Kategoria BISAC: Computers >> Database Administration & Management

This book discusses integration of internet of things (IoT), cloud computing, and big data. It presents a unique platform where IoT, cloud computing, and big data are fused together and can be foreseen as a perfect solution to many applications. Usually, IoT, cloud computing, and big data are researched separately on the basis of their properties, underlying technologies, and other open issues. Integration of IoT, cloud computing and big data is not that easy and can face key open issues like standardization of interfaces, power and energy efficiency in both data processing and...

Now in a thoroughly revised and expanded second edition, this classroom-tested text demonstrates and illustrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability, statistics, experimental design, regression, optimization, parameter estimation, inverse modeling, risk analysis, decision-making, and sustainability assessment methods to energy processes and systems. It provides a formal structure that offers a broad and integrative perspective to enhance knowledge, skills, and confidence to work in applied data analysis and modeling...

This book provides a concise guide tailored for researchers, bioinformaticians, and enthusiasts eager to unravel the mysteries hidden within single-cell RNA sequencing (scRNA-seq) data using cutting-edge machine learning techniques. The advent of scRNA-seq technology has revolutionized our understanding of cellular diversity and function, offering unprecedented insights into the intricate tapestry of gene expression at the single-cell level. However, the deluge of data generated by these experiments presents a formidable challenge, demanding advanced analytical tools, methodologies, and...

This two-volume set constitutes the refereed proceedings of the Second International Conference, ISDS 2024, held in Nha Trang, Vietnam, during November 9-10, 2024.

The 38 full papers and 10 short papers were carefully reviewed and selected from 129 submissions. They were categorized under the topical sections as follows: AI in E-Commerce, Agriculture, and Aquaculture; AI in Health Care Analytics; Big Data, IoT, and Cloud Computing; and Natural Language Processing.

This book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It presents comparative studies of model-centric and data-centric AI. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI. It serves as a reference guide for researchers and practitioners in academia and industry.