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Dependable Software Engineering. Theories, Tools, and Applications: 4th International Symposium, Setta 2018, Beijing, China, September 4-6, 2018, Proceedings (Lecture Notes in Computer Science #10998)
by Xinyu Feng Markus Müller-Olm Zijiang YangThis book constitutes the proceedings of the Third International Symposium on Dependable Software Engineering: Theories, Tools, and Applications, SETTA 2018, held in Beijing, China, in September 2018. The 9 full papers presented together with 3 short papers were carefully reviewed and selected from 22 submissions. The purpose of SETTA is to provide an international forum for researchers and practitioners to share cutting-edge advancements and strengthen collaborations in the field of formal methods and its interoperability with software engineering for building reliable, safe, secure, and smart systems.
Actionable Science of Global Environment Change: From Big Data to Practical Research
by Ziheng SunThis volume teaches readers how to sort through the vast mountain of climate and environmental science data to extract actionable insights. With the advancements in sensing technology, we now observe petabytes of data related to climate and the environment. While the volume of data is impressive, collecting big data for the sake of data alone proves to be of limited utility. Instead, our quest is for actionable data that can drive tangible actions and meaningful impact.Yet, unearthing actionable insights from the accumulated big data and delivering them to global stakeholders remains a burgeoning field. Although traditional data mining struggles to keep pace with data accumulation, scientific evolution has spurred the emergence of new technologies like numeric modeling and machine learning. These cutting-edge tools are now tackling grand challenges in climate and the environment, from forecasting extreme climate events and enhancing environmental productivity to monitoring greenhouse gas emissions, fostering smart environmental solutions, and understanding aerosols. Additionally, they model environmental-human interactions, inform policy, and steer markets towards a healthier and more environment-friendly direction.While there's no universal solution to address all these formidable tasks, this book takes us on a guided journey through three sections, enriched with chapters from domain scientists. Part I defines actionable science and explores what truly renders data actionable. Part II showcases compelling case studies and practical use scenarios, illustrating these principles in action. Finally, Part III provides an insightful glimpse into the future of actionable science, focusing on the pressing climate and environmental issues we must confront.Embark on this illuminating voyage with us, where big data meets practical research, and discover how our collective efforts move us closer to a sustainable and thriving future. This book is an invitation to unlock the mysteries of our environment, transforming data into decisive action for generations to come.
Dynamic Management of Sustainable Development
by Irina Oleinikova Anna Mutule Yuri Merkuryev Zigurds KrishansDynamic management of systems development is a precondition for the realization of sustainable system development. This approach allows for the usage of systems theory methods that take into consideration the interaction of decisions made over time and space. A characteristic feature of this kind of method is that the process of sophisticated object development over time is examined for optimal decision selection. This requires the application of modelling methods that represent properties of the developing objects, high speed calculation methods for the estimation of technical and economic characteristics, as well as effective optimization methods. Dynamic Management of Sustainable Development presents a concise summary of the authors' research in the area of dynamic methods analysis of technical systems development. Along with systematic illustration of mathematical methods, considerable attention is drawn to practical realization and applications. Dynamic Management of Sustainable Development will be helpful for scientists involved in the mathematical modelling of large technical systems development and for engineers working in the area of large technical systems planning.
Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 17th European Conference, ECSQARU 2023, Arras, France, September 19–22, 2023, Proceedings (Lecture Notes in Computer Science #14294)
by Zied Bouraoui Srdjan VesicThis book constitutes the refereed proceedings of the 17th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2023, held in Arras, France, in September 2023. The 35 full papers presented in this volume were carefully reviewed and selected from 46 submissions. The papers are organized in topical sections about Complexity and Database Theory; Formal Concept Analysis: Theoretical Advances; Formal Concept Analysis: Applications; Modelling and Explanation; Semantic Web and Graphs; Posters.
