offer a fresh perspective, since flexibility in different levels of resource management is emerging as a key concern -- a business enterprise needs to have reactive flexibility (as adaptiveness and responsiveness) to cope with the changing and uncertain business environment. It may also endeavor to intentionally create flexibility by way of leadership change, re-engineering, innovation in products and processes, use of information and communication technology, and so on. The selected papers discussing a variety of issues concerning flexibility in resource management, are organized into following four parts: flexibility and innovation; flexibility in organizational management; operations and technology management; and financial and risk management. In addition to addressing the organizational needs of corporate bodies spread across the globe, the book serves as a useful reference resource for a variety of audiences including management students, researchers, business managers, consultants and professional institutes.

Management. --- Administration --- Business. --- Organization. --- Planning. --- Production management. --- Risk management. --- Business and Management. --- Operations Management. --- Risk Management. --- Operations Research/Decision Theory. --- Industrial relations --- Organization --- Operations research. --- Insurance --- Management --- Organisation --- Manufacturing management --- Industrial management --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Decision making. --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management decisions --- Choice (Psychology) --- Problem solving --- Creation (Literary, artistic, etc.) --- Executive ability --- Decision making

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This book provides insights into deep learning techniques that impact the implementation strategies toward achieving the Sustainable Development Goals (SDGs) laid down by the United Nations for its 2030 agenda, elaborating on the promises, limits, and the new challenges. It also covers the challenges, hurdles, and opportunities in various applications of deep learning for the SDGs. A comprehensive survey on the major applications and research, based on deep learning techniques focused on SDGs through speech and image processing, IoT, security, AR-VR, formal methods, and blockchain, is a feature of this book. In particular, there is a need to extend research into deep learning and its broader application to many sectors and to assess its impact on achieving the SDGs. The chapters in this book help in finding the use of deep learning across all sections of SDGs. The rapid development of deep learning needs to be supported by the organizational insight and oversight necessary for AI-based technologies in general; hence, this book presents and discusses the implications of how deep learning enables the delivery agenda for sustainable development.

Computational intelligence. --- Blockchains (Databases). --- Sustainability. --- Quantitative research. --- Artificial intelligence. --- Internet of things. --- Computational Intelligence. --- Blockchain. --- Data Analysis and Big Data. --- Artificial Intelligence. --- Internet of Things. --- IoT (Computer networks) --- Things, Internet of --- Computer networks --- Embedded Internet devices --- Machine-to-machine communications --- 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 --- Data analysis (Quantitative research) --- Exploratory data analysis (Quantitative research) --- Quantitative analysis (Research) --- Quantitative methods (Research) --- Research --- Sustainability science --- Human ecology --- Social ecology --- Block chains (Databases) --- Database security --- Distributed databases --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Blockchains (Databases)

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Sustainable development --- Data processing. --- Development, Sustainable --- Ecologically sustainable development --- Economic development, Sustainable --- Economic sustainability --- ESD (Ecologically sustainable development) --- Smart growth --- Sustainable economic development --- Economic development --- Environmental aspects

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This book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications (MIDAS 2022), held on October 28 and 29, 2022, at the University of Versailles—Paris-Saclay, France. The book covers applications in various fields like data science, machine intelligence, image processing, natural language processing, computer vision, sentiment analysis, and speech and gesture analysis. It also includes interdisciplinary applications like legal, healthcare, smart society, cyber-physical system, and smart agriculture. The book is a good reference for computer science engineers, lecturers/researchers in the machine intelligence discipline, and engineering graduates.

Computational intelligence. --- Artificial intelligence. --- Quantitative research. --- Machine learning. --- Computational Intelligence. --- Artificial Intelligence. --- Data Analysis and Big Data. --- Machine Learning. --- Learning, Machine --- Artificial intelligence --- Machine theory --- 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 --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Data analysis (Quantitative research) --- Exploratory data analysis (Quantitative research) --- Quantitative analysis (Research) --- Quantitative methods (Research) --- Research --- Intelligence, Computational --- Soft computing

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This book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications, organized by the School of Computer Science, University of Petroleum & Energy Studies, Dehradun, India, during 4-5 September 2020. The book addresses the algorithmic aspect of machine intelligence which includes the framework and optimization of various states of algorithms. Variety of papers related to wide applications in various fields like data-driven industrial IoT, bioinformatics, network and security, autonomous computing and various other aligned areas. The book concludes with interdisciplinary applications like legal, health care, smart society, cyber-physical system and smart agriculture. All papers have been carefully reviewed. The book is of interest to computer science engineers, lecturers/researchers in machine intelligence discipline and engineering graduates.

Programming --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- neuronale netwerken --- fuzzy logic --- cybernetica --- programmeren (informatica) --- computerbeveiliging --- KI (kunstmatige intelligentie) --- AI (artificiële intelligentie)