Hui Yang – författare

Big Data Mining and Machine Learning in Geoscience offers a comprehensive overview of techniques and applications of data science in the geosciences. Sections cover essential, foundational concepts in data cleaning and preprocessing, thus ensuring the quality and reliability of geoscientific data. Next, the book explores dimensionality reduction methods designed to simplify high-dimensional data without losing critical information. The text covers classification and prediction techniques that enable the identification of patterns and forecasting of geological phenomena, and graphical data processing and handling of infinite stream data and time series are highlighted, along with their importance in real-time monitoring and dynamic systems analysis.In addition, the book explores advanced machine learning and deep learning methods, showcasing their transformative impact on geoscientific research. It also introduces knowledge graphs and large language models as emerging tools that enhance data integration, interpretation, and discovery. AI-driven geology is presented as a forward-looking approach that leverages artificial intelligence to revolutionize traditional geological practices, offering improved accuracy and insight. Throughout, practical examples and case studies illustrate how these technologies can be applied to solve complex problems in geoscience.Offers a systematic introduction to the fundamental framework and principles of big data mining and machine learning in geoscienceExamines machine learning and deep learning applications, along with algorithms specifically for geoscienceProvides relevant Python-based case studies for key applications

Features of statistical and operational research methods and tools being used to improve the healthcare industryWith a focus on cutting-edge approaches to the quickly growing field of healthcare, Healthcare Analytics: From Data to Knowledge to Healthcare Improvement provides an integrated and comprehensive treatment on recent research advancements in data-driven healthcare analytics in an effort to provide more personalized and smarter healthcare services. Emphasizing data and healthcare analytics from an operational management and statistical perspective, the book details how analytical methods and tools can be utilized to enhance healthcare quality and operational efficiency.Organized into two main sections, Part I features biomedical and health informatics and specifically addresses the analytics of genomic and proteomic data; physiological signals from patient-monitoring systems; data uncertainty in clinical laboratory tests; predictive modeling; disease modeling for sepsis; and the design of cyber infrastructures for early prediction of epidemic events. Part II focuses on healthcare delivery systems, including system advances for transforming clinic workflow and patient care; macro analysis of patient flow distribution; intensive care units; primary care; demand and resource allocation; mathematical models for predicting patient readmission and postoperative outcome; physician–patient interactions; insurance claims; and the role of social media in healthcare. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement also features:• Contributions from well-known international experts who shed light on new approaches in this growing area• Discussions on contemporary methods and techniques to address the handling of rich and large-scale healthcare data as well as the overall optimization of healthcare system operations• Numerous real-world examples and case studies that emphasize the vast potential of statistical and operational research tools and techniques to address the big data environment within the healthcare industry• Plentiful applications that showcase analytical methods and tools tailored for successful healthcare systems modeling and improvementThe book is an ideal reference for academics and practitioners in operations research, management science, applied mathematics, statistics, business, industrial and systems engineering, healthcare systems, and economics. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement is also appropriate for graduate-level courses typically offered within operations research, industrial engineering, business, and public health departments.

This volume offers the state-of-the-art research and developments in service science and related research, education and practice areas. It showcases emerging technology and applications in fields including healthcare, information technology, transportation, sports, logistics, and public services. Regardless of size and service, a service organization is a service system. Because of the socio-technical nature of a service system, a systems approach must be adopted to design, develop, and deliver services, aimed at meeting end users' both utilitarian and socio-psychological needs. Effective understanding of service and service systems often requires combining multiple methods to consider how interactions of people, technology, organizations, and information create value under various conditions. The papers in this volume highlight ways to approach such technical challenges in service science and are based on submissions from the 2018 INFORMS International Conference on Service Science.

Regardless of size and service, a service organization is a service system. Because of the socio-technical nature of a service system, a systems approach must be adopted to design, develop, and deliver services, aimed at meeting end users‘ both utilitarian and socio-psychological needs.

Regardless of size and service, a service organization is a service system. Because of the socio-technical nature of a service system, a systems approach must be adopted to design, develop, and deliver services, aimed at meeting end users‘ both utilitarian and socio-psychological needs.

Regardless of size and service, a service organization is a service system. Effective understanding of service and service systems often requires combining multiple methods to consider how interactions of people, technology, organizations, and information create value under various conditions.

Regardless of size and service, a service organization is a service system. Effective understanding of service and service systems often requires combining multiple methods to consider how interactions of people, technology, organizations, and information create value under various conditions.

This book reviews the development of physics-based modeling and sensor-based data fusion for optimizing medical decision making in connection with spatiotemporal cardiovascular disease processes.

This two-volume work presents state-of-the-art mathematical theories and results on infinite-dimensional dynamical systems. Inertial manifolds, approximate inertial manifolds, discrete attractors and the dynamics of small dissipation are discussed in detail. The unique combination of mathematical rigor and physical background makes this work an essential reference for researchers and graduate students in applied mathematics and physics. The main emphasis in the first volume is on the mathematical analysis of attractors and inertial manifolds. This volume deals with the existence of global attractors, inertial manifolds and with the estimation of Hausdorff fractal dimension for some dissipative nonlinear evolution equations in modern physics. Known as well as many new results about the existence, regularity and properties of inertial manifolds and approximate inertial manifolds are also presented in the first volume. The second volume will be devoted to modern analytical tools and methods in infinite-dimensional dynamical systems. ContentsAttractor and its dimension estimationInertial manifoldThe approximate inertial manifold

This two-volume work presents state-of-the-art mathematical theories and results on infinite-dimensional dynamical systems. Inertial manifolds, approximate inertial manifolds, discrete attractors and the dynamics of small dissipation are discussed in detail. The unique combination of mathematical rigor and physical background makes this work an essential reference for researchers and graduate students in applied mathematics and physics. The main emphasis in the fi rst volume is on the existence and properties for attractors and inertial manifolds. This volume highlights the use of modern analytical tools and methods such as the geometric measure method, center manifold theory in infinite dimensions, the Melnihov method, spectral analysis and so on for infinite-dimensional dynamical systems. The second volume includes the properties of global attractors, the calculation of discrete attractors, structures of small dissipative dynamical systems, and the existence and stability of solitary waves. 　 ContentsDiscrete attractor and approximate calculation Some properties of global attractor Structures of small dissipative dynamical systems Existence and stability of solitary waves

The 2016 International Conference on Artificial Intelligence Science and Technology (AIST2016) was held in Shanghai, China, from 15th to 17th July, 2016.AIST2016 aims to bring together researchers, engineers, and students to the areas of Artificial Intelligence Science and Technology. AIST2016 features unique mixed topics of artificial intelligence and application, computer and software, communication and network, information and security, data mining, and optimization.This volume consists of 101 peer-reviewed articles by local and foreign eminent scholars which cover the frontiers and state-of-art development in AI Technology.

This book describes the reliability research results and experience of BeiDou navigation satellite in engineering development. According to the characteristics of high reliability and high availability, this book discusses the reliability requirements, reliability design, reliability modeling, and reliability analysis of navigation satellite and constellation, focusing on the demonstration and decomposition of reliability requirements, constellation availability design, satellite availability design, and availability analysis. Based on the characteristics of batch production of navigation satellites, the particularity of reliability work is analyzed, and the reliability assurance works during batch production such as process reliability, data consistency comparison, storage reliability, and redundant satellite demonstration are introduced.This book is suitable for spacecraft developers, as well as postgraduates majoring in spacecraft engineering, quality, or reliability.