Yang Liu

Yang Liu East Meets West /ANGLAIS/ALLEMAND/CHINOIS

In this first in a new series for TASCHEN, leading graphic designer Yang Liu tackles one of the hottest, and one of the oldest, topics of all: he and she. Drawing on the experiences, challenges and many perspectives on men and women she has encountered in her own life, Yang Liu distils the vast, swirling question of gender to bold, binary pictograms.

Man Meets Woman

Jianquan Lu

Liangjie Sun

This book mainly focuses on the sampled-data control of logical networks. We believe that the methods (semi-tensor product of matrices), results (recent results on Boolean control networks under periodic sampled-data control, Boolean control networks under aperiodic sampled-data control, and logical control networks under event-triggered control) and topics (logical networks) in this book have become of particular interest to readers recently. Firstly, logical networks are of interest due to their rich range of applications in biology, game theory, coding, finite automata, graph theory, and other fields. Secondly, semi-tensor product of matrices offers a useful tool for formulating, analyzing and designing controllers for logical networks. Moreover, this book is the first to introduce sampled-data control into the study of logical control networks. All research results in this book are novel and worthy of further study. The book’s content is divided into three parts (Boolean control networks under periodic sampled-data control, Boolean control networks under aperiodic sampled-data control, and logical control networks under event-triggered control), which essentially progress from easier to more difficult. In addition, corresponding examples and diagrams are included in each section to facilitate understanding.

Sampled-data Control of Logical Networks

Maosong Sun

Zhiyuan Liu

Ting Liu

Xiaojie Wang

This book constitutes the proceedings of the 17th China National Conference on Computational Linguistics, CCL 2018, and the 6th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2018, held in Changsha, China, in October 2018. The 33 full papers presented in this volume were carefully reviewed and selected from 84 submissions. They are organized in topical sections named: Semantics; machine translation; knowledge graph and information extraction; linguistic resource annotation and evaluation; information retrieval and question answering; text classification and summarization; social computing and sentiment analysis; and NLP applications.

17th China National Conference, CCL 2018, and 6th International Symposium, NLP-NABD 2018, Changsha, China, October 19–21, 2018, Proceedings

Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data

Eben Goodale

Emilio Pagani-Núñez

Caroline Dingle

Craig Barnett

Junhua Hu

Yuanzhi Li

Yi Zou

Naicheng Wu

Impacts of Habitat Transformation on Species, Biodiversity and Ecosystems in Asia

Yu Zhou

Dewey H. Hodges

Lixi Huang

With rapid economic and industrial development in China, India and elsewhere, fluid-related structural vibration and noise problems are widely encountered in many fields, just as they are in the more developed parts of the world, causing increasingly grievous concerns. Turbulence clearly has a significant impact on many such problems. On the other hand, new opportunities are emerging with the advent of various new technologies, such as signal processing, flow visualization and diagnostics, new functional materials, sensors and actuators, etc. These have revitalized interdisciplinary research activities, and it is in this context that the 2nd symposium on fluid-structure-sound interactions and control (FSSIC) was organized. Held in Hong Kong (May 20-21, 2013) and Macau (May 22-23, 2013), the meeting brought together scientists and engineers working in all related branches from both East and West and provided them with a forum to exchange and share the latest progress, ideas and advances and to chart the frontiers of FSSIC. The Proceedings of the 2nd Symposium on Fluid-Structure-Sound Interactions and Control largely focuses on advances in the theory, experimental research and numerical simulations of turbulence in the contexts of flow-induced vibration, noise and their control. This includes several practical areas for interaction, such as the aerodynamics of road and space vehicles, marine and civil engineering, nuclear reactors and biomedical science etc. One of the particular features of these proceedings is that it integrates acoustics with the study of flow-induced vibration, which is not a common practice but is scientifically very helpful in understanding, simulating and controlling vibration. This offers a broader view of the discipline from which readers will benefit greatly. These proceedings are intended for academics, research scientists, design engineers and graduate students in engineering fluid dynamics, acoustics, fluid and aerodynamics, vibration, dynamical systems and control etc. Yu Zhou is a professor in Institute for Turbulence-Noise-Vibration Interaction and Control at Harbin Institute of Technology. Yang Liu is an associate professor at The Hong Kong Polytechnic University. Lixi Huang, associate professor, works at the University of Hong Kong. Professor Dewey H. Hodges works at the School of Aerospace Engineering, Georgia Institute of Technology.

