Welcome to our book review site www.go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Cloud Computing for Geospatial Big Data Analytics
This book introduces the latest research findings in cloud, edge, fog, and mist computing and their applications in various fields using geospatial data. It solves a number of problems of cloud computing and big data, such as scheduling, security issues using different techniques, which researchers from industry and academia have been attempting to solve in virtual environments. Some of these problems are of an intractable nature and so efficient technologies like fog, edge and mist computing play an important role in addressing these issues. By exploring emerging advances in cloud computing and big data analytics and their engineering applications, the book enables researchers to understand the mechanisms needed to implement cloud, edge, fog, and mist computing in their own endeavours, and motivates them to examine their own research findings and developments.
Big Data Analytics
This volume comprises the select proceedings of the annual convention of the Computer Society of India. Divided into 10 topical volumes, the proceedings present papers on state-of-the-art research, surveys, and succinct reviews. The volumes cover diverse topics ranging from communications networks to big data analytics, and from system architecture to cyber security. This volume focuses on Big Data Analytics. The contents of this book will be useful to researchers and students alike.
Networks of the Future
With the ubiquitous diffusion of the IoT, Cloud Computing, 5G and other evolved wireless technologies into our daily lives, the world will see the Internet of the future expand ever more quickly. Driving the progress of communications and connectivity are mobile and wireless technologies, including traditional WLANs technologies and low, ultra-power, short and long-range technologies. These technologies facilitate the communication among the growing number of connected devices, leading to the generation of huge volumes of data. Processing and analysis of such "big data" brings about many opportunities, as well as many challenges, such as those relating to efficient power consumptions, securi...
Artificial Intelligence for Health 4.0: Challenges and Applications
Healthcare is one of the major success stories of our times. Medical science has improved rapidly, raising life expectancy around the world. However, as longevity increases, healthcare systems face growing demands for their services, rising costs, and a workforce that is struggling to meet the needs of its patients. Healthcare is one of the most critical sectors in the broader landscape of big data because of its fundamental role in a productive, thriving society. Building on automation, artificial intelligence (AI) has the potential to revolutionize healthcare and help address some of the challenges set out above. The application of AI to healthcare data can literally be a matter of life an...
Principles of Big Graph: In-depth Insight
Principles of Big Graph: In-depth Insight, Volume 128 in the Advances in Computer series, highlights new advances in the field with this new volume presenting interesting chapters on a variety of topics, including CESDAM: Centered subgraph data matrix for large graph representation, Bivariate, cluster and suitability analysis of NoSQL Solutions for big graph applications, An empirical investigation on Big Graph using deep learning, Analyzing correlation between quality and accuracy of graph clustering, geneBF: Filtering protein-coded gene graph data using bloom filter, Processing large graphs with an alternative representation, MapReduce based convolutional graph neural networks: A comprehen...
Internet of Behavior-Based Computational Intelligence for Smart Education Systems
Smart education is transforming the way we teach and learn by incorporating advanced technologies that enhance interactivity, personalization, and efficiency. By integrating digital tools, data analytics, and innovative strategies, it can better address the needs of 21st-century learners. Central to this shift is the Internet of Behavior (IoB). As IoT grows, it collects behavior-related data and combines that data analysis with intelligent systems. While this fusion enhances personalized learning, it also raises important concerns about privacy, security, and ethics. Internet of Behavior-Based Computational Intelligence for Smart Education Systems explores the intricacies of how IoB and computational intelligence are transforming education. It offers practical insights and theoretical foundations on how behavioral data can create smarter, more adaptive learning environments. Targeting educators, technologists, and researchers, the book delves into the latest developments at the intersection of technology and education, guiding readers toward more personalized, efficient, and effective learning systems.
Proceedings of 4th International Conference on ICT for Digital, Smart, and Sustainable Development
This book contains original, peer-reviewed research articles from 4th International Conference on ICT for Digital, Smart, and Sustainable Development (ICIDSSD 2024), organized by Jamia Hamdard, Delhi, India, during 23–24 April 2024. It includes most recent research trends and advancements in sustainable computing, sustainable energy consumption, governance, sustainability and security, human-built systems for sustainable development, sustainable IoT and cyber physical systems, big data analytics, data science and IoT, cloud computing, and artificial intelligence.
Health Informatics: A Computational Perspective in Healthcare
This book presents innovative research works to demonstrate the potential and the advancements of computing approaches to utilize healthcare centric and medical datasets in solving complex healthcare problems. Computing technique is one of the key technologies that are being currently used to perform medical diagnostics in the healthcare domain, thanks to the abundance of medical data being generated and collected. Nowadays, medical data is available in many different forms like MRI images, CT scan images, EHR data, test reports, histopathological data and doctor patient conversation data. This opens up huge opportunities for the application of computing techniques, to derive data-driven mod...
Newsline
None
The Herald
None
