Edge and cloud networking for 5G 6G HPC workflows for hybrid cloud AI for sustainable cloud operations Multimedia cloud computing Software engineering methods for cloud services Resource management and optimization Data management and distribution Blockchain driven cloud services Software Process as a Service Everything as a Service AI and ML for cloud operations management Intelligent Storage & data architectures Software defined network (SDN) Network function virtualization (NFV)

The book features original papers from International Conference on Expert Clouds and Applications (ICOECA 2023), organized by RV Institute of Technology and Management, Bangalore, India, during February 9–10, 2023. It covers new research insights on artificial intelligence, big data, cloud computing, sustainability, and knowledge-based expert systems. The book discusses innovative research from all aspects including theoretical, practical, and experimental domains that pertain to the expert systems, sustainable clouds, and artificial intelligence technologies. The thrust of the book is to showcase different research chapters dealing with the design, development, implementation, testing and analysis of intelligent systems, and expert clouds, and also to provide empirical and practical guidelines for the development of such systems.

This book features original papers from International Conference on Expert Clouds and Applications (ICOECA 2021), organized by GITAM School of Technology, Bangalore, India during February 18–19, 2021. It covers new research insights on artificial intelligence, big data, cloud computing, sustainability, and knowledge-based expert systems. The book discusses innovative research from all aspects including theoretical, practical, and experimental domains that pertain to the expert systems, sustainable clouds, and artificial intelligence technologies.

The year 2023 marks the 100th birth anniversary of E.F. Codd (19 August 1923 - 18 April 2003), a computer scientist, who while working for IBM invented the relational model for database management, the theoretical basis for relational databases and relational database management systems. He made other valuable contributions to computer science but the relational model, a very influential general theory of data management, remains his most mentioned, analyzed, and celebrated achievement. School of Computer Application, under the aegis of Lovely Professional University, pays homage to this great scientist of all times by hosting “CODD100 – International Conference on Networks, Intelligence and Computing (ICONIC-2023)”.

This book serves as a bridge connecting the theoretical foundations of DRL with practical, actionable insights for implementing these technologies in a variety of industrial contexts, making it a valuable resource for professionals and enthusiasts at the forefront of technological innovation. Deep Reinforcement Learning (DRL) represents one of the most dynamic and impactful areas of research and development in the field of artificial intelligence. Bridging the gap between decision-making theory and powerful deep learning models, DRL has evolved from academic curiosity to a cornerstone technology driving innovation across numerous industries. Its core premise—enabling machines to learn optimal actions within complex environments through trial and error—has broad implications, from automating intricate decision processes to optimizing operations that were previously beyond the reach of traditional AI techniques. “Deep Reinforcement Learning and Its Industrial Use Cases: AI for Real-World Applications” is an essential guide for anyone eager to understand the nexus between cutting-edge artificial intelligence techniques and practical industrial applications. This book not only demystifies the complex theory behind deep reinforcement learning (DRL) but also provides a clear roadmap for implementing these advanced algorithms in a variety of industries to solve real-world problems. Through a careful blend of theoretical foundations, practical insights, and diverse case studies, the book offers a comprehensive look into how DRL is revolutionizing fields such as finance, healthcare, manufacturing, and more, by optimizing decisions in dynamic and uncertain environments. This book distills years of research and practical experience into accessible and actionable knowledge. Whether you’re an AI professional seeking to expand your toolkit, a business leader aiming to leverage AI for competitive advantage, or a student or academic researching the latest in AI applications, this book provides valuable insights and guidance. Beyond just exploring the successes of DRL, it critically examines challenges, pitfalls, and ethical considerations, preparing readers to not only implement DRL solutions but to do so responsibly and effectively. Audience The book will be read by researchers, postgraduate students, and industry engineers in machine learning and artificial intelligence, as well as those in business and industry seeking to understand how DRL can be applied to solve complex industry-specific challenges and improve operational efficiency.

Due to the advancement of emerging technologies — Internet of Things (IoT), Artificial Intelligence (AI), and Blockchain (BC) — numerous aspects of our daily lives have witnessed remarkable progress. Further, with the involvement of these technologies (IoT, AI, and BC), the social life of a human is becoming more intelligent than ever. These technologies play a pivotal role in enhancing sectors such as healthcare, education, cities, households, agriculture, and industrial applications despite encountering certain challenges and complexities. Based on the contributions of these technologies, we provide a comprehensive survey covering various smart applications in different areas of everyday life. Firstly, we undertake an examination of state-of-the-art information, attributes, and prospects, with a specific emphasis on the literature that revolves around the technologies of AI, BC, and IoT. Further, we discuss the contributions of these technologies in the targeted areas and applications. Then, we efficiently introduce the integration of these technologies, including IoT-BC, IoT-AI-BC, and BC-AI, in the desired fields. Lastly, some open issues and future challenges have been analysed.

Healthcare systems globally are grappling with how best to implement effective and efficient patient-centred care while simultaneously trying to contain runaway costs and provide high quality. This book explores the essential enabling role of digital health, taking a socio-technical perspective and looking at the key facets of technology, people and process in turn. This book examines the opportunities of key digital health components, demystifying digital health and demonstrating how to use its key precepts effectively. The book presents evidence and anecdotes from stakeholders around the world, demonstrating the global relevance and the ability of digital health to uplift and upskill care delivery as it is applied commercially. Bridging academic theory and practice, this is a functional and accessible text for all digital health stakeholders. The text introduces critical issues and is suitable reading for students, practitioners and researchers in digital health and all healthcare-related domains.

This book contains the proceedings of 5th International Conference on Advances in AI for Biomedical Instrumentation, Electronics and Computing (ICABEC - 2023), which provided an international forum for the exchange of ideas among researchers, students, academicians, and practitioners. It presents original research papers on subjects of AI, Biomedical, Communications & Computing Systems. Some interesting topics it covers are enhancing air quality prediction using machine learning, optimization of leakage power consumption using hybrid techniques, multi-robot path planning in complex industrial dynamic environment, enhancing prediction accuracy of earthquake using machine learning algorithms and advanced machine learning models for accurate cancer diagnostics. Containing work presented by a diverse range of researchers, this book will be of interest to students and researchers in the fields of Electronics and Communication Engineering, Computer Science Engineering, Information Technology, Electrical Engineering, Electronics and Instrumentation Engineering, Computer applications and all interdisciplinary streams of Engineering Sciences.

This is the first coherent book on literature-based discovery (LBD). LBD is an inherently multi-disciplinary enterprise. The aim of this volume is to plant a flag in the ground and inspire new researchers to the LBD challenge.