Finite Frequency Analysis and Synthesis for Singularly Perturbed Systems
by Zidong Wang Chenxiao Cai Jing Xu Yun ZouThis book is a self-contained collection of recent research findings providing a comprehensive and systematic unified framework for both analysis and synthesis for singularly perturbed systems. It paves the way for the gap between frequency-domain-transfer-function-based results and time-domain-state-space-based results to be bridged. It is divided into three parts focusing on: fundamental background of singular perturbation; general singular perturbation methodologies and time-scale techniques and the theoretical foundation of finite-frequency control; the analysis and synthesis of singularly perturbed systems; and real-world engineering applications implementing the results developed in systems like wind turbines and autonomous-aerial-vehicle hovering. It also presents solutions to analysis and design problems in terms of linear matrix inequalities. Lastly, it provides valuable reference material for researchers who wish to explore the design of controllers for such systems.
Microarray Image Analysis: An Algorithmic Approach (Chapman & Hall/CRC Computer Science & Data Analysis)
by Karl Fraser Zidong Wang Xiaohui LiuTo harness the high-throughput potential of DNA microarray technology, it is crucial that the analysis stages of the process are decoupled from the requirements of operator assistance. Microarray Image Analysis: An Algorithmic Approach presents an automatic system for microarray image processing to make this decoupling a reality. The proposed syste
Nonlinear Control and Filtering for Stochastic Networked Systems
by Zidong Wang Lifeng Ma Yuming BoIn this book, control and filtering problems for several classes of stochastic networked systems are discussed. In each chapter, the stability, robustness, reliability, consensus performance, and/or disturbance attenuation levels are investigated within a unified theoretical framework. The aim is to derive the sufficient conditions such that the resulting systems achieve the prescribed design requirements despite all the network-induced phenomena. Further, novel notions such as randomly occurring sensor failures and consensus in probability are discussed. Finally, the theories/techniques developed are applied to emerging research areas. Key Features Unifies existing and emerging concepts concerning stochastic control/filtering and distributed control/filtering with an emphasis on a variety of network-induced complexities Includes concepts like randomly occurring sensor failures and consensus in probability (with respect to time-varying stochastic multi-agent systems) Exploits the recursive linear matrix inequality approach, completing the square method, Hamilton-Jacobi inequality approach, and parameter-dependent matrix inequality approach to handle the emerging mathematical/computational challenges Captures recent advances of theories, techniques, and applications of stochastic control as well as filtering from an engineering-oriented perspective Gives simulation examples in each chapter to reflect the engineering practice
Nonlinear Stochastic Control and Filtering with Engineering-oriented Complexities (Engineering Systems and Sustainability #2)
by Zidong Wang Guoliang Wei Wei QianNonlinear Stochastic Control and Filtering with Engineering-oriented Complexities presents a series of control and filtering approaches for stochastic systems with traditional and emerging engineering-oriented complexities. The book begins with an overview of the relevant background, motivation, and research problems, and then: Discusses the robust stability and stabilization problems for a class of stochastic time-delay interval systems with nonlinear disturbances Investigates the robust stabilization and H∞ control problems for a class of stochastic time-delay uncertain systems with Markovian switching and nonlinear disturbances Explores the H∞ state estimator and H∞ output feedback controller design issues for stochastic time-delay systems with nonlinear disturbances, sensor nonlinearities, and Markovian jumping parameters Analyzes the H∞ performance for a general class of nonlinear stochastic systems with time delays, where the addressed systems are described by general stochastic functional differential equations Studies the filtering problem for a class of discrete-time stochastic nonlinear time-delay systems with missing measurement and stochastic disturbances Uses gain-scheduling techniques to tackle the probability-dependent control and filtering problems for time-varying nonlinear systems with incomplete information Evaluates the filtering problem for a class of discrete-time stochastic nonlinear networked control systems with multiple random communication delays and random packet losses Examines the filtering problem for a class of nonlinear genetic regulatory networks with state-dependent stochastic disturbances and state delays Considers the H∞ state estimation problem for a class of discrete-time complex networks with probabilistic missing measurements and randomly occurring coupling delays Addresses the H∞ synchronization control problem for a class of dynamical networks with randomly varying nonlinearities Nonlinear Stochastic Control and Filtering with Engineering-oriented Complexities describes novel methodologies that can be applied extensively in lab simulations, field experiments, and real-world engineering practices. Thus, this text provides a valuable reference for researchers and professionals in the signal processing and control engineering communities.
Nonlinear Stochastic Systems with Incomplete Information
by Huisheng Shu Zidong Wang Bo ShenNonlinear Stochastic Processes addresses the frequently-encountered problem of incomplete information. The causes of this problem considered here include: missing measurements; sensor delays and saturation; quantization effects; and signal sampling. Divided into three parts, the text begins with a focus on H filtering and control problems associated with general classes of nonlinear stochastic discrete-time systems. Filtering problems are considered in the second part, and in the third the theory and techniques previously developed are applied to the solution of issues arising in complex networks with the design of sampled-data-based controllers and filters. Among its highlights, the text provides: * a unified framework for filtering and control problems in complex communication networks with limited bandwidth; * new concepts such as random sensor and signal saturations for more realistic modeling; and * demonstration of the use of techniques such as the Hamilton-Jacobi-Isaacs, difference linear matrix, and parameter-dependent matrix inequalities and sums of squares to handle the computational challenges inherent in these systems. The collection of recent research results presented in Nonlinear Stochastic Processes will be of interest to academic researchers in control and signal processing. Graduate students working with communication networks with lossy information and control of stochastic systems will also benefit from reading the book.
Nonlinear Stochastic Systems with Network-Induced Phenomena
by Zidong Wang Huijun Gao Jun HuThis monograph introduces methods for handling filtering and control problems in nonlinear stochastic systems arising from network-induced phenomena consequent on limited communication capacity. Such phenomena include communication delay, packet dropout, signal quantization or saturation, randomly occurring nonlinearities and randomly occurring uncertainties. The text is self-contained, beginning with an introduction to nonlinear stochastic systems, network-induced phenomena and filtering and control, moving through a collection of the latest research results which focuses on the three aspects of: · the state-of-the-art of nonlinear filtering and control; · recent advances in recursive filtering and sliding mode control; and · their potential for application in networked control systems, and concluding with some ideas for future research work. New concepts such as the randomly occurring uncertainty and the probability-constrained performance index are proposed to make the network models as realistic as possible. The power of combinations of such recent tools as the completing-the-square and sums-of-squares techniques, HamiltonJacobiIsaacs matrix inequalities, difference linear matrix inequalities and parameter-dependent matrix inequalities is exploited in treating the mathematical and computational challenges arising from nonlinearity and stochasticity. Nonlinear Stochastic Systems with Network-Induced Phenomena establishes a unified framework of control and filtering which will be of value to academic researchers in bringing structure to problems associated with an important class of networked system and offering new means of solving them. The significance of the new concepts, models and methods presented for practical control engineering and signal processing will also make it a valuable reference for engineers dealing with nonlinear control and filtering problems.
Performance Analysis and Synthesis for Discrete-Time Stochastic Systems with Network-Enhanced Complexities
by Zidong Wang Derui Ding Guoliang WeiThe book addresses the system performance with a focus on the network-enhanced complexities and developing the engineering-oriented design framework of controllers and filters with potential applications in system sciences, control engineering and signal processing areas. Therefore, it provides a unified treatment on the analysis and synthesis for discrete-time stochastic systems with guarantee of certain performances against network-enhanced complexities with applications in sensor networks and mobile robotics. Such a result will be of great importance in the development of novel control and filtering theories including industrial impact. <P><P>Key Features <li>Provides original methodologies and emerging concepts to deal with latest issues in the control and filtering with an emphasis on a variety of network-enhanced complexities <li>Gives results of stochastic control and filtering distributed control and filtering, and security control of complex networked systems <li>Captures the essence of performance analysis and synthesis for stochastic control and filtering <li>Concepts and performance indexes proposed reflect the requirements of engineering practice <li>Methodologies developed in this book include backward recursive Riccati difference equation approach and the discrete-time version of input-to-state stability in probability
Variance-Constrained Filtering for Stochastic Complex Systems: Theories and Algorithms (Intelligent Control and Learning Systems #18)
by Zidong Wang Jun Hu Chaoqing JiaThis book is concerned with the variance-constrained optimized filtering problems and their potential applications for nonlinear time-varying dynamical systems. The distinguished features of this book are highlighted as follows. (1) A unified framework is provided for handling the variance-constrained filtering problems of nonlinear time-varying dynamical systems with incomplete information. (2) The application potentials of variance-constrained optimized filtering in networked time-varying dynamical systems are outlined. It contains some new concepts, new models and new methodologies with practical significance in control engineering and signal processing. It is a collection of several research results and thereby serves as a useful reference for upper undergraduate, postgraduate and engineers who are interested in studying (i) the variance-constrained filtering, (ii) recent advances affected by incomplete information and (iii) potential applications in practical engineering systems.
Variance-Constrained Multi-Objective Stochastic Control and Filtering
by Zidong Wang Lifeng Ma Yuming BoUnifies existing and emerging concepts concerning multi-objective control and stochastic control with engineering-oriented phenomena Establishes a unified theoretical framework for control and filtering problems for a class of discrete-time nonlinear stochastic systems with consideration to performance Includes case studies of several nonlinear stochastic systems Investigates the phenomena of incomplete information, including missing/degraded measurements, actuator failures and sensor saturations Considers both time-invariant systems and time-varying systems Exploits newly developed techniques to handle the emerging mathematical and computational challenges
Blockchain Transaction Data Analytics: Complex Network Approaches (Big Data Management)
by Zibin Zheng Dan Lin Jiajing WuBlockchain, a decentralized ledger technology based on cryptographic algorithms, ensures the creation of immutable and tamper-proof ledgers in decentralized systems. The transparent nature of blockchain allows public access to transaction records, providing unprecedented opportunities for blockchain data analytics and mining. The primary value of blockchain transaction data analytics lies in two aspects: 1) by delving into the details of blockchain transaction data, we can extensively explore various types of user behavior patterns and the evolutionary process of blockchain transaction networks; and 2) analyzing blockchain transaction data aids in identifying illicit activities, offering effective regulatory solutions for the establishment of a healthier blockchain ecosystem. This book focuses on data analytics based on network-based approaches, providing a comprehensive analysis of blockchain data analytics problems, key technologies, and future directions. Different from most existing book, this book takes a unique approach to blockchain data analysis research, focusing on data analytics based on network-based approaches. Leveraging network analysis methods, the book concentrates on three main aspects of blockchain transaction data analytics and mining: (1) transaction network modelling and pattern mining, including macro and micro-level account attributes, money laundering network patterns, and network evolution patterns; (2) account business classification, such as account label prediction based on graph neural networks; and (3) anomaly behavior identification, covering phishing detection, risk scoring, and transaction tracking. Designed as a valuable resource for students, researchers, engineers, and policymakers in various fields related to blockchain data analytics, this book holds significant importance for understanding blockchain transaction behavior and addressing the detection of illicit activities in the blockchain space.
Advanced Finite Element Simulation with MSC Marc: Application of User Subroutines
by Andreas Öchsner Zia JavanbakhtThis book offers an in-depth insight into the general-purpose finite element program MSC Marc, which is distributed by MSC Software Corporation. It is a specialized program for nonlinear problems (implicit solver) which is common in academia and industry. The primary goal of this book is to provide a comprehensive introduction to a special feature of this software: the user can write user-subroutines in the programming language Fortran, which is the language of all classical finite element packages. This subroutine feature allows the user to replace certain modules of the core code and to implement new features such as constitutive laws or new elements. Thus, the functionality of commercial codes ('black box') can easily be extended by linking user written code to the main core of the program. This feature allows to take advantage of a commercial software package with the flexibility of a 'semi-open' code.
