Machine Learning and Artificial Intelligence to Advance Earth System Science: Opportunities and Challenges: Proceedings of a Workshop PDF Download

Author: National Academies Of Sciences Engineeri
Publisher: National Academies Press
ISBN: 9780309688536
Category : Computers
Languages : en
Pages :

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Book Description
The Earth system - the atmospheric, hydrologic, geologic, and biologic cycles that circulate energy, water, nutrients, and other trace substances - is a large, complex, multiscale system in space and time that involves human and natural system interactions. Machine learning (ML) and artificial intelligence (AI) offer opportunities to understand and predict this system. Researchers are actively exploring ways to use ML/AI approaches to advance scientific discovery, speed computation, and link scientific communities. To address the challenges and opportunities around using ML/AI to advance Earth system science, the National Academies convened a workshop in February 2022 that brought together Earth system experts, ML/AI researchers, social and behavioral scientists, ethicists, and decision makers to discuss approaches to improving understanding, analysis, modeling, and prediction. Participants also explored educational pathways, responsible and ethical use of these technologies, and opportunities to foster partnerships and knowledge exchange. This publication summarizes the workshop discussions and themes that emerged throughout the meeting.

Author:
Publisher: Academic Press
ISBN: 0128234679
Category : Medical
Languages : en
Pages : 578

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Book Description
Advances in Pharmacology series, highlights new advances in the field, with this new volume presenting interesting chapters. Each chapter is written by an international board of authors. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in Advances in Pharmacology series Updated release includes the latest information on Endocrine-Disrupting Chemicals

Author: Rajappan, Roopa Chandrika
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 428

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Book Description
Picture a world where autonomous systems operate continuously and intelligently, utilizing real-time data to make informed decisions. Such systems have the potential to revolutionize agriculture, urban infrastructure, and industrial automation. This transformation, often termed the Internet of Self-Sustaining Systems (IoSS), is a pivotal topic that demands academic attention and exploration. Addressing this critical issue head-on is The Convergence of Self-Sustaining Systems With AI and IoT, which offers an in-depth examination of this transformative convergence. It serves as a guiding light for academic scholars seeking to unravel the vast potential of self-sustaining systems coupled with AI and IoT. Inside its pages, readers will delve into AI-driven autonomous agriculture, eco-friendly transportation solutions, and intelligent energy management. Moreover, the book explores emerging technologies, security concerns, ethical considerations, and governance frameworks. Join us on this intellectual journey and position yourself at the forefront of the AI and IoT revolution that promises a sustainable, autonomous future.

Author: J. Andersson
Publisher: IOS Press
ISBN: 1643685112
Category : Technology & Engineering
Languages : en
Pages : 750

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Book Description
Collaboration between those working in product development and production is essential for successful product realization. The Swedish Production Academy (SPA) was founded in 2006 with the aim of driving and developing production research and higher education in Sweden, and increasing national cooperation in research and education within the area of production. This book presents the proceedings of SPS2024, the 11th Swedish Production Symposium, held from 23 to 26 April 2024 in Trollhättan, Sweden. The conference provided a platform for SPA members, as well as for professionals from industry and academia interested in production research and education from around the world, to share insights and ideas. The title and overarching theme of SPS2024 was Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning, and the conference emphasized stakeholder value, the societal role of industry, worker wellbeing, and environmental sustainability, in alignment with the European Commission's vision for the future of manufacturing. The 59 papers included here were accepted for publication and presentation at the symposium after a thorough review process. They are divided into 6 sections reflecting the thematic areas of the conference, which were: sustainable manufacturing, smart production and automation, digitalization for efficient product realization, circular production, industrial transformation for sustainability, and the integration of education and research. Highlighting the latest developments and advances in automation and sustainable production, the book will be of interest to all those working in the field.

Author: Fadi Al-Turjman
Publisher: Elsevier
ISBN: 0323957846
Category : Political Science
Languages : en
Pages : 428

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Book Description
XAI Based Intelligent Systems for Society 5.0 focuses on the development and analysis of Explainable Artificial Intelligence (XAI)-based models and intelligent systems that can be utilized for Society 5.0—characterized by a knowledge intensive, data driven, and non-monetary society. The book delves into the issues of transparency, explainability, data fusion, and interpretability, which are significant for the development of a super smart society and are addressed through XAI-based models and techniques. XAI-based deep learning models, fuzzy and hybrid intelligent systems, expert systems, and intrinsic explainable models in the context of Society 5.0 are presented in detail. The book also addresses—using XAI-based intelligent techniques—the privacy issues intrinsic in storing huge amounts of data or information in virtual space. The concept of Responsible AI, which is at the core of the future direction of XAI for Society 5.0, is also explored in this book. Finally, the application areas of XAI, including relevant case studies, are presented in the concluding chapter. This book serves as a valuable resource for graduate/post graduate students, academicians, analysts, computer scientists, engineers, researchers, professionals, and other personnel working in the area of artificial intelligence, machine learning, and intelligent systems, who are interested in creating a people-centric smart society. Defines the basic terminology and concepts surrounding explainability and related topics to bring coherence to the field Focuses on what techniques are available to improve explainability and how explainability can progress society Offers a broad range of topics, addressing multiple facets of XAI within the context of Society 5.0

Author: Ziheng Sun
Publisher: Elsevier
ISBN: 0323972160
Category : Science
Languages : en
Pages : 430

