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International Conference on Computing, Networking and Communications

作者： Yuke Li Miaowen Wen Xiang Cheng Liu-Qing Yang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Electronic and Information Engineering South China University of Technology School of Electronics Engineering and Computer Science Peking University

ISBN: (纸本)9781467385800

Recent years have witnessed the rapid development of intelligent transportation systems (ITS), which urgently call for highly reliable and effective communication technologies for vehicle-to-vehicle and vehicle-to-infrastructure (V2X) applications. Orthogonal frequency division multiplexing (OFDM) is widely believed to be the most promising candidate among these applications. However, the orthogonality of subcarriers in OFDM can be easily destroyed by the Doppler-induced inter-carrier interference (ICI), which is very common in V2X channels. In this paper, we propose a novel scheme which integrates the ICI self-cancellation technique into the index modulated (IM-) OFDM framework. Via careful designs, the proposed scheme can not only inherit the advantages of IM-OFDM but also suppress the ICI from active subcarriers. Simulations validate that in V2X channels, the proposed scheme significantly outperforms existing IM-OFDM and more importantly shows better performance than the conventional OFDM with ICI self-cancellation without sacrificing the spectral efficiency.

关键词： OFDM Vehicles Indexes Detectors Modulation Computational complexity Doppler shift

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Multi-player pursuit–evasion games with one superior evader

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Automatica 2016年 71卷 24-32页

作者： Jie Chen Wenzhong Zha Zhihong Peng Dongbing Gu School of Automation Beijing Institute of Technology Beijing 100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 China School of Computer Science and Electronic Engineering University of Essex Colchester CO4 3SQ UK

Inspired by the hunting and foraging behaviors of group predators, this paper addresses a class of multi-player pursuit–evasion games with one superior evader, who moves faster than the pursuers. We are concerned with the conditions under which the pursuers can capture the evader, involving the minimum number and initial spatial distribution required as well as the cooperative strategies of the pursuers. We present some necessary or sufficient conditions to regularize the encirclement formed by the pursuers to the evader. Then we provide a cooperative scheme for the pursuers to maintain and shrink the encirclement until the evader is captured. Finally, we give some examples to illustrate the theoretical results.

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Long short-term memory model for traffic congestion prediction with online open data

Long short-term memory model for traffic congestion predicti...

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International Conference on Intelligent Transportation

作者： Yuan-yuan Chen Yisheng Lv Zhenjiang Li Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao Shandong China

ISBN: (纸本)9781509018901

Traffic congestion in metropolitan areas has become more and more serious. Over the past decades, many academic and industrial efforts have been made to alleviate this problem, among which providing accurate, timely and predictive traffic conditions is a promising approach. Nowadays, online open data have rich traffic related information. Typical such resources include official websites of traffic management and operations, web-based map services (like Google map), weather forecasting websites, and local events (sport games, music concerts, etc.) websites. In this paper, online open data are discussed to provide traffic related information. Traffic conditions collected from web based map services are used to demonstrate the feasibility. The stacked long short-term memory model, a kind of deep architecture, is used to learn and predict the patterns of traffic conditions. Experimental results show that the proposed model for traffic condition prediction has superior performance over multilayer perceptron model, decision tree model and support vector machine model.

关键词： Logic gates Predictive models Computer architecture Google Data mining Microprocessors Social network services

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Extended State Observer Based control for Ground-Coupled Heat Pump System

Extended State Observer Based Control for Ground-Coupled Hea...

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第27届中国控制与决策会议

作者： Zhang Yu Wang Junxiao LI Shihua School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (纸本)9781479970186

This paper aims to investigate an extended state observer（ESO） based control approach for the ground-coupled heat pump system（GCHP）.As GCHP system has strong disturbances,a feasible approach of disturbance rejection should be proposed *** is employed to estimate the disturbance and compensate it to the controller to eliminate effects of the *** using ESO-based control and comparing with traditional control method,a better control performance is obtained through simulation verification.

关键词： GCHP ESO disturbance rejection simulation

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Plant growth architecture and production dynamics : A set of e-learning resources

Plant growth architecture and production dynamics : A set of...

