This book explores how human civilization has contributed to changes in the Anthropocene, an era that marks a fundamental change in the way mankind has interacted with the Earth system. It examines the 21st century in the context of human development of water infrastructures, climate change impacts on freshwater resources, groundwater depletion, rising population, land use change, extreme events (droughts, floods, and wildfires). The implications of climate change impacts on environmental assets and the global water cycle are also highlighted. The book takes a pragmatically trans-disciplinary and holistic approach to the discussion of these issues, and the Earth system in the Anthropocene, drawing from a plethora of case studies. The capabilities of machine learning tools in satellite hydrology applications have been demonstrated as well as the feasibility of remote sensing data and innovative geospatial tools in environmental assessment. The book further showcases the multiple strengths and potential of new multi-disciplinary satellite radar programmes and geodetic missions, to measure and characterize extreme events, and their links to global climate, as well as in remote sensing of the environment.

This book covers all the emerging trends in artificial intelligence (AI) and the Internet of Things (IoT). The Internet of Things is a term that has been introduced in recent years to define devices that are able to connect and transfer data to other devices via the Internet. While IoT and sensors have the ability to harness large volumes of data, AI can learn patterns in the data and quickly extract insights in order to automate tasks for a variety of business benefits.

"Time Series Forecasting Using Generative AI introduces readers to Generative Artificial Intelligence (Gen AI) in time series analysis, offering an essential exploration of cutting-edge forecasting methodologies."

This volume deals with three key areas of the advancements in AI: machine learning and data mining, computer vision, and multi-agent systems. This book should serve as a valuable resource not just to scientists dealing with AI research but also to anyone interested in its broad application areas across various disciplines.

This book discusses deep learning, from its fundamental principles to its practical applications, with hands-on exercises and coding. It focuses on deep learning techniques and shows how to apply them across a wide range of practical scenarios.

This book discusses deep learning, from its fundamental principles to its practical applications, with hands-on exercises and coding. It focuses on deep learning techniques and shows how to apply them across a wide range of practical scenarios.

The book includes peer-reviewed papers presented at the 2nd International Conference on Intelligent Computing Systems and Applications (ICICSA 2023). The book discusses the most recent advances in artificial intelligence, machine learning, data science, natural language processing, computer vision, image processing, embedded systems, robotics, IoT, computer networking and communications, optimization, security, and cryptography, among other topics. It also discusses several application areas and modeling methodologies in many fields. This book will be useful for researchers and academics working in relevant fields.

This is the first book completely dedicated to positioning and navigation using machine learning methods. It deals with ground, aerial, and space positioning and navigation for pedestrians, vehicles, UAVs, and LEO satellites. Most of the major machine learning methods are utilized, including supervised learning, unsupervised learning, deep learning, and reinforcement learning. The book presents both fundamentals and in-depth studies as well as practical examples in positioning and navigation. Extensive data processing and experimental results are provided in the major chapters through conducting experimental campaigns or using in-situ measurements.

This book presents a comprehensive framework for analyzing, evaluating, and guiding AI for Sciences (AI4Sci) research, offering a unified approach that facilitates analysis across various academic fields through a shared set of dimensions and indicators. It provides a systematic overview of recent AI4Sci advances in various disciplines and offers insights into the latest issues in and prospects of AI4Sci. The book is based on the theory of Parallel Intelligence (PI), which forms the foundation for the general AI4Sci framework. By analyzing multiple cases in various academic fields, this framework integrates key elements of AI4Sci, such as real scientific problems, datasets, virtual systems, AI methods, human roles, and organizational mechanisms, from a multidimensional perspective. It also assesses and summarizes the limitations of AI4Sci, incorporating the latest advances in AI for fundamental models. Lastly, it explores the impact of DeSci and DAO, as well as TAO, on AI4Sci ecosystem development and prospects. Through its balanced approach, the book offers readers a goal-oriented perspective, focusing on a concise presentation of the core ideas and reducing detailed descriptions of specific AI4Sci cases to a minimum.

This book constitutes the Proceedings of the International Conference on Internet of Everything and Quantum Information Processing (IEQIP-2023), held on 24–25 November 2023 in Andhra Pradesh, India. This edition was organized in hybrid mode by the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, and sponsored by the Department of Science and Technology, India.

These two-volume set IFIP AICT 717 and 718 constitutes the refereed post-conference proceedings of the 7th International Conference on Computational Intelligence in Data Science, ICCIDS 2024, held in Chennai, India, during February 21–23, 2024. The 63 full papers and 9 short papers were presented in these proceedings were carefully reviewed and selected from 259 submissions. The conference papers are organized in topical sections on:

This book offers an extensive guide to the most engaging computer and laboratory sessions for teaching manufacturing engineering topics. It serves as a valuable resource for educators in planning their practical coursework. The book comprises 14 chapters covering a wide range of subjects, including design and simulations, various manufacturing processes such as additive manufacturing, injection molding, forming, machining, casting, and non-conventional machining, as well as process monitoring, metrology, and inspection using computed tomography. It also explores the application of methodologies like the design of experiments and machine learning. These contributions enable both lecturers and students to apply manufacturing engineering theory in real-world scenarios, drawing from the best practices developed in engineering institutions worldwide.