This book gives a brief review of current development models and governance of urban sharing platforms, and looks into the economic efficiency of a novel market transaction model of sharing economy, which has been accelerated by high-density urban population and the Internet technology. With an aim to solve current problems featuring excessive competition, waste of resources, security risks, and unfair competition, this book delves into the two governance models in accommodation sharing platforms and bike and car sharing platforms and puts forward a multi-dimensional collaborative governance model that involves the participation of enterprises, the government, and the community. Under such a model, the platforms may utilize their own key technologies to implement supervision and solicit feedback; the government may resort to tax regulation and reallocating shared space to mitigate the negative externality effect and promote fair competition; and the community, as the basic unit of a city, may play its part through on-site participation and real-time feedback.

This book interprets China's development and the opportunities it can leverage in the context of unprecedented change and the COVID-19 pandemic. It aims to provide case studies and insights for researchers and offer authoritative information for those interested in China’s development. In this book, 20 distinguished experts and researchers contribute their wisdom around five topics: science and technology innovation, ecological environment, the global and Chinese economies, high-tech industry development, and international and Chinese media research.

This book explores the experiences and emotional expression of 30 people Living with HIV/AIDS (PLWHA) using qualitative research methods such as "illness narratives," and analyzes the dilemmas of "sicknesses of the society" including "Acquired Needs Deficiency" Syndrome, "Acquired Expectation Insufficiency" Syndrome, and "Acquired Punishment" Syndrome at the micro, meso and macro levels, so as to investigate higher-intensity negative emotions.In turn, the book draws on the perspectives of conflict and game, structure and function, and system and interaction, in order to propose a dynamic mechanism of emotion and expression, and argues that these negative emotions can be transformed, strengthened and presented through defense mechanisms such as suppression and attribution, which will influence social institutions at the micro, meso and macro levels and even possibly bring about positive changes in the social structure.

Methods for detecting protein-protein interactions (PPIs) have given researchers a global picture of protein interactions on a genomic scale. ""Biological Data Mining in Protein Interaction Networks"" explains bioinformatic methods for predicting PPIs, as well as data mining methods to mine or analyze various protein interaction networks. A defining body of research within the field, this book discovers underlying interaction mechanisms by studying intra-molecular features that form the common denominator of various PPIs.

This book explores key techniques and methods in electromagnetic compatibility management, analysis, design, improvement and test verification for spacecraft. The first part introduces the general EMC technology of spacecraft, the electromagnetic interference control method and management of electromagnetic compatibility. The second part discusses the EMC prediction analysis technique and its application in spacecraft, while the third presents the EMC design of spacecraft modules and typical equipment. The final two parts address spacecraft magnetic design testing technologies and spacecraft testing technologies. The book also covers the program control test process, the special power control unit (PCU), electric propulsion, PIM test and multipaction testing for spacecraft, making it a valuable resource for researchers and engineers alike.

The book focuses on the current research of the relation between protein phosphorylation and meat quality, reviews the influence mechanism of protein phosphorylation on meat quality, and summarizes the improvement of meat quality by regulating protein phosphorylation. It could help to clarify some dilemmas and encourage further research in this field, aiming for effective application of protein phosphorylation in meat quality in the near future. The book is written for researchers and graduate students in the field of meat science, food chemistry and molecular biology etc.

This book is an up-to-date text covering topics in utilizing hydrogen bonding for constructing functional architectures and supramolecular materials. The first chapter addresses the control of photo-induced electron and energy transfer. The second chapter summarizes the formation of nano-porous materials. The following two chapters introduce self-assembled gels, many of which exhibit unique functions. Other chapters cover the advances in supramolecular liquid crystals and the versatility of hydrogen bonding in tuning/improving the properties and performance of materials. This book is designed to bring together in a single volume the most important and active fields of hydrogen bonding strategy for designing supramolecular materials. The book will be a valuable resource for graduates and researchers working in the fields of supramolecular chemistry and materials sciences. Zhan-Ting Li, PhD, is a Professor of Organic Chemistry at the Department of Chemistry, Fudan University, China Li-Zhu Wu, PhD, is a Professor of Organic Chemistry at the Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, China

This book addresses the fundamental theory and key technologies of narrowband and broadband mobile communication systems specifically for railways. It describes novel relaying schemes that meet the different design criteria for railways and discusses the applications of signal classification techniques as well as offline resource scheduling as a way of advancing rail practice. Further, it introduces Novel Long Term Evolution for Railway (LTE-R) network architecture, the Quality of Service (QoS) requirement of LTE-R and its performance evaluation and discusses in detail security technologies for rail-dedicated mobile communication systems. The advanced research findings presented in the book are all based on high-speed railway measurement data, which offer insights into the propagation mechanisms and corresponding modeling theory and approaches in unique railway scenarios.It is a valuable resource for researchers, engineers and graduate students in the fields of rail traffic systems, telecommunication and information systems.

This book systematically introduces the nonlinear adiabatic evolution theory of quantum many-body systems. The nonlinearity stems from a mean-field treatment of the interactions between particles, and the adiabatic dynamics of the system can be accurately described by the nonlinear Schroedinger equation. The key points in this book include the adiabatic condition and adiabatic invariant for nonlinear system; the adiabatic nonlinear Berry phase; and the exotic virtual magnetic field, which gives the geometric meaning of the nonlinear Berry phase. From the quantum-classical correspondence, the linear and nonlinear comparison, and the single particle and interacting many-body difference perspectives, it shows a distinct picture of adiabatic evolution theory. It also demonstrates the applications of the nonlinear adiabatic evolution theory for various physical systems. Using simple models it illustrates the basic points of the theory, which are further employed for the solution of complex problems of quantum theory for many-particle systems. The results obtained are supplemented by numerical calculations, presented as tables and figures.

This book reviews cutting-edge developments in neural signalling processing (NSP), systematically introducing readers to various models and methods in the context of NSP. Neuronal Signal Processing is a comparatively new field in computer sciences and neuroscience, and is rapidly establishing itself as an important tool, one that offers an ideal opportunity to forge stronger links between experimentalists and computer scientists. This new signal-processing tool can be used in conjunction with existing computational tools to analyse neural activity, which is monitored through different sensors such as spike trains, local filed potentials and EEG. The analysis of neural activity can yield vital insights into the function of the brain. This book highlights the contribution of signal processing in the area of computational neuroscience by providing a forum for researchers in this field to share their experiences to date.

Fractal analysis has rapidly become an important field in materials science and engineering with broad applications to theoretical analysis and quantitative description of microstructures of materials. Fractal methods have thus far shown great potential in engineering applications in quantitative microscopic analysis of materials using commercial microscopes.
This book attempts to introduce the fundamentals and the basis methods of fractal description of microstructures in combination with digital imaging and computer technologies. Basic concepts are given in the form of mathematical expressions. Detailed algorithms in practical applications are also provided. Fractal measurement, error analysis and fractal description of cluster growth, thin films and surfaces are emphasized in this book.
Image-Based Fractal Description of Microstructures provides a comprehensive approach to materials characterization by fractal from theory to application.

Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.

Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep learning technology can be a very good candidate for improving sensing capabilities.In this edited volume, we aim to narrow the gap between humans and machines by showcasing various deep learning applications in the area of sensing. The book will cover the fundamentals of deep learning techniques and their applications in real-world problems including activity sensing, remote sensing and medical sensing. It will demonstrate how different deep learning techniques help to improve the sensing capabilities and enable scientists and practitioners to make insightful observations and generate invaluable discoveries from different types of data.

This book covers the advances in the studies of hydrogen-bonding-driven supramolecular systems made over the past decade. It is divided into four parts, with the first introducing the basics of hydrogen bonding and important hydrogen bonding patterns in solution as well as in the solid state. The second part covers molecular recognition and supramolecular structures driven by hydrogen bonding. The third part introduces the formation of hollow and giant macrocycles directed by hydrogen bonding, while the last part summarizes hydrogen bonded supramolecular polymers. This book is designed to bring together in a single volume the many important aspects of hydrogen bonding supramolecular chemistry and will be a valuable resource for graduates and researchers working in supramolecular and related sciences. Zhan-Ting Li, PhD, is a Professor of Organic Chemistry at the Department of Chemistry, Fudan University, China. Li-Zhu Wu, PhD, is a Professor of Organic Chemistry at the Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, China.

'This book is suitable for courses at the MBA core level, PGDIBO students who are pursuing International Business at PG level, MS in supply chain management level, upper undergraduate level, and also suitable for executive education. The book is very constructive for managers involved in creating, optimizing or redesigning a supply chain. Readers after reading would unquestionably have say to, the supply chain decision-making process and build academic orientation in logistics.'Global Journal of Enterprise Information SystemThis book, developed in collaboration with the Rutgers Center for Supply Chain Management and based upon research projects conducted with over 100 participating corporations, combines theory and practice in presenting the concepts necessary for strategic implementation of supply chain management techniques in a global environment. Coauthored by top teaching and research faculty and a senior industry executive, this academic/industry partnership ensures the relevance of the text in terms of both practical application and academic rigor.This book introduces students to the key drivers of supply chain performance, including demand forecasting, sales and operations planning, inventory control, capacity analysis, transportation models, supply chain integration, and project management and risk analysis. It is enhanced by real-life examples and case studies as well as strategies from best practices and a focus on social and economic impact. The content reaches beyond a traditional operations management text and draws on the extensive experience of the authors conducting industry projects through the Rutgers Center for Supply Chain Management. The input of senior business executives has been an invaluable asset in presenting a balanced knowledge of both quantitative models and qualitative insights.This book is suitable for courses at the MBA core level, MS in supply chain management level, upper undergraduate level, and also suitable for executive education.

Biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. This has resulted in a flood of biological and clinical data from genomic and protein sequences, DNA microarrays, protein interactions, biomedical images, to disease pathways and electronic health records. To exploit these data for discovering new knowledge that can be translated into clinical applications, there are fundamental data analysis difficulties that have to be overcome. Practical issues such as handling noisy and incomplete data, processing compute-intensive tasks, and integrating various data sources, are new challenges faced by biologists in the post-genome era. This book will cover the fundamentals of state-of-the-art data mining techniques which have been designed to handle such challenging data analysis problems, and demonstrate with real applications how biologists and clinical scientists can employ data mining to enable them to make meaningful observations and discoveries from a wide array of heterogeneous data from molecular biology to pharmaceutical and clinical domains.

Radiomics and Radiogenomics: Technical Basis and Clinical Applications provides a first summary of the overlapping fields of radiomics and radiogenomics, showcasing how they are being used to evaluate disease characteristics and correlate with treatment response and patient prognosis. It explains the fundamental principles, technical bases, and clinical applications with a focus on oncology. The book's expert authors present computational approaches for extracting imaging features that help to detect and characterize disease tissues for improving diagnosis, prognosis, and evaluation of therapy response. This book is intended for audiences including imaging scientists, medical physicists, as well as medical professionals and specialists such as diagnostic radiologists, radiation oncologists, and medical oncologists. Features Provides a first complete overview of the technical underpinnings and clinical applications of radiomics and radiogenomics Shows how they are improving diagnostic and prognostic decisions with greater efficacy Discusses the image informatics, quantitative imaging, feature extraction, predictive modeling, software tools, and other key areas Covers applications in oncology and beyond, covering all major disease sites in separate chapters Includes an introduction to basic principles and discussion of emerging research directions with a roadmap to clinical translation

This book explains deep learning concepts and derives semi-supervised learning and nuclear learning frameworks based on cognition mechanism and Lie group theory. Lie group machine learning is a theoretical basis for brain intelligence, Neuromorphic learning (NL), advanced machine learning, and advanced artifi cial intelligence. The book further discusses algorithms and applications in tensor learning, spectrum estimation learning, Finsler geometry learning, Homology boundary learning, and prototype theory. With abundant case studies, this book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artifi cial intelligence, machine learning, automation, mathematics, management science, cognitive science, financial management, and data analysis. In addition, this text can be used as the basis for teaching the principles of machine learning. Li Fanzhang is professor at the Soochow University, China. He is director of network security engineering laboratory in Jiangsu Province and is also the director of the Soochow Institute of industrial large data. He published more than 200 papers, 7 academic monographs, and 4 textbooks. Zhang Li is professor at the School of Computer Science and Technology of the Soochow University. She published more than 100 papers in journals and conferences, and holds 23 patents. Zhang Zhao is currently an associate professor at the School of Computer Science and Technology of the Soochow University. He has authored and co-authored more than 60 technical papers.

The book focuses on the current research of the relation between protein phosphorylation and meat quality, reviews the influence mechanism of protein phosphorylation on meat quality, and summarizes the improvement of meat quality by regulating protein phosphorylation. It could help to clarify some dilemmas and encourage further research in this field, aiming for effective application of protein phosphorylation in meat quality in the near future. The book is written for researchers and graduate students in the field of meat science, food chemistry and molecular biology etc.

This Element provides a basic introduction to sentiment analysis, aimed at helping students and professionals in corpus linguistics to understand what sentiment analysis is, how it is conducted, and where it can be applied. It begins with a definition of sentiment analysis and a discussion of the domains where sentiment analysis is conducted and used the most. Then, it introduces two main methods that are commonly used in sentiment analysis known as supervised machine-learning and unsupervised learning (or lexicon-based) methods, followed by a step-by-step explanation of how to perform sentiment analysis with R. The Element then provides two detailed examples or cases of sentiment and emotion analysis, with one using an unsupervised method and the other using a supervised learning method.

This book constitutes the refereed post-conference proceedings of the 6th EAI International Conference on Green Energy and Networking, GreeNets 2019, held in Dalian, China, May 5, 2019. The 30 full papers were selected form 44 submissions and cover a wide spectrum of ideas to reduce the impact of the climate change, while maintaining social prosperity. In this context, growing global concern leads to the adoption of the new technological paradigms, especially for the operation of future smart cities.