Advancement of Data Processing Methods for Artificial and Computing Intelligence (River Publishers Series in Computing and Information Science and Technology)

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Advancement of Data Processing Methods for Artificial and Computing Intelligence (River Publishers Series in Computing and Information Science and Technology)

Rawat, Seema (EDT)/ Devi, V. Ajantha (EDT)/ Kumar, Praveen (EDT)

ウェブストア価格 ¥31,257（本体¥28,416）
River Publishers（2024/04発売）
外貨定価 US$ 150.00
ポイント 284pt

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製本 Hardcover:ハードカバー版／ページ数 384 p.
言語 ENG
商品コード 9788770040174
DDC分類 006.3

Full Description

This book emphasizes the applications of advances in data processing methods for Artificial Intelligence in today's fast-changing world, as well as to serve society through research, innovation, and development in this field. This book is applicable to a wide range of data that contribute to data science concerns and can be used to promote research in this high-potential new field. People's perceptions of the world and how they conduct their lives have changed dramatically as a result of technological advancements. The world has been gripped by technology, and the advances that are being made every day are undeniably transforming the planet. In the domains of Big Data, engineering, and data science, this cutting-edge technology is ready to support us.

Artificial intelligence (AI) is a current research topic because it can be applied to a wide range of applications and disciplines to solve complicated problems and find optimal solutions. In research, medicine, technology, and the social sciences, the benefits of AI have already been proven. Data science, also known as pattern analytics and mining, is a technique for extracting useful and relevant information from databases, enabling better decision-making and strategy formulation in a range of fields. As a result of the exponential growth of data in recent years, the combined notions of big data and AI have given rise to many study areas, such as scale-up behaviour from classical algorithms. Furthermore, combining numerous AI technologies from other areas (such as vision, security, control, and biology) in order to build efficient and durable systems that interact in the real world is a new problem. Despite recent improvements in fundamental AI technologies, the integration of these skills into larger, trustworthy, transparent, and maintainable systems is still in its development. Both conceptually and practically, there are a number of unanswered issues.

1. Novel Nonparametric Method of Multivariate Data Analysis and Interpretation 2. Data Analysis on Automation of Purging with IoT in FRAMO Cargo Pump 3. Big Data Analytics in Healthcare Sector: Potential Strength and Challenges 4. Role of Big Data Analytics in Cloud Applications 5. Big data Analytics with Artificial Intelligence: A Comprehensive Investigation 6. Cloud Computing Environment For Big Data Analytics 7. Artificial Intelligence-based Data Wrangling Issues and Data Analytics Process for Various Domains 8. Artificial Intelligence and Data Science in Various Domains 9. Method for Implementing Time-control Functions in Real-time Operating Systems 10. Efficient Blurred and De-Blurred Image Classification using Machine Learning Approach 11. Method for Characterization of Brain Activity using Brain-Computer Interface Devices 12. Streaming Highway Traffic Alerts using Twitter API 13. Harnessing the Power of Artificial Intelligence and Data Science 14. Determining the Severity of Diabetic Retinopathy through Neural Network Models 15. Method for Muscle Activity Characterization using Wearable Devices