Ramesh Chandra Poonia

Kamal Upreti

Danish Nadeem

Jossy George

Ankit Gautam

This book serves as a comprehensive guide, covering the fundamentals of cloud computing, advanced concepts, and practical applications. Discusses cyber-physical systems, cloud integration for environmental management, and cloud security intelligence systems for sustainable operations. Presents case studies based on computational intelligence-based optimization for sustainable operations and cloud integration. Emphasizes how cloud computing revolutionizes traditional processes, enabling direct input of assembly details into a computation model, streamlining development cycles, and reducing costs. Bridges the gap between theory and practice by offering guidelines on problem encoding and implementation strategies, empowering readers to apply their acquired knowledge to solve complex industrial problems. Covers wireless security in the cloud era, mechatronics and cloud integration, and cloud-enabled manufacturing for eco-friendly operations. The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer engineering, and information technology.

Building Intelligent Systems for Tomorrow

Cognitive Cloud Computing

Xiao-Zhi Gao

Ashish Kumar Luhach

Dharm Singh Jat

This book gathers high-quality papers presented at the Second International Conference on Sustainable Technologies for Computational Intelligence (ICTSCI 2021) held at Graphic Era University, Dehradun, India, during May 22–23, 2021. It covers emerging topics in computational intelligence and effective strategies for its implementation in engineering applications.

Proceedings of ICTSCI 2021

Second International Conference on Sustainable Technologies for Computational Intelligence

Lakhmi C. Jain

Valentina Emilia Balas

Manisha Sharma

Basant Agarwal

Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis

Deep Learning Techniques for Biomedical and Health Informatics

Janmenjoy Nayak

Sandeep Kumar

Mohammad Khan

Goncalo Marques

Cyber-Physical Systems: AI and COVID-19 highlights original research which addresses current data challenges in terms of the development of mathematical models, cyber-physical systems-based tools and techniques, and the design and development of algorithmic solutions, etc. It reviews the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS) and reviews tools and techniques that can be used. This book will act as a resource to guide COVID researchers as they move forward with clinical and epidemiological studies on this outbreak, including the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS). The major problem in the identification of COVID-19 is detection and diagnosis due to non-availability of medicine. In this situation, only one method, Reverse Transcription Polymerase Chain Reaction (RT-PCR) has been widely adopted and used for diagnosis. With the evolution of COVID-19, the global research community has implemented many machine learning and deep learning-based approaches with incremental datasets. However, finding more accurate identification and prediction methods are crucial at this juncture. Offers perspectives on the design, development and commissioning of intelligent applications Provides reviews on the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of COVID-19 Puts forth insights on how future illnesses can be supported using intelligent corona virus monitoring techniques

AI and COVID-19

Cyber-Physical Systems

Dharm Singh

Janos Arpad Kosa

This book gathers high-quality papers presented at the First International Conference on Sustainable Technologies for Computational Intelligence (ICTSCI 2019), which was organized by Sri Balaji College of Engineering and Technology, Jaipur, Rajasthan, India, on March 29–30, 2019. It covers emerging topics in computational intelligence and effective strategies for its implementation in engineering applications.

Proceedings of ICTSCI 2019

First International Conference on Sustainable Technologies for Computational Intelligence

Ramesh Chandra Poonia

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