Power System Dynamic Modelling and Analysis in Evolving Networks (CIGRE Green Books)
by Babak Badrzadeh Zia EminThis Green Book is an essential resource for power system engineers seeking comprehensive information on contemporary power system dynamic modelling and analysis. With today's rapid adoption of inverter-based resources and the resulting changes in power system dynamics, this book compares conventional power systems with evolving power systems characterized by high shares of grid-connected and distributed inverter-based resources. It covers dynamic phenomena, analysis methods, simulation tools and enablers required for secure and reliable system planning and operation. Starting with an overview of power system studies and associated analysis tools, the book provides modelling requirements for various power system components, including existing and emerging technologies. It includes practical examples from real-world power systems worldwide that act as step-by-step study guides for practising engineers and provides knowledge to apply in their day-to-day tasks. Additionally, the book emphasizes the importance of power system model acceptance testing and validation, providing practical examples of various testing methods. Written with practising power system engineers in mind, this book minimizes the use of advanced mathematics. However, relevant sources for those interested in learning more about mathematical concepts are provided. Overall, this book is an invaluable resource for power system engineers navigating contemporary power systems. Readers who would like to comment on any of the published books or identify errors to the editorial team please contact: cigregreenbooks@springer.com.
Statistical Capacity Building
by Thomas K. Morrison Zia Abbasi Noel Atcherley Jaroslav Ku Era Graham L. SlackIMF technical assistance provided by the Statistics Department -- toward assisting IMF member countries in developing the ability to provide reliable and comparable economic and financial data on a timely basis to policymakers and markets -- has increased more than fourfold over the past decade. This assistance has proven critical in countries' building their statistical capacity so as to come into line with international data standards in an increasingly globalized and electronically interconnected world. Statistical Capacity Building: Case Studies and Lessons Learned presents four case studies drawn from experience in three countries in transition to the market, two of which were also in postconflict situations, in the 1990s and early 2000s: Cambodia, Bosnia and Herzegovina, and Ukraine. Issues of setting, institutional and statistical arrangements, strategies, and implementation are examined, and lessons drawn.
Applying the Rasch Model: Fundamental Measurement in the Human Sciences
by Trevor Bond Zi Yan Moritz HeeneRecognised as the most influential publication in the field, ARM facilitates deep understanding of the Rasch model and its practical applications. The authors review the crucial properties of the model and demonstrate its use with examples across the human sciences. Readers will be able to understand and critically evaluate Rasch measurement research, perform their own Rasch analyses and interpret their results. The glossary and illustrations support that understanding, and the accessible approach means that it is ideal for readers without a mathematical background. Highlights of the new edition include: More learning tools to strengthen readers’ understanding including chapter introductions, boldfaced key terms, chapter summaries, activities and suggested readings. Greater emphasis on the use of R packages; readers can download the R code from the Routledge website. Explores the distinction between numerical values, quantity and units, to understand the measurement and the role of the Rasch logit scale (Chapter 4). A new four-option data set from the IASQ (Instrumental Attitude towards Self-assessment Questionnaire) for the Rating Scale Model (RSM) analysis exemplar (Chapter 6). Clarifies the relationship between Rasch measurement, path analysis and SEM, with a host of new examples of Rasch measurement applied across health sciences, education and psychology (Chapter 10). Intended as a text for graduate courses in measurement, item response theory, (advanced) research methods or quantitative analysis taught in psychology, education, human development, business, and other social and health sciences. Professionals in these areas will also appreciate the book’s accessible introduction.
Recent Advances in Radial Basis Function Collocation Methods
by Wen Chen Zhuo-Jia Fu C. S. ChenThis book surveys the latest advances in radial basis function (RBF) meshless collocation methods which emphasis on recent novel kernel RBFs and new numerical schemes for solving partial differential equations. The RBF collocation methods are inherently free of integration and mesh, and avoid tedious mesh generation involved in standard finite element and boundary element methods. This book focuses primarily on the numerical algorithms, engineering applications, and highlights a large class of novel boundary-type RBF meshless collocation methods. These methods have shown a clear edge over the traditional numerical techniques especially for problems involving infinite domain, moving boundary, thin-walled structures, and inverse problems. Due to the rapid development in RBF meshless collocation methods, there is a need to summarize all these new materials so that they are available to scientists, engineers, and graduate students who are interest to apply these newly developed methods for solving real world's problems. This book is intended to meet this need. Prof. Wen Chen and Dr. Zhuo-Jia Fu work at Hohai University. Prof. C. S. Chen works at the University of Southern Mississippi.
