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Books in Physical sciences and engineering

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    • Deep Learning for Cardiac Signal Analysis in Robotic Applications

      • 1st Edition
      • Kapil Gupta + 1 more
      • English
      Deep Learning for Cardiac Signal Analysis in Robotic Applications delves into the transformative role of artificial intelligence in enhancing robotic-assisted cardiovascular procedures. Addressing the complexities of heart signal interpretation amidst the dynamic environment of cardiac surgery, this book meets the critical need for a comprehensive resource that bridges deep learning advances with practical surgical applications. It responds to the challenge of understanding intricate bio-signals, such as ECG, VCG, and BCG, by providing clear explanations, case studies, and methodological insights tailored to improve surgical precision, safety, and patient outcomes. The book is organized into three parts, starting with the fundamentals of cardiac signals and deep learning. It introduces key heart modalities, including the physiological underpinnings and challenges of signals like ECG and BCG, followed by an overview of deep learning architectures relevant to signal processing. Pre-processing and feature extraction techniques are detailed to prepare readers for advanced analysis. Part II focuses on AI-enhanced cardiac signal analysis, covering arrhythmia detection, myocardial ischemia diagnostics, hypertension monitoring via BCG, and explainable AI approaches for fetal arrhythmia monitoring. The final section integrates AI with robotic cardiac surgery, addressing real-time signal integration, AI-guided intervention precision, intraoperative decision support, postoperative monitoring, and future trends in cardiac AI and robotic-assisted surgery.This book is an invaluable resource for engineering students and academicians seeking to deepen their understanding of AI applications in healthcare. It equips readers with practical knowledge to tackle challenges in cardiac signal processing and robotic application, fostering interdisciplinary expertise that spans biomedical engineering, computer science, and clinical practice. This book not only advances academic research but also supports innovation in developing intelligent surgical systems and improving patient care.

    • Data Compression for Data Mining Algorithms

      • 1st Edition
      • Xiaochun Wang
      • English
      Data Compression for Data Mining Algorithms tackles the important problems in the design of more efficient data mining algorithms by way of data compression techniques and provides the first systematic and comprehensive description of the relationships between data compression mechanisms and the computations involved in data mining algorithms. Data mining algorithms are powerful analytical techniques used across various disciplines, including business, engineering, and science. However, in the big data era, tasks such as association rule mining and classification often require multiple scans of databases, while clustering and outlier detection methods typically depend on Euclidean distance for similarity measures, leading to high computational costs.Data Compression for Data Mining Algorithms addresses these challenges by focusing on the scalarization of data mining algorithms, leveraging data compression techniques to reduce dataset sizes and applying information theory principles to minimize computations involved in tasks such as feature selection and similarity computation. The book features the latest developments in both lossless and lossy data compression methods and provides a comprehensive exposition of data compression methods for data mining algorithm design from multiple points of view.Key discussions include Huffman coding, scalar and vector quantization, transforms, subbands, wavelet-based compression for scalable algorithms, and the role of neural networks, particularly deep learning, in feature selection and dimensionality reduction. The book’s contents are well-balanced for both theoretical analysis and real-world applications, and the chapters are well organized to compose a solid overview of the data compression techniques for data mining. To provide the reader with a more complete understanding of the material, projects and problems solved with Python are interspersed throughout the text.

    • Biohydrometallurgy of Rare Earth Ores

      • 1st Edition
      • Hongbo Zhao + 3 more
      • English
      Biohydrometallurgy of Rare Earth Ores offers an in-depth exploration of innovative bioleaching techniques for the extraction of rare earth elements that is critical for various high-tech applications. The book begins with foundational concepts in bioleaching, explaining how microorganisms and their metabolites can facilitate the extraction of REEs from ores. Further sections examine different biological approaches, including the use of native and genetically improved microorganisms, and highlight the role of coordination chemistry in enhancing leaching processes. The text also delves into comparative analyses of chemical versus bioleaching methods, emphasizing the advantages of biological techniques in terms of efficiency and environmental sustainability.Addit... the book addresses the environmental impacts of bioleaching practices, providing a holistic view of the sustainability of these methods while also detailing the recovery processes of REEs from bioleaching solutions and exploring various methods such as inorganic and organic precipitation, biosorption, and the utilization of waste-derived metabolites. It will serve as a valuable resource for researchers, practitioners, and industry professionals interested in the sustainable extraction of rare earth elements.

