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Realization
"Everything was perfect, at least for him. Now even a message notification would cheer him up, which was of no importance to him before. Now he spent most of his time with his cellphone. From being Mr. Attitude of college, he had transformed into a lover boy. This was something he had never witnessed or experienced before. This was a great feeling, a never-ending warmth in his heart. These new happenings made his life heaven; after all, it was first time he was experiencing love. He had friends who were his life and now, he had someone who was more than a friend to him. He was happy about his decision to be in love. His life was in full pace and the little emptiness of his heart had been fil...
Utilization of AI Technology in Supply Chain Management
The surge in digital transformation and the integration of innovative technologies into manufacturing processes have given rise to a pressing issue in supply chain management. Businesses are in dire need of solutions to navigate this complexity and harness the true potential of intelligent supply chains. Utilization of AI Technology in Supply Chain Management is a comprehensive guide tailored for academic scholars seeking to unravel the mysteries of artificial intelligence (AI) and machine learning (ML) in the context of supply chain management. Amid the hype surrounding AI and ML, there exists a critical need to bridge the gap between human expertise and technological advancements. Utilization of AI Technology in Supply Chain Management addresses this necessity by delving into real-world instances where teams have successfully employed these innovative technologies to enhance supply chain performance, reduce inventory, and optimize routes. The adoption of AI and ML is not just a trend; it is the cornerstone of digital acceleration initiatives, making it imperative for scholars to understand and leverage these technologies effectively.
Computational Intelligence for Engineering and Management Applications
This book comprises select proceedings of the 1st International Conference on Computational Intelligence for Engineering and Management Applications (CIEMA - 2022). This book emphasizes applications of computational intelligence including machine intelligence, data analytics, and optimization algorithms for solving fundamental and advanced engineering and management problems. This book serves as a valuable resource for researchers, industry professionals, academicians, and doctoral scholars in engineering, production, thermal, materials, design, computer engineering, natural sciences, and management who work on computational intelligence. The book also serves researchers who are willing to use computational intelligence algorithms in real-time applications.
Integrating Artificial Intelligence and Machine Learning with Blockchain Security
Due to its transparency and dependability in secure online transactions, blockchain technology has grown in prominence in recent years. Several industries, including those of finance, healthcare, energy and utilities, manufacturing, retail marketing, entertainment and media, supply chains, e-commerce, and e-business, among others, use blockchain technology. In order to enable intelligent decision-making to prevent security assaults, particularly in permission-less blockchain platforms, artificial intelligence (AI) techniques and machine learning (ML) algorithms are used. By exploring the numerous use cases and security methods used in each of them, this book offers insight on the application of AI and ML in blockchain security principles. The book argues that it is crucial to include artificial intelligence and machine learning techniques in blockchain technology in order to increase security.
Computational Intelligence for Modern Business Systems
This book covers the applications of computational intelligence techniques in business systems and advocates how these techniques are useful in modern business operations. The book redefines the computational intelligence foundations, the three pillars - neural networks, evolutionary computation, and fuzzy systems. It also discusses emerging areas such as swarm intelligence, artificial immune systems (AIS), support vector machines, rough sets, and chaotic systems. The other areas have also been demystified in the book to strengthen the range of computational intelligence techniques such as expert systems, knowledge-based systems, and genetic algorithms. Therefore, this book will redefine the...
Healthcare 4.0
The main aim of Healthcare 4.0: Health Informatics and Precision Data Management is to improve the services given by the healthcare industry and to bring meaningful patient outcomes by applying the data, information and knowledge in the healthcare domain. Features: Improves the quality of health data of a patient Presents a wide range of opportunities and renewed possibilities for healthcare systems Gives a way for carefully and meticulously tracking the provenance of medical records Accelerates the process of disease-oriented data and medical data arbitration Brings meaningful patient health outcomes Eradicates delayed clinical communications Helps the research intellectuals to step down further toward the disease and clinical data storage Creates more patient-centered services The precise focus of this handbook is on the potential applications and use of data informatics in healthcare, including clinical trials, tailored ailment data, patient and ailment record characterization and health records management.
Proceedings of Third Doctoral Symposium on Computational Intelligence
This book features high-quality research papers presented at Third Doctoral Symposium on Computational Intelligence (DoSCI 2022), organized by Institute of Engineering and Technology (IET), AKTU, Lucknow, India, on March 5, 2022. This book discusses the topics such as computational intelligence, artificial intelligence, deep learning, evolutionary algorithms, swarm intelligence, fuzzy sets and vague sets, rough set theoretic approaches, quantum inspired computational intelligence, hybrid computational intelligence, machine learning, computer vision, soft computing, distributed computing, parallel and grid computing, cloud computing, high performance computing, biomedical computing, and decision support and decision making.
Artificial Intelligence Techniques for Sustainable Development
How can the efficiency of the algorithms be increased with a lesser number of computations as well as optimized with the resources for cost-effective solutions? Artificial Intelligence Techniques for Sustainable Development provides an answer. Further, it discusses important concepts such as green communication network design and implementation for the Internet of Things ecosystem, green computing in network security, and artificial intelligence models for remote sensing applications. Key features: Presents the latest tools and techniques in developing solutions intended for resource utilization, energy efficiency, and human and environmental health Highlights the advancement in electronics ...
