Wei Wang

Effective Dynamics of Stochastic Partial Differential Equations focuses on stochastic partial differential equations with slow and fast time scales, or large and small spatial scales. The authors have developed basic techniques, such as averaging, slow manifolds, and homogenization, to extract effective dynamics from these stochastic partial differential equations. The authors’ experience both as researchers and teachers enable them to convert current research on extracting effective dynamics of stochastic partial differential equations into concise and comprehensive chapters. The book helps readers by providing an accessible introduction to probability tools in Hilbert space and basics of stochastic partial differential equations. Each chapter also includes exercises and problems to enhance comprehension.

Smart Hydrogel Functional Materials comprehensively and systematically describes our current understanding of smart or intelligent hydrogel functional materials with environmental stimuli-responsive functions. The contents range from hydrogels (including hydrogel-functionalized membranes) to microgels (including hydrogel-functionalized microcapsules) with various response properties, such as thermo-response, pH-response, pH-/thermo-dual-response, glucose-response, ethanol-response, ion-recognition, molecular-recognition, and so on. Most of the contents in this book represent the fresh achievements of the authors’ group on smart hydrogel functional materials. While all chapters can be read as stand-alone papers, together they clearly describe the design concepts, fabrication strategies and methods, microstructures and performances of smart hydrogel functional materials. Vivid schematics and illustrations throughout the book enhance the accessibility of the theory and technologies involved. This is an ideal reference book for a broad general readership including chemists, materials researchers, chemical engineers, pharmaceutical scientists and biomedical researchers, who are interested in designing and fabricating smart hydrogel functional materials for various application purposes.Dr. Liang-Yin Chu is a professor at the School of Chemical Engineering, Sichuan University, China. He is a Distinguished Young Scholar of the National Natural Science Foundation of China and a Distinguished Professor of the “Chang Jiang Scholars Program” of the Ministry of Education of China.

Switched delay systems appear in a wide field of applications including networked control systems, power systems, memristive systems. Though the large amount of ideas with respect to such systems have generated, until now, it still lacks a framework to focus on filter design and fault detection issues which are relevant to life safety and property loss. Beginning with the comprehensive coverage of the new developments in the analysis and control synthesis for switched delay systems, the monograph not only provides a systematic approach to designing the filter and detecting the fault of switched delay systems, but it also covers the model reduction issues. Specific topics covered include:(1) Arbitrary switching signal where delay-independent and delay-dependent conditions are presented by proposing a linearization technique. (2) Average dwell time where a weighted Lyapunov function is come up with dealing with filter design and fault detection issues beside taking model reduction problems.The monograph is intended for academic researchers and engineers in systems and control community who will discover of particular value in dealing with filter design and fault detection of switched system and time delay systems. In addition, it will be helpful and complementary reading for graduate students in such field.

Suitable for students with three or more years of modern Chinese language instruction, Anything Goes uses advanced materials to reinforce language skills and increase understanding of contemporary China in one semester. This fully revised edition provides learners with a deeper fluency in high-level Chinese vocabulary and grammar, and includes newspaper articles and critiques as well as other primary source documents, such as political speeches and legal documents. The textbook covers topics that are essential to understanding contemporary Chinese society, including changing attitudes toward women and marriage, the one-child policy, economic development, China's ethnic minorities, and debates surrounding Taiwan and Hong Kong. The lessons intentionally investigate thought-provoking and sometimes controversial issues in order to spark lively classroom discussions. This new edition incorporates suggestions and improvements from years of student and teacher feedback. With an improved, more user-friendly format, Anything Goes juxtaposes text and vocabulary on adjacent pages. Grammar explanations and exercises have also been thoroughly updated. * Advanced-level Chinese language textbook * Includes newspaper articles and primary source documents * Thought-provoking topics on contemporary Chinese society * Updated grammar explanations and exercises * New user-friendly format

In many applications, e.g., bioinformatics, web access traces, system u- lization logs, etc., the data is naturally in the form of sequences. It has been of great interests to analyze the sequential data to find their inherent char- teristics. The sequential pattern is one of the most widely studied models to capture such characteristics. Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces. In this book, we focus on sequential pattern mining. To meet different needs of various applications, several models of sequential patterns have been proposed. We do not only study the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. The objective of this book is to provide computer scientists and domain - perts such as life scientists with a set of tools in analyzing and understanding the nature of various sequences by : (1) identifying the specific model(s) of - quential patterns that are most suitable, and (2) providing an efficient algorithm for mining these patterns. Chapter 1 INTRODUCTION Data Mining is the process of extracting implicit knowledge and discovery of interesting characteristics and patterns that are not explicitly represented in the databases. The techniques can play an important role in understanding data and in capturing intrinsic relationships among data instances. Data mining has been an active research area in the past decade and has been proved to be very useful.

The advance in robotics has boosted the application of autonomous vehicles to perform tedious and risky tasks or to be cost-effective substitutes for their - man counterparts. Based on their working environment, a rough classi cation of the autonomous vehicles would include unmanned aerial vehicles (UAVs), - manned ground vehicles (UGVs), autonomous underwater vehicles (AUVs), and autonomous surface vehicles (ASVs). UAVs, UGVs, AUVs, and ASVs are called UVs (unmanned vehicles) nowadays. In recent decades, the development of - manned autonomous vehicles have been of great interest, and different kinds of autonomous vehicles have been studied and developed all over the world. In part- ular, UAVs have many applications in emergency situations; humans often cannot come close to a dangerous natural disaster such as an earthquake, a ood, an active volcano, or a nuclear disaster. Since the development of the rst UAVs, research efforts have been focused on military applications. Recently, however, demand has arisen for UAVs such as aero-robotsand ying robotsthat can be used in emergency situations and in industrial applications. Among the wide variety of UAVs that have been developed, small-scale HUAVs (helicopter-based UAVs) have the ability to take off and land vertically as well as the ability to cruise in ight, but their most importantcapability is hovering. Hoveringat a point enables us to make more eff- tive observations of a target. Furthermore, small-scale HUAVs offer the advantages of low cost and easy operation.

In many applications, e.g., bioinformatics, web access traces, system u- lization logs, etc., the data is naturally in the form of sequences. It has been of great interests to analyze the sequential data to find their inherent char- teristics. The sequential pattern is one of the most widely studied models to capture such characteristics. Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces. In this book, we focus on sequential pattern mining. To meet different needs of various applications, several models of sequential patterns have been proposed. We do not only study the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. The objective of this book is to provide computer scientists and domain - perts such as life scientists with a set of tools in analyzing and understanding the nature of various sequences by : (1) identifying the specific model(s) of - quential patterns that are most suitable, and (2) providing an efficient algorithm for mining these patterns. Chapter 1 INTRODUCTION Data Mining is the process of extracting implicit knowledge and discovery of interesting characteristics and patterns that are not explicitly represented in the databases. The techniques can play an important role in understanding data and in capturing intrinsic relationships among data instances. Data mining has been an active research area in the past decade and has been proved to be very useful.