    • AI Platforms as Global Governance for the Health Ecosystem

      The Future's Global Hospital
      • 1st Edition
      • Dominique J. Monlezun
      • English
      AI Platforms as Global Governance for the Health Ecosystem: The Future’s Global Hospital provides comprehensive and actionable approaches for readers to understand and optimize responsible AI to create global governance for the healthcare ecosystem. The book explores how AI platforms can transform hospitals and clinical practice by digitally unifying patients, providers, and payors, advancing healthcare for all. Users will find content that defines and explains the main hurdles and technical innovations in responsibly governing AI platforms for efficient, equitable, and sustainable global healthcare.Additiona... sections delve into the history, science, politics, economics, ethics, policy, and future of these AI platforms, and how governance efforts can work toward the common good. Written from the first-hand perspective of a practicing physician-data scientist and AI ethicist, the book maps out how to develop successful governance for AI platforms.

    • Per- and Polyfluoroalkyl Substances (PFAS) as Environmental Contaminants

      Materials and Technologies for Advancements in Water and Soil Remediation
      • 1st Edition
      • Dimitrios A Giannakoudakis + 1 more
      • English
      Per- and Polyfluoroalkyl Substances (PFAS) as Environmental Contaminants: Materials and Technologies for Advancements in Water and Soil Remediation offers a comprehensive examination of the challenges posed by PFAS contamination and the innovative solutions available for remediation. The book delves into the chemical properties, toxicity mechanisms, and environmental persistence of PFAS while also exploring advanced remediation technologies such as adsorption, chemical oxidation, and phytoremediation. By consolidating current knowledge and showcasing new approaches, this comprehensive resource equips readers with the tools necessary to address PFAS contamination and effectively advance research and practice in environmental health and safety.In addition, users will find updates on emerging materials like Metal-Organic Frameworks and activated carbons that enhance remediation efforts, providing practical insights and case studies throughout.

    • Understanding Models Developed with AI

      Including Applications with Python and MATLAB Code
      • 1st Edition
      • Ömer Faruk Ertuğrul + 2 more
      • English
      Understanding Models Developed by AI: Including Applications with Python and MATLAB Code is a comprehensive guide on the intricacies of AI models and their real-world applications. The book demystifies complex AI methodologies by providing clear explanations and practical examples that are reinforced with Python and MATLAB program codes. Its content structure emphasizes a practical, applications-driven approach to understanding AI models, with hands-on coding examples throughout each chapter. Readers will find the tools they need to build AI models, along with the knowledge to make these models accessible and interpretable to stakeholders, thus fostering trust and reliability in AI systems.As the primary issues with the adoption of AI/ML models are reliability, transparency, interpretation of results, and bias (data and algorithm) management, this resource give researchers and developers what they need to be able to not only implement AI models, but also interpret and explain them. This is crucial in industries where decision-making processes must be transparent and understandable.

    • Integrative Sensing Strategies for Disaster Management

      • 1st Edition
      • Danlin Yu + 1 more
      • English
      Integrative Sensing Strategies for Disaster Management explores the synergy between airborne remote sensing and social data in addressing disaster management. The book provides a framework for leveraging diverse data sources to enhance response and resilience. Detailed chapters cover the fundamentals of remote sensing, data integration techniques, and ethical implications, showcasing practical case studies in urban flooding, air quality monitoring, and pandemic evaluation. The book is an essential resource for postgraduates, PhD students, researchers, and professors in Earth observation and disaster management.Users will find this book to be a great resource for advancing their understanding of integrated sensing technologies, including current challenges and emerging trends, and tactics on how to implement innovative solutions.

