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Convergence of IoT, Blockchain, and Computational Intelligence in Smart Cities
This edited book presents an insight for modelling, procuring, and building the smart city plan using the Internet of Things (IoT) and a security framework using blockchain technology. The applications of Li-Fi and 5G in smart cities are included, along with their implementation, challenges, and advantages. This book focuses on the use of IoT and blockchain in the day-to-day transparent and recorded activities of citizens of smart cities like, smart citizen management. The future for upgrading the system as per technological advancements is also discussed. This book: integrates IoT, blockchain, Li-Fi, and 5G in smart city implementation covers smart supply chain management using IoT outlines the state-of-the-art and sustainable implementation of smart cities and practical challenges includes sustainable development of smart cities presents detailed explanation of case studies of smart cities of developed countries and developing countries and their comparisons This book is aimed at researchers and graduate students in Artificial Intelligence, Urban Planning, and Information Technology Systems and Management.
Learning Curves
Written by international contributors, Learning Curves: Theory, Models, and Applications first draws a learning map that shows where learning is involved within organizations, then examines how it can be sustained, perfected, and accelerated. The book reviews empirical findings in the literature in terms of different sources for learning and partia
Machine Learning Hybridization and Optimization for Intelligent Applications
This book discusses state-of-the-art reviews of the existing machine learning techniques and algorithms including hybridizations and optimizations. It covers applications of machine learning via artificial intelligence (AI) prediction tools, discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, pattern recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation. Features: • Focuses on hybridization and optimization of machine learning techniques. • Reviews supervised, unsupervised, and reinforcement learning using...
Information Technology Ethics
This book explains moral dilemmas in the IT industry, focusing on a different area of IT ethics. It starts by introducing theories, decision-making models, and the fundamental function of moral leadership in IT companies, followed by ethical obligations related to intellectual property, privacy, professional ethics, and software development. It looks at how IT affects society in terms of accessibility and well-being, including cybersecurity tactics, privacy and data protection legislation, legal and regulatory frameworks, and the moral obligations of IT workers and companies. Features: Includes extensive examination of IT ethics encompassing fundamental theories Covers foundational concepts,...
Big Data Computing
This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka, and so forth. It also covers developments in big data computing applications such as machine learning, deep learning, graph processing, and many others. Features: Provides comprehensive analysis of advanced aspects of big data challenges and enabling technologies. Explains computing models using real-world examples and dataset-based experiments. Includes case studies, quality diagrams, and demonstrations in each chapter. Describes modifications and optimization of existing technologies along with the novel big data computing models. Explores references to machine learning, deep learning, and graph processing. This book is aimed at graduate students and researchers in high-performance computing, data mining, knowledge discovery, and distributed computing.
Applications of Blockchain and Computational Intelligence in Environmental Sustainability
The book explores the complex correlation between blockchain technology and sustainability, demonstrating the potential of cutting-edge computational intelligence methods to address critical environmental and societal challenges. It provides a comprehensive analysis of the most recent developments in research, innovative approaches to design, and real-world implementations, establishing a strategic plan for the incorporation of blockchain technology into environmentally friendly solutions. Features: Focuses on the intersection of blockchain technology, computational intelligence, and sustainability. Covers international regulatory landscapes and ethical considerations. Emphasizes real-world applications such as supply chain management systems and smart energy networks. Offers concrete examples of how these technologies contribute to sustainability. Provides insight into how new technologies are transforming health informatics. This book is aimed at graduate students and researchers in computer engineering and environmental sustainability.
Software-Defined Network Frameworks
Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and...
Network Security and Data Privacy in 6G Communication
This book proposes robust solutions for securing a network against intrusions for data privacy and safety. It includes theoretical models, commercialization of validated models, and case studies. Explains the integration of technologies such as artificial intelligence, the Internet of Things, and blockchain for network security in a 6G communication system. Highlights the challenges such as spectrum allocation and management, network architecture and heterogeneity, energy efficiency and sustainability, antenna, and radio frequency. Discuss theories like quantum-safe cryptography, zero-trust networking, and blockchain-based trust management. Covers emerging technologies including homomorphic encryption, secure multi-party computation, post-quantum cryptography, and distributed ledger technology for security and privacy in 6G communication systems. Presents light and deep secure algorithms to detect fake incidents in wireless communication. The text is primarily written for senior undergraduates, graduate students, and academic researchers in fields including electrical engineering, electronics and communications engineering, and computer science.
Dissertation Abstracts International
Abstracts of dissertations available on microfilm or as xerographic reproductions.