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2016 IEEE International Conference on Functional-Structural Plant Growth Modeling, Simulation, Visualization and Applications, FSPMA 2016

作者： Jaeger, Marc De Reffye, Philippe Sabatier, Sylvie Caraglio, Yves Krit, Hatem Lafond, Marie-Helene Letort, Veronique Heuvelink, Ep Motisi, Matacha Zhang, BaoGui Kang, Mengzhen CIRAD AMAP Unit Montpellier34398 France University of Montpellier LIRMM ICAR Montpellier34095 France CentraleSupélec MAS Châtenay-Malabry92290 France WURL HPC Group Wageningen6700AA Netherlands CIRAD Pest and Disease Unit Montpellier34398 France Key Laboratory of Plant-Soil Interactions College of Resources and Environment China Agricultural University Beijing100193 China State Key Laboratory of Management and Control for Complex Systems LIAMA CASIA Beijing100190 China Qingdao Academy of Intelligent Sciences Qingdao266109 China

ISBN: (纸本)9781509016594

FSPM Plant and crop models are popular in the research community and there is increasing interest in their applications, from yield prediction to crop management optimization. A wide range of approaches and their software implementation can be found in the literature, with a large diversity in modelling scale (from plant organ to plot levels) and scope (structural, functional or both), as well as generic or specific aim. However, most of these approaches rely on similar key assumptions and methods related to different disciplines: Botany for plant structure, eco-physiology for production, statistics and dynamic system theory for parameter identification and estimation. Web disseminated plant and crop models learning supports are not numerous, often specific, and partial. We present here a set of e-learning resources, named 'Plant growth architecture and production dynamics' which describes the main notions from plant morphology and architecture, eco-physiology and applied mathematics necessary to the understanding of most plant and crop models, and their typology. In this paper, after an overview of existing learning resources on plant and crop modelling which, we believe, might be of interest for the whole research community, we present the proposed resource, which uses the GreenLab model as illustration, organized as follows: •Five standalone introductive disciplinary resources: Botanical notions, assumptions in eco-physiology, basis in data processing, introduction to models, introduction to GreenLab •An FSPM example in more details: GreenLab positioning, its basis, structure modelling, production modelling, and applications including model fitting and a study case •Tools: Inline (for structure analysis and statistics), online (access to fitters for instance) and access to download simulators and their documentation •Glossary, bibliography, web site collection, and a pedagogic kit for instructors Supported by the French Sustainable Development Virtual University

关键词： Glossaries

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Contributions of Social Manufacturing to Sustainable Apparel Industry

Contributions of Social Manufacturing to Sustainable Apparel...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Babak Mohajeri Timo Nyberg Jesse Karjalainen Mark Nelson Gang Xiong Aalto University Department of Industrial Engineering and Management Human Sciences and Technologies Advanced Research Institute (H-STAR)Stanford University The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Science

The global apparel and textile market has been changed considerably during the recent years. At the one hand, new trends and consumer preferences for different styles and fashion products emerge continuously, thus the apparel industry becomes more mass customized. On the other hand, attention to social and environmental sustainability has been dramatically increased in the entire industry. However, the current fast-changing fashion trends result to significant environmental and resource depletion problems in the textile lifecycle. As a result, the apparel industry should consider sustainable manufacturing strategies. The current options such as organic fibers and environmentally safe dyes seem promising. Nonetheless, there are significant challenges for apparel manufacturers and retailers to capitalize sustainability. To address these problems, in this paper, we develop a conceptual model of Social Manufacturing for the apparel industry. We study the current value chain of the apparel industry and identify its challenges from the sustainability's view. Then, we propose a new model to improve the sustainability throughout the value chain of the apparel industry

关键词： Social Manufacturing Apparel Industry Value chain sustainability

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Automatic Busbar Detection in Substation: Using Directional Gaussian Filter, Gradient Density, Hough Transform and Adaptive Dynamic K-means Clustering 34

Automatic Busbar Detection in Substation: Using Directional ...

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第三十四届中国控制会议

作者： CHEN Hongkai SUN Shiying WANG Tianzheng ZHAO Xiaoguang TAN Min The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences State Grid Shanxi Electric Power Research Institute

ISBN: (纸本)9781467374439

As the power system developing towards the extra-high-voltage(EHV), ultra-high-voltage(UHV), and large capacity direction in China, online monitoring becomes much more vital for power equipment to ensure the safe operation of power system. The computer vision-based Equipment Map State Detection technique can capture the abnormal status of power *** busbar, as a intermediate link at all levels of voltage distribution device, is vital in system safety and stability *** this paper, we propose an automatic busbar detection method in an image for substation using directional Gaussian lter to strengthen horizontal linear target in an image, gradient density to generate a busbar con dence map, Hough Transform to detect straight lines and adaptive dynamic K-means clustering to get closed lines for optimizing. Then, the busbar can be marked in image and it can be used for further checking whether there are foreign things hanging on the busbar. Experiments on some images taken in several substations demonstrate that our method is effective.

关键词： Busbar Detection,Directional Gaussian Filter,Gradient Density,Hough Transform,Adaