Bin Li - Böcker

Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation of the Moran eigenvector spatial filtering (MESF) technique. MESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in their georeferenced data analyses. Its appeal is in its simplicity, yet its implementation drawbacks include serious complexities associated with constructing an eigenvector spatial filter.

This book discusses MESF specifications for various intermediate-level topics, including spatially varying coefficients models, (non) linear mixed models, local spatial autocorrelation, space-time models, and spatial interaction models. Spatial Regression Analysis Using Eigenvector Spatial Filtering is accompanied by sample R codes and a Windows application with illustrative datasets so that readers can replicate the examples in the book and apply the methodology to their own application projects. It also includes a Foreword by Pierre Legendre.

Reviews the uses of ESF across linear regression, generalized linear regression, spatial autocorrelation measurement, and spatially varying coefficient models Includes computer code and template datasets for further modeling Provides comprehensive coverage of related concepts in spatial data analysis and spatial statistics

Protection Technologies of Ultra-High-Voltage AC Transmission Systems considers the latest research on UHV, UHV transmission line electromagnetic field, transmission line parameters, and tower structures, with a focus on protective relaying of UHV transmission systems. This book gives insights into protective relaying of UHV AC transmission systems and sheds light on the conundrum of protective relaying for the EHV systems. In addition, it elaborates on both traditional relaying and the application of new type current differential protection, distance protection and automatic reclosing, as well as protective schemes for transformers and reactors in UHV transmission systems.

This resource will serve as an important reference for technical personnel in network design and operation, as well as students and engineers in related engineering areas.

Compares new advances and trends in Ultra-High-Voltage (UHV) transmission system from a global aspect Describes UHV protection technologies Evaluates conventional protection and novel protection principles in applied and verified global systems

Bioactive Materials for Soft Tissue Regeneration covers human tissue and its classification as hard tissue such as bone and soft tissue like skin, muscle, tendon, blood vessel, nerve etc., and including organs such as heart, liver, lung. Regenerative medicine deals with both hard tissue and soft tissue regeneration and is one of the most important part of the modern medicine with significant clinical needs including general surgery, plastic surgery, burn and wound healing, cardiovascular disease treatments. Based on the authors' previous research and review of the international advances in hard tissue regeneration, this book focuses on the hard tissue regeneration using bioactive materials.Sections cover biomaterials for entire human tissue regeneration, which is key important for research and development in the field of biomedical engineering and the medical device industry. Readers will find this to be a comprehensive review of the most updated advances of the research in bioactive materials for soft tissue repair and regeneration, along with perspectives for future directions of research and development in this field.

Covers recent development of bioactive materials for soft tissue regenerationProvides basic principles for design of bioactive materials for tissue regenerationIncludes future perspectives surrounding the development of bioactive materials that will be valuable to the readers

Third-variable effect refers to the effect transmitted by third-variables that intervene in the relationship between an exposure and a response variable. Differentiating between the indirect effect of individual factors from multiple third-variables is a constant problem for modern researchers.Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS introduces general definitions of third-variable effects that are adaptable to all different types of response (categorical or continuous), exposure, or third-variables. Using this method, multiple third- variables of different types can be considered simultaneously, and the indirect effect carried by individual third-variables can be separated from the total effect. Readers of all disciplines familiar with introductory statistics will find this a valuable resource for analysis.Key Features:Parametric and nonparametric method in third variable analysisMultivariate and Multiple third-variable effect analysisMultilevel mediation/confounding analysisThird-variable effect analysis with high-dimensional data Moderation/Interaction effect analysis within the third-variable analysisR packages and SAS macros to implement methods proposed in the book

Justice apps – mobile and web-based programmes that can assist individuals with legal tasks – are being produced, improved, and accessed at an unprecedented rate. These technologies have the potential to reshape the justice system, improve access to justice, and demystify legal institutions. Using artificial intelligence techniques, apps can even facilitate the resolution of common legal disputes. However, these opportunities must be assessed in light of the many challenges associated with app use in the justice sector. These include the digital divide and other accessibility issues; the ethical challenges raised by the dehumanisation of legal processes; and various privacy, security, and confidentiality risks. Surveying the landscape of this emergent industry, this book explores the objectives, opportunities, and challenges presented by apps across all areas of the justice sector. Detailed consideration is also given to the use of justice apps in specific legal contexts, including the family law and criminal law sectors. The first book to engage with justice apps, this book will appeal to a wide range of legal scholars, students, practitioners, and policy-makers.

Justice apps – mobile and web-based programmes that can assist individuals with legal tasks – are being produced, improved, and accessed at an unprecedented rate. These technologies have the potential to reshape the justice system, improve access to justice, and demystify legal institutions. Using artificial intelligence techniques, apps can even facilitate the resolution of common legal disputes. However, these opportunities must be assessed in light of the many challenges associated with app use in the justice sector. These include the digital divide and other accessibility issues; the ethical challenges raised by the dehumanisation of legal processes; and various privacy, security, and confidentiality risks. Surveying the landscape of this emergent industry, this book explores the objectives, opportunities, and challenges presented by apps across all areas of the justice sector. Detailed consideration is also given to the use of justice apps in specific legal contexts, including the family law and criminal law sectors. The first book to engage with justice apps, this book will appeal to a wide range of legal scholars, students, practitioners, and policy-makers.

Loess is a product of aeolian deposition during the Quaternary glaciation cycles and covers approximately 6% of the Earth’s land. The Loess Plateau of China, which is home to a population of nearly three hundred million, has the thickest and most complete loess strata, where loess geohazards occur most frequently due to the weak geoenvironment and dense human activities. In recent years, the engineering geological characteristics of loess and geohazards in loess areas have gradually received increasing attention from academic researchers. This book reviews an informative collection of up-to-date literature in this field. It presents the unique features of loess and loess geohazards, and provides a strong foundation for future study via eight systematically structured chapters, e.g., origin and spatial distribution, loess landforms, microstructure, physical properties, permeability, shear strength, tensile strength, and loess geohazard. It can serve as a principal reference for researchers, practical engineers and technicians who are engaged in loess geology and surface processes, and is suitable especially for undergraduate and postgraduate students in the field of loess engineering geology.

Unlocking the Secrets of the Soil: Applying AI and Sensor Technologies for Sustainable Land Use is a comprehensive guide to the latest advances in soil characterization. This book explores the role of sensors and artificial intelligence in improving soil management practices and supporting sustainable land use. Through detailed descriptions of sensor and AI-based techniques for measuring physical, chemical, and biological soil properties, readers will gain a deep understanding of the tools and technologies available for soil characterization. The book also covers the latest machine learning algorithms and image processing for analyzing soil data and making informed decisions about land use. Unlocking the Secrets of the Soil is an essential resource for researchers, practitioners, and students interested in the intersection of AI and sensor technologies for soil management and sustainability.Provides an integration of AI and Sensor technologiesHighlights the importance of sustainable land use and the role that modern technologies can play in achieving this goalPresents an interdisciplinary approach, drawing on expertise from various fields such as agriculture, environmental science, and computer science

Spatial Autocorrelation: A Fundamental Property of Geospatial Phenomena offers a state-of-the-art exploration of one of the most pivotal spatial analysis concepts. Beginning with foundational theories and clear definitions, it sets out the concepts and basic theory of spatial autocorrelation through elaborated conceptualizations and practical examples. In-depth case studies reveal the pervasive influence of spatial patterns in scientific inquiry while anticipating emerging research and innovative techniques. It offers practical methods for quantifying spatial autocorrelation, complete with step-by-step instructions and real-world examples.Spatial Autocorrelation equips graduate students, researchers, and professionals with the knowledge and tools to confidently comprehend, navigate, and apply spatial analysis in their respective domains, making it an ideal companion for technical reference books, and a vital addition to the libraries of any discipline utilizing spatial analysis.Explores a fundamental geospatial concept via a blend of multidisciplinary topicsProvides an educational focus in a conceptually friendly mannerOffers a progressive, iterative layout, spanning basic to advanced conceptsEmphasizes novel as well as benchmark empirical and simulation examplesCovers spatial autocorrelation in various disciplines, being nascent in some of them

Third-variable effect refers to the effect transmitted by third-variables that intervene in the relationship between an exposure and a response variable. Differentiating between the indirect effect of individual factors from multiple third-variables is a constant problem for modern researchers.Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS introduces general definitions of third-variable effects that are adaptable to all different types of response (categorical or continuous), exposure, or third-variables. Using this method, multiple third- variables of different types can be considered simultaneously, and the indirect effect carried by individual third-variables can be separated from the total effect. Readers of all disciplines familiar with introductory statistics will find this a valuable resource for analysis.Key Features:Parametric and nonparametric method in third variable analysisMultivariate and Multiple third-variable effect analysisMultilevel mediation/confounding analysisThird-variable effect analysis with high-dimensional data Moderation/Interaction effect analysis within the third-variable analysisR packages and SAS macros to implement methods proposed in the book

Loess is a product of aeolian deposition during the Quaternary glaciation cycles and covers approximately 6% of the Earth’s land. The Loess Plateau of China, which is home to a population of nearly three hundred million, has the thickest and most complete loess strata, where loess geohazards occur most frequently due to the weak geoenvironment and dense human activities. In recent years, the engineering geological characteristics of loess and geohazards in loess areas have gradually received increasing attention from academic researchers. This book reviews an informative collection of up-to-date literature in this field. It presents the unique features of loess and loess geohazards, and provides a strong foundation for future study via eight systematically structured chapters, e.g., origin and spatial distribution, loess landforms, microstructure, physical properties, permeability, shear strength, tensile strength, and loess geohazard. It can serve as a principal reference for researchers, practical engineers and technicians who are engaged in loess geology and surface processes, and is suitable especially for undergraduate and postgraduate students in the field of loess engineering geology.

With the aim to sequentially determine optimal allocations across a set of assets, Online Portfolio Selection (OLPS) has significantly reshaped the financial investment landscape. Online Portfolio Selection: Principles and Algorithms supplies a comprehensive survey of existing OLPS principles and presents a collection of innovative strategies that leverage machine learning techniques for financial investment.The book presents four new algorithms based on machine learning techniques that were designed by the authors, as well as a new back-test system they developed for evaluating trading strategy effectiveness. The book uses simulations with real market data to illustrate the trading strategies in action and to provide readers with the confidence to deploy the strategies themselves. The book is presented in five sections that: Introduce OLPS and formulate OLPS as a sequential decision taskPresent key OLPS principles, including benchmarks, follow the winner, follow the loser, pattern matching, and meta-learningDetail four innovative OLPS algorithms based on cutting-edge machine learning techniquesProvide a toolbox for evaluating the OLPS algorithms and present empirical studies comparing the proposed algorithms with the state of the artInvestigate possible future directionsComplete with a back-test system that uses historical data to evaluate the performance of trading strategies, as well as MATLAB® code for the back-test systems, this book is an ideal resource for graduate students in finance, computer science, and statistics. It is also suitable for researchers and engineers interested in computational investment.Readers are encouraged to visit the authors’ website for updates: http://olps.stevenhoi.org.

With the aim to sequentially determine optimal allocations across a set of assets, Online Portfolio Selection (OLPS) has significantly reshaped the financial investment landscape. Online Portfolio Selection: Principles and Algorithms supplies a comprehensive survey of existing OLPS principles and presents a collection of innovative strategies that leverage machine learning techniques for financial investment.The book presents four new algorithms based on machine learning techniques that were designed by the authors, as well as a new back-test system they developed for evaluating trading strategy effectiveness. The book uses simulations with real market data to illustrate the trading strategies in action and to provide readers with the confidence to deploy the strategies themselves. The book is presented in five sections that: Introduce OLPS and formulate OLPS as a sequential decision taskPresent key OLPS principles, including benchmarks, follow the winner, follow the loser, pattern matching, and meta-learningDetail four innovative OLPS algorithms based on cutting-edge machine learning techniquesProvide a toolbox for evaluating the OLPS algorithms and present empirical studies comparing the proposed algorithms with the state of the artInvestigate possible future directionsComplete with a back-test system that uses historical data to evaluate the performance of trading strategies, as well as MATLAB® code for the back-test systems, this book is an ideal resource for graduate students in finance, computer science, and statistics. It is also suitable for researchers and engineers interested in computational investment.Readers are encouraged to visit the authors’ website for updates: http://olps.stevenhoi.org.

Elgar Advanced Introductions are stimulating and thoughtful introductions to major fields in the social sciences, business and law, expertly written by the world’s leading scholars. Designed to be accessible yet rigorous, they offer concise and lucid surveys of the substantive and policy issues associated with discrete subject areas.This Advanced Introduction provides a critical review and discussion of research concerning spatial statistics, differentiating between it and spatial econometrics, to answer a set of core questions covering the geographic-tagging-of-data origins of the concept and its theoretical underpinnings, conceptual advances, and challenges for future scholarly work. It offers a vital tool for understanding spatial statistics and surveys how concerns about violating the independent observations assumption of statistical analysis developed into this discipline.Key Features:A concise overview of spatial statistics theory and methods, looking at parallel developments in geostatistics and spatial econometrics, highlighting the eclipsing of centography and point pattern analysis by geostatistics and spatial autoregression, and the emergence of local analysisContemporary descriptions of popular geospatial random variables, emphasizing one- and two-parameter spatial autoregression specifications, and Moran eigenvector spatial filtering coupled with a broad coverage of statistical estimation techniquesA detailed articulation of a spatial statistical workflow conceptualizationThe helpful insights from empirical applications of spatial statistics in agronomy, criminology, demography, economics, epidemiology, geography, remotely sensed data, urban studies, and zoology/botany, will make this book a useful tool for upper-level students in these disciplines.

Elgar Advanced Introductions are stimulating and thoughtful introductions to major fields in the social sciences, business and law, expertly written by the world’s leading scholars. Designed to be accessible yet rigorous, they offer concise and lucid surveys of the substantive and policy issues associated with discrete subject areas.This Advanced Introduction provides a critical review and discussion of research concerning spatial statistics, differentiating between it and spatial econometrics, to answer a set of core questions covering the geographic-tagging-of-data origins of the concept and its theoretical underpinnings, conceptual advances, and challenges for future scholarly work. It offers a vital tool for understanding spatial statistics and surveys how concerns about violating the independent observations assumption of statistical analysis developed into this discipline.Key Features:A concise overview of spatial statistics theory and methods, looking at parallel developments in geostatistics and spatial econometrics, highlighting the eclipsing of centography and point pattern analysis by geostatistics and spatial autoregression, and the emergence of local analysisContemporary descriptions of popular geospatial random variables, emphasizing one- and two-parameter spatial autoregression specifications, and Moran eigenvector spatial filtering coupled with a broad coverage of statistical estimation techniquesA detailed articulation of a spatial statistical workflow conceptualizationThe helpful insights from empirical applications of spatial statistics in agronomy, criminology, demography, economics, epidemiology, geography, remotely sensed data, urban studies, and zoology/botany, will make this book a useful tool for upper-level students in these disciplines.

The aim of this book is to furnish the reader with a rigorous and detailed exposition of the concept of control parametrization and time scaling transformation. This book is intended as reference for researchers in mathematics, engineering, and other sciences, graduate students and practitioners who apply optimal control methods in their work.

The aim of this book is to furnish the reader with a rigorous and detailed exposition of the concept of control parametrization and time scaling transformation. This book is intended as reference for researchers in mathematics, engineering, and other sciences, graduate students and practitioners who apply optimal control methods in their work.

Therefore, it is necessary to investigate the dynamic stability and control of tripped and untripped vehicle rollover so as to avoid vehicle rollover accidents.In this book, different dynamic models are used to describe the vehicle rollover under both untripped and special tripped situations.

This book constitutes the refereed proceedings of the 17 International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2016, held in Yangzhou, China, in October 2016.

This book constitutes the refereed proceedings of the 14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013, held in Hefei, China, in October 2013. The 76 revised full papers presented were carefully reviewed and selected from more than 130 submissions. These papers provided a valuable collection of latest research outcomes in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, neural networks, probabilistic modelling, swarm intelligent, multi-objective optimisation, and practical applications in regression, classification, clustering, biological data processing, text processing, video analysis, including a number of special sessions on emerging topics such as adaptation and learning multi-agent systems, big data, swarm intelligence and data mining, and combining learning and optimisation in intelligent data engineering.

This book offers a broad overview of the concepts and research findings in immunometabolism. The immune system is made up of numerous different cell types, pathways, and components that must be able to respond rapidly to a pathogen or cancer, but must also remain quiescent in the absence of challenges. Immune cells rely on metabolic pathways to adapt to changing environments and stimuli. Additionally, these cells can be modified in function or fate by fluctuations in available nutrients.The chapters in this book describe ways in which immune cells utilize and are regulated by metabolic pathways. Topics include how immune-cell metabolism shapes immune homeostasis, and how dysregulation of these pathways can lead to immune disorders. In different contexts, such as a tumor microenvironment, immune-cell function and identity may be modified not only by cytokines and checkpoint molecules, but also by nutrient availability and other metabolic stimuli. Transcriptional reprogramming confers many of the changes in immune cell metabolism that are seen when a T-cell, for example, undergoes activation or functional adaptation to different environments. Lastly, immune cells can destructively or protectively participate in human metabolic homeostasis or disorders.This book summarizes immune-metabolism from a variety of different perspectives, including the ways in which metabolic cues, pathways, and requirements of immune cells change in conditions of homeostasis and activation. The exploration of the significance of metabolic checkpoints and other cues, particularly in the context of cancer and immune disorders, may form the foundation for the development of therapeutics.

This book offers a broad overview of the concepts and research findings in immunometabolism. The immune system is made up of numerous different cell types, pathways, and components that must be able to respond rapidly to a pathogen or cancer, but must also remain quiescent in the absence of challenges. Immune cells rely on metabolic pathways to adapt to changing environments and stimuli. Additionally, these cells can be modified in function or fate by fluctuations in available nutrients.The chapters in this book describe ways in which immune cells utilize and are regulated by metabolic pathways. Topics include how immune-cell metabolism shapes immune homeostasis, and how dysregulation of these pathways can lead to immune disorders. In different contexts, such as a tumor microenvironment, immune-cell function and identity may be modified not only by cytokines and checkpoint molecules, but also by nutrient availability and other metabolic stimuli. Transcriptional reprogramming confers many of the changes in immune cell metabolism that are seen when a T-cell, for example, undergoes activation or functional adaptation to different environments. Lastly, immune cells can destructively or protectively participate in human metabolic homeostasis or disorders.This book summarizes immune-metabolism from a variety of different perspectives, including the ways in which metabolic cues, pathways, and requirements of immune cells change in conditions of homeostasis and activation. The exploration of the significance of metabolic checkpoints and other cues, particularly in the context of cancer and immune disorders, may form the foundation for the development of therapeutics.

This book addresses selected practical applications and recent developments in the areas of quantitative financial modeling in derivatives instruments, some of which are from the authors' own research and practice. It is written from the viewpoint of financial engineers or practitioners, and, as such, it puts more emphasis on the practical applications of financial mathematics in the real market than the mathematics itself with precise (and tedious) technical conditions. It attempts to combine economic insights with mathematics and modeling so as to help the reader to develop intuitions.Among the modeling and the numerical techniques presented are the practical applications of the martingale theories, such as martingale model factory and martingale resampling and interpolation. In addition, the book addresses the counterparty credit risk modeling, pricing, and arbitraging strategies from the perspective of a front office functionality and a revenue center (rather than merely a risk management functionality), which are relatively recent developments and are of increasing importance. It also discusses various trading structuring strategies and touches upon some popular credit/IR/FX hybrid products, such as PRDC, TARN, Snowballs, Snowbears, CCDS, and credit extinguishers.While the primary scope of this book is the fixed-income market (with further focus on the interest rate market), many of the methodologies presented also apply to other financial markets, such as the credit, equity, foreign exchange, and commodity markets.