Yang examines the use of crowdsourcing for translation in the Chinese context, focusing on Yeeyan, which is the largest translation community in China.

Mapping Crowdsourcing Translation in China (Routledge Advances in Translation and Interpreting Studies)

Politics & Social Sciences

Yang, Jun

Sociology

Routledge

Disturbance Observer-Based Control: Methods and Applications

Due to its abilities to compensate disturbances and uncertainties, disturbance observer based control (DOBC) is regarded as one of the most promising approaches for disturbance-attenuation. One of the first books on DOBC, Disturbance Observer Based Control: Methods and Applications presents novel theory results as well as best practices for applications in motion and process control that have already benefited numerous organizations.Supplying authoritative guidance in the areas of disturbance estimation and compensation for practical engineering systems, the book includes coverage of theoretic methods and practical applications of disturbance estimation and compensation for control systems through a DOBC approach. It considers applications in flight control systems, motion control systems, and process control systems.  Supplies an authoritative overview of disturbance observer based control approaches Reports on recent developments in disturbance estimation techniques Considers matched and mismatched disturbance/uncertainty attenuation for DOBC Illustrates applications of the methods covered with detailed engineering case studies Filled with valuable insights gathered over decades of research by the authors, this book provides time- and stress-saving guidance for anyone interested in the theory and method research of DOBC. Using typical engineering examples, the text provides readers with an understanding of recent developments in DOBC as well as the tools required to make the most of this promising approach to disturbance-attenuation.

Computers & Technology

Li, Shihua

Chen, Wen-Hua

Chen, Xisong

Computer Science

CRC-Press

Data Management in Machine Learning Systems (Synthesis Lectures on Data Management)

Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications. ML systems provide means of specifying and executing these ML workloads in an efficient and scalable manner. Data management is at the heart of many ML systems due to data-driven application characteristics, data-centric workload characteristics, and system architectures inspired by classical data management techniques. In this book, we follow this data-centric view of ML systems and aim to provide a comprehensive overview of data management in ML systems for the end-to-end data science or ML lifecycle. We review multiple interconnected lines of work: (1) ML support in database (DB) systems, (2) DB-inspired ML systems, and (3) ML lifecycle systems. Covered topics include: in-database analytics via query generation and user-defined functions, factorized and statistical-relational learning; optimizing compilers for ML workloads; execution strategies and hardware accelerators; data access methods such as compression, partitioning and indexing; resource elasticity and cloud markets; as well as systems for data preparation for ML, model selection, model management, model debugging, and model serving. Given the rapidly evolving field, we strive for a balance between an up-to-date survey of ML systems, an overview of the underlying concepts and techniques, as well as pointers to open research questions. Hence, this book might serve as a starting point for both systems researchers and developers.

Kumar, Arun

Boehm, Matthias

Morgan & Claypool Publishers

Reference

Springer

Provides a systematic and coherent picture of the solution-based methods for the preparation of noble metal-based composite nanomaterials, their characterization, and potential applications in electrocatalysis Within the last decade, the development of wet-chemistry methods has led to the blossom of research in composite nanomaterials. However, the design and synthesis of composite nanomaterials with controlled properties remains a significant challenge. This book summarizes the solution-based methods for the preparation of noble metal-based composite nanomaterials. It examines their characterization, as well as their use in electrocatalysis. It also discusses the intrinsic relationship between the catalytic properties and the physical /chemical effects in the composite materials, and offers some perspectives for the future development of metal-based composite nanomaterials. In addition, the book not only provides a systematic and coherent picture of this field, but also inspires rethinking of the current processing technologies. Noble Metal-Based Nanocomposites: Preparation and Applications offers in-depth chapter coverage of ethanol-mediated phase transfer of metal ions and nanoparticles. It presents the full range of nanocomposites consisting of chalcogenide semiconductors and gold, silver sulfide, or other noble metals. It also examines core-shell structured cadmium selenide-platinum nanocomposites; Pt-containing Ag2S-noble metal nanocomposites for direct methanol fuel cells operated at high fuel concentrations; and nanocomposites consisting of metal oxides and noble metals. In addition, the book looks at scientific issues derived from noble metal-based nanocomposites. -Covers all of the preparations of noble metal-based nanocomposites and their numerous applications -Highlights some of the recent breakthroughs in the design, engineering, and applications of noble metal-based nanocomposites -Appeals to a wide range audience, especially researchers in the areas of catalysis, chemistry, chemical engineering, materials synthesis and characterization, and fuel cell Noble Metal-Based Nanocomposites: Preparation and Applications is an excellent book for inorganic chemists, materials scientists, catalytic chemists, chemical engineers, and those interested in the subject.

Noble Metal-Based Nanocomposites: Preparation and Applications

Science & Math

Chemistry

Vch Verlagsgesellschaft Mbh

This book reports on the latest findings in the study of Stochastic Neural Networks (SNN). The book collects the novel model of the disturbance driven by Levy process, the research method of M-matrix, and the adaptive control method of the SNN in the context of stability and synchronization control. The book will be of interest to university researchers, graduate students in control science and engineering and neural networks who wish to learn the core principles, methods, algorithms and applications of SNN.

Stability and Synchronization Control of Stochastic Neural Networks (Studies in Systems, Decision and Control, 35)

Zhou, Wuneng

Zhou, Liuwei

Tong, Dongbing

Die Realisierbarkeit Des Foderalismus in China (Nomos Universitatsschriften - Recht, 761) (English and German Edition)

Legal Theory & Systems

Nomos Verlagsgesellschaft Mbh & Co

Ministers of the Republic Files 1949-1966(Chinese Edition)

Xinjiang teenagers Press

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Books by Yang, Jun