    • Analytical Chemistry for Environmental Solutions

      Elements of Change
      • 1st Edition
      • Rohit Bhatia + 1 more
      • English
      Analytical Chemistry for Environmental Solutions: Elements of Change provides in-depth coverage of cutting-edge analytical techniques, emerging trends like AI-powered data analysis, real-time monitoring, and the global impact of environmental issues, aligning with sustainability goals such as clean water, climate action, and sustainable cities. The book includes practical case studies, real-world data analysis, and a comprehensive instructor's manual, making it suitable for both academic and professional audiences. Its focus on global perspectives and cultural sensitivity ensures it resonates across diverse regions, while interactive learning tools and digital resources enhance the educational experience.This edition, along with a sturdy collection of interactive ancillary resources for both students and instructors, delivers accessible, engaging, and comprehensive resources for readers, enhancing both the understanding and practical applications of analytical chemistry in environmental science. Designed to equip students with problem-solving, critical thinking, and data analysis skills, this textbook is an ideal resource for the next generation of environmental scientists, policymakers, and sustainability experts.

    • Nonlinear Process Modeling in Chemical and Particle Systems

      • 1st Edition
      • Lakshmanan Rajendran + 1 more
      • English
      Nonlinear Process Modeling in Chemical and Particle Systems delivers a comprehensive guide to the analysis and application of nonlinear models in chemical engineering. Addressing the growing demand for simulation-driven design, process optimization, and sustainable innovation, the book integrates nonlinear ordinary and partial differential equations with real-world chemical and particle system applications. Readers are introduced to fundamental principles of nonlinear transport, reaction kinetics, and multiphase systems, followed by advanced treatments of particle dynamics, electrochemical processes, and environmental modeling. Each chapter combines theoretical underpinnings with detailed methods, computational strategies, and practical case studies, ranging from catalytic reactor dynamics to biosensor design and CO₂ capture technologies. The inclusion of both semi-analytical and numerical approaches, alongside predictive analytics and machine learning, ensures that the book speaks equally to mathematical rigor and industrial relevance.Written for graduate students, researchers, and practicing engineers, this resource provides the skills to model, analyze, and optimize nonlinear processes across a range of chemical engineering applications. Its balance of theory, methods, and applied insights makes it an indispensable reference for advancing research, teaching, and professional practice in the field.

    • Advanced Molecular Magnetism

      • 1st Edition
      • Roman Boča
      • English
      Advanced Molecular Magnetism provides a rigorous overview of the magnetic properties of molecular and extended inorganic systems. The book begins by introducing the fundamentals of magnetic data recording and analysis, establishing exchange interactions as a foundational concept before progressing to more advanced topics. Key areas of focus include exchange interactions involving both d- and f-block elements, the role of magnetic anisotropy, single-molecule magnets, and spin crossover phenomena. The text emphasizes the correlation of magnetic property analysis with complementary techniques such as UV-Vis and electron paramagnetic resonance (EPR) spectroscopy. A thorough overview of electronic energy levels in transition metal complexes is provided, covering electronic terms, multiplets, and Zeeman splitting. The interface between quantum mechanics and macroscopic thermodynamic properties is explored through statistical thermodynamics. The book reviews the major types of magnetic materials—diamagneti... paramagnetic, ferromagnetic, and antiferromagnetic—wi... a focus on their underlying principles and real-world examples. Methods for deriving magnetochemical formulae for Curie paramagnets, zero-field splitting systems, T- and E-term systems, and pure multiplet systems are clearly presented, alongside practical guidance for magnetic data collection and analysis. Special attention is given to the magnetism of f-elements and the unique properties of single-molecule magnets, as well as to the correct description of many-electron states in both free atoms and those influenced by crystal fields. The Zeeman effect is introduced, followed by in-depth chapters on paramagnetic materials exhibiting zero-field splitting and exchange interactions of isotropic and anisotropic kind. Worked examples show experimental data for different kinds of interactions in transition metal complexes along with their modelling using advanced theoretical tools. The synergy between molecular magnetism, electron spectroscopy, and EPR is also highlighted throughout. One important objective of this book is to help readers with more marginal backgrounds in quantum mechanics understand the current state of the art of molecular magnetism. Advanced Molecular Magnetism is written primarily for inorganic, physical or computational/theore... chemists, as well as being of use to condensed matter physicists and materials scientists with an interest in the magnetic properties of transition metal and lanthanide complexes.

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