Proceedings of the 2nd Symposium on Fluid-Structure-Sound Interactions and Control

Fluid-Structure-Sound Interactions and Control

Hui Hu

Linyue Gao

Wind Turbine Icing Physics and Anti-/De-Icing Technology gives a comprehensive update of research on the underlying physics pertinent to wind turbine icing and the development of various effective and robust anti-/de-icing technology for wind turbine icing mitigation. The book introduces the most recent research results derived from both laboratory studies and field experiments. Specifically, the research results based on field measurement campaigns to quantify the characteristics of the ice structures accreted over the blades surfaces of utility-scale wind turbines by using a Supervisory Control and Data Acquisition (SCADA) system and an Unmanned-Aerial-Vehicle (UAV) equipped with a high-resolution digital camera are also introduced. In addition, comprehensive lab experimental studies are explored, along with a suite of advanced flow diagnostic techniques, a detailed overview of the improvements, and the advantages and disadvantages of state-of-the-art ice mitigation strategies. This new addition to the Wind Energy Engineering series will be useful to all researchers and industry professionals who address icing issues through testing, research and industrial innovation. Covers detailed improvements and the advantages/disadvantages of state-of-the-art ice mitigation strategies Includes condition monitoring contents for lab-scale experiments and field tests Presents the potential of various bio-inspired icephobic coatings of wind turbine blades

Wind Turbine Icing Physics and Anti-/De-Icing Technology

Myint Swe Khine

This comprehensive book presents emerging research findings and promising reform practices in the field of teacher education, curriculum, assessment, teaching and learning approaches, pedagogical innovations, and professional development in educating the next generation of globally competent students. It reflects the current trends and highlights contemporary teacher education programs in twenty greater Asian countries and regions. It offers insight into improving teacher education in Singapore, Malaysia, Thailand, Philippines, Vietnam, Cambodia, Laos, Myanmar, Indonesia, Brunei, India, Pakistan, Bangladesh, Bhutan, China, Korea, Taiwan, Japan, Hong Kong, and Macau. The handbook contains chapters written by experienced international teacher educators who draw on their experience and expertise to perennial issues and formidable challenges in teacher preparation and meaningful school reforms. This volume is a valuable resource and essential companion for teacher educators, faculty members, staff developers, trainee teachers, undergraduate and postgraduate students, researchers, school leaders, policy-makers, and professional learning communities to refresh their knowledge and improve their understanding. This book is a must-read for anyone interested in evolving issues in teacher education.

Innovations and Practices in Asia

Handbook of Research on Teacher Education

Ben Hutchinson

Qiang Yang

Graham Cormode

David Evans

Han Yu

Ramesh Raskar

Mehryar Mohri

Zheng Xu

Rachel Cummings

Dawn Song

Mehdi Bennis

Peter Kairouz

H. Brendan McMahan

Brendan Avent

Aurélien Bellet

Arjun Nitin Bhagoji

Kallista Bonawit

Zachary Charles

Rafael G. L. D'Oliveira

Hubert Eichner

Salim El Rouayheb

Josh Gardner

Zachary Garrett

Adrià Gascón

Badih Ghazi

Phillip B. Gibbons

Marco Gruteser

Zaid Harchaoui

Chaoyang He

Lie He

Zhouyuan Huo

Justin Hsu

Martin Jaggi

Tara Javidi

Gauri Joshi

Mikhail Khodak

Jakub Konecný

Aleksandra Korolova

Farinaz Koushanfar

Sanmi Koyejo

Tancrède Lepoint

Prateek Mittal

Richard Nock

Ayfer Özgür

Rasmus Pagh

Daniel Ramage

Mariana Raykova

Weikang Song

Sebastian U. Stich

Ziteng Sun

Ananda Theertha Suresh

Florian Tramèr

Praneeth Vepakomma

Jianyu Wang

Li Xiong

Felix X. Yu

Sen Zhao

The term Federated Learning was coined as recently as 2016 to describe a machine learning setting where multiple entities collaborate in solving a machine learning problem, under the coordination of a central server or service provider. Each client's raw data is stored locally and not exchanged or transferred; instead, focused updates intended for immediate aggregation are used to achieve the learning objective.Since then, the topic has gathered much interest across many different disciplines and the realization that solving many of these interdisciplinary problems likely requires not just machine learning but techniques from distributed optimization, cryptography, security, differential privacy, fairness, compressed sensing, systems, information theory, statistics, and more.This monograph has contributions from leading experts across the disciplines, who describe the latest state-of-the art from their perspective. These contributions have been carefully curated into a comprehensive treatment that enables the reader to understand the work that has been done and get pointers to where effort is required to solve many of the problems before Federated Learning can become a reality in practical systems.Researchers working in the area of distributed systems will find this monograph an enlightening read that may inspire them to work on the many challenging issues that are outlined. This monograph will get the reader up to speed quickly and easily on what is likely to become an increasingly important topic: Federated Learning.

Advances and Open Problems in Federated Learning

Zidong Wang

Donghua Zhou

The objective of this book is to present the up-to-date research developments and novel methodologies on state estimation and fault diagnosis (FD) techniques for a class of complex systems subject to closed-loop control, nonlinearities, and stochastic phenomena. It covers state estimation design methodologies and FD unit design methodologies including framework of optimal filter and FD unit design, robust filter and FD unit design, stability, and performance analysis for the considered systems subject to various kinds of complex factors. Features: Reviews latest research results on the state estimation and fault diagnosis issues. Presents comprehensive framework constituted for systems under imperfect measurements. Includes quantitative performance analyses to solve problems in practical situations. Provides simulation examples extracted from practical engineering scenarios. Discusses proper and novel techniques such as the Carleman approximation and completing the square method is employed to solve the mathematical problems. This book aims at Graduate students, Professionals and Researchers in Control Science and Application, Stochastic Process, Fault Diagnosis, and Instrumentation and Measurement.

State Estimation and Fault Diagnosis under Imperfect Measurements

Min Zhang

This book constitutes the refereed proceedings of the 14th China National Conference on Computational Linguistics, CCL 2014, and of the Third International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2015, held in Guangzhou, China, in November 2015. The 34 papers presented were carefully reviewed and selected from 283 submissions. The papers are organized in topical sections on lexical semantics and ontologies; semantics; sentiment analysis, opinion mining and text classification; machine translation; multilinguality in NLP; machine learning methods for NLP; knowledge graph and information extraction; discourse, coreference and pragmatics; information retrieval and question answering; social computing; NLP applications.

14th China National Conference, CCL 2015 and Third International Symposium, NLP-NABD 2015, Guangzhou, China, November 13-14, 2015, Proceedings

Kurt Fritzsche

Lan Zhang

Rainer Leonhart

Validation of the Chinese Version of the PHQ-15 in a Tertiary Hospital

Omar Torres

Jun Wang

This book is a printed edition of the Special Issue "Remote Sensing of Atmospheric Pollution" that was published in Remote Sensing

Remote Sensing of Atmospheric Pollution

Hongfei Lin

Xuanjing Huang

This book constitutes the proceedings of the 15th China National Conference on Computational Linguistics, CCL 2016, and the 4th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2016, held in Yantai City, China, in October 2016. The 29 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 85 submissions. They were organized in topical sections named: semantics; machine translation; multilinguality in NLP; knowledge graph and information extraction; linguistic resource annotation and evaluation; information retrieval and question answering; text classification and summarization; social computing and sentiment analysis; and NLP applications.

15th China National Conference, CCL 2016, and 4th International Symposium, NLP-NABD 2016, Yantai, China, October 15-16, 2016, Proceedings

In this fourth installment of her best-selling pictogram series, award-winning graphic designer Yang Liu distills all the little joys and aches of childhood and parenting. Big meets Little takes on the daily happenings of family life through tongue-in-cheek irony and incisive observations, bringing fresh awareness to our different perspectives...

Yang Liu. Big Meets Little

Jun Sun

Grigoris Antoniou

Wei Hu

Jin Song Dong

Yuan-Fang Li

Zhe Wang

This book constitutes the thoroughly refereed proceedings of the 6th Joint International Semantic Technology Conference, JIST 2016, held in Singapore, Singapore, in November 2016. The main topics of JIST 2016 include among others ontology and reasoning; linked data; knowledge graph. The JIST 2016 conference consists of two keynotes, a main technical track, including (full and short papers) from the research and the in-use tracks, a Poster and Demo session, a workshop and two tutorials. The 16 full and 8 short papers presented were carefully reviewed and selected from 34 submissions. The papers cover the following topics: ontology and data management; linked data; information retrieval and knowledge discovery; RDF and query; knowledge graph; application of semantic technologies.

6th Joint International Conference, JIST 2016, Singapore, Singapore, November 2-4, 2016, Revised Selected Papers

Semantic Technology

Li Deng

In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.

Deep Learning in Natural Language Processing

Yang Liu

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