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Book Description
Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges provides a comprehensive, step-by-step guide to AI workflows for solving problems in Earth Science. The book focuses on the most challenging problems in applying AI in Earth system sciences, such as training data preparation, model selection, hyperparameter tuning, model structure optimization, spatiotemporal generalization, transforming model results into products, and explaining trained models. In addition, it provides full-stack workflow tutorials to help walk readers through the whole process, regardless of previous AI experience. The book tackles the complexity of Earth system problems in AI engineering, fully guiding geoscientists who are planning to implement AI in their daily work. Provides practical, step-by-step guides for Earth Scientists who are interested in implementing AI techniques in their work Features case studies to show real-world examples of techniques described in the book Includes additional elements to help readers who are new to AI, including end-of-chapter, key concept bulleted lists that concisely cover key concepts in the chapter

Author: Pradeep Sharma
Publisher: Academic Press
ISBN: 0323885993
Category : Technology & Engineering
Languages : en
Pages : 707

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Book Description
Bioinformatics in Agriculture: Next Generation Sequencing Era is a comprehensive volume presenting an integrated research and development approach to the practical application of genomics to improve agricultural crops. Exploring both the theoretical and applied aspects of computational biology, and focusing on the innovation processes, the book highlights the increased productivity of a translational approach. Presented in four sections and including insights from experts from around the world, the book includes: Section I: Bioinformatics and Next Generation Sequencing Technologies; Section II: Omics Application; Section III: Data mining and Markers Discovery; Section IV: Artificial Intelligence and Agribots. Bioinformatics in Agriculture: Next Generation Sequencing Era explores deep sequencing, NGS, genomic, transcriptome analysis and multiplexing, highlighting practices forreducing time, cost, and effort for the analysis of gene as they are pooled, and sequenced. Readers will gain real-world information on computational biology, genomics, applied data mining, machine learning, and artificial intelligence. This book serves as a complete package for advanced undergraduate students, researchers, and scientists with an interest in bioinformatics. Discusses integral aspects of molecular biology and pivotal tool sfor molecular breeding Enables breeders to design cost-effective and efficient breeding strategies Provides examples ofinnovative genome-wide marker (SSR, SNP) discovery Explores both the theoretical and practical aspects of computational biology with focus on innovation processes Covers recent trends of bioinformatics and different tools and techniques

Author: Ashok N. Srivastava
Publisher: CRC Press
ISBN: 1498703887
Category : Computers
Languages : en
Pages : 238

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Book Description
From the Foreword: "While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences is still in the early stages. This book, edited by Ashok Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as an outstanding resource for anyone interested in the opportunities and challenges for the machine learning community in analyzing these data sets to answer questions of urgent societal interest...I hope that this book will inspire more computer scientists to focus on environmental applications, and Earth scientists to seek collaborations with researchers in machine learning and data mining to advance the frontiers in Earth sciences." --Vipin Kumar, University of Minnesota Large-Scale Machine Learning in the Earth Sciences provides researchers and practitioners with a broad overview of some of the key challenges in the intersection of Earth science, computer science, statistics, and related fields. It explores a wide range of topics and provides a compilation of recent research in the application of machine learning in the field of Earth Science. Making predictions based on observational data is a theme of the book, and the book includes chapters on the use of network science to understand and discover teleconnections in extreme climate and weather events, as well as using structured estimation in high dimensions. The use of ensemble machine learning models to combine predictions of global climate models using information from spatial and temporal patterns is also explored. The second part of the book features a discussion on statistical downscaling in climate with state-of-the-art scalable machine learning, as well as an overview of methods to understand and predict the proliferation of biological species due to changes in environmental conditions. The problem of using large-scale machine learning to study the formation of tornadoes is also explored in depth. The last part of the book covers the use of deep learning algorithms to classify images that have very high resolution, as well as the unmixing of spectral signals in remote sensing images of land cover. The authors also apply long-tail distributions to geoscience resources, in the final chapter of the book.

Author: Bhavya Kailkhura
Publisher: Frontiers Media SA
ISBN: 2889714144
Category : Science
Languages : en
Pages : 101

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Author: Osvaldo Gervasi
Publisher: Springer Nature
ISBN: 3031371178
Category : Computers
Languages : en
Pages : 747

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Book Description
This nine-volume set LNCS 14104 – 14112 constitutes the refereed workshop proceedings of the 23rd International Conference on Computational Science and Its Applications, ICCSA 2023, held at Athens, Greece, during July 3–6, 2023. The 350 full papers and 29 short papers and 2 PHD showcase papers included in this volume were carefully reviewed and selected from a total of 876 submissions. These nine-volumes includes the proceedings of the following workshops: Advances in Artificial Intelligence Learning Technologies: Blended Learning, STEM, Computational Thinking and Coding (AAILT 2023); Advanced Processes of Mathematics and Computing Models in Complex Computational Systems (ACMC 2023); Artificial Intelligence supported Medical data examination (AIM 2023); Advanced and Innovative web Apps (AIWA 2023); Assessing Urban Sustainability (ASUS 2023); Advanced Data Science Techniques with applications in Industry and Environmental Sustainability (ATELIERS 2023); Advances in Web Based Learning (AWBL 2023); Blockchain and Distributed Ledgers: Technologies and Applications (BDLTA 2023); Bio and Neuro inspired Computing and Applications (BIONCA 2023); Choices and Actions for Human Scale Cities: Decision Support Systems (CAHSC-DSS 2023); and Computational and Applied Mathematics (CAM 2023).