Belief Functions: 6th International Conference, BELIEF 2021, Shanghai, China, October 15–19, 2021, Proceedings (Lecture Notes in Computer Science #12915)
by Frédéric Pichon Thierry Denœux Eric Lefèvre Zhunga LiuThis book constitutes the refereed proceedings of the 6th International Conference on Belief Functions, BELIEF 2021, held in Shanghai, China, in October 2021. The 30 full papers presented in this book were carefully selected and reviewed from 37 submissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more.
Analysis of Industrial Clusters in China
by Zhu YingmingTaking a close look at the national economic system of China, this book defines industrial clusters, then summarizes their measurement indices and identifies their methods. The author identifies 11 industrial clusters and analyses their structural relationships. He studies the relationships between structures and characters of industrial clusters u
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics 2021 (Conference Proceedings of the Society for Experimental Mechanics Series)
by Zhu MaoModel Validation and Uncertainty Quantification, Volume 3: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics, 2021, the third volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on:Inverse Problems and Uncertainty QuantificationControlling UncertaintyValidation of Models for Operating EnvironmentsModel Validation & Uncertainty Quantification: Decision MakingUncertainty Quantification in Structural DynamicsUncertainty in Early Stage DesignComputational and Uncertainty Quantification Tools
Compressive Sensing for Wireless Networks
by Wotao Yin Zhu Han Husheng LiCompressive sensing is a new signal processing paradigm that aims to encode sparse signals by using far lower sampling rates than those in the traditional Nyquist approach. It helps acquire, store, fuse and process large data sets efficiently and accurately. This method, which links data acquisition, compression, dimensionality reduction and optimization, has attracted significant attention from researchers and engineers in various areas. This comprehensive reference develops a unified view on how to incorporate efficiently the idea of compressive sensing over assorted wireless network scenarios, interweaving concepts from signal processing, optimization, information theory, communications and networking to address the issues in question from an engineering perspective. It enables students, researchers and communications engineers to develop a working knowledge of compressive sensing, including background on the basics of compressive sensing theory, an understanding of its benefits and limitations, and the skills needed to take advantage of compressive sensing in wireless networks.
Game Theory in Wireless and Communication Networks
by Tamer Başar Zhu Han Dusit Niyato Walid Saad Are HjørungnesThis unified treatment of game theory focuses on finding state-of-the-art solutions to issues surrounding the next generation of wireless and communications networks. Future networks will rely on autonomous and distributed architectures to improve the efficiency and flexibility of mobile applications, and game theory provides the ideal framework for designing efficient and robust distributed algorithms. This book enables readers to develop a solid understanding of game theory, its applications and its use as an effective tool for addressing wireless communication and networking problems. The key results and tools of game theory are covered, as are various real-world technologies including 3G networks, wireless LANs, sensor networks, dynamic spectrum access and cognitive networks. The book also covers a wide range of techniques for modeling, designing and analysing communication networks using game theory, as well as state-of-the-art distributed design techniques. This is an ideal resource for communications engineers, researchers, and graduate and undergraduate students.
Overlapping Coalition Formation Games in Wireless Communication Networks
by Zhu Han Walid Saad Tianyu Wang Lingyang SongThis brief introduces overlapping coalition formation games (OCF games), a novel mathematical framework from cooperative game theory that can be used to model, design and analyze cooperative scenarios in future wireless communication networks. The concepts of OCF games are explained, and several algorithmic aspects are studied. In addition, several major application scenarios are discussed. These applications are drawn from a variety of fields that include radio resource allocation in dense wireless networks, cooperative spectrum sensing for cognitive radio networks, and resource management for crowd sourcing. For each application, the use of OCF games is discussed in detail in order to show how this framework can be used to solve relevant wireless networking problems. Overlapping Coalition Formation Games in Wireless Communication Networks provides researchers, students and practitioners with a concise overview of existing works in this emerging area, exploring the relevant fundamental theories, key techniques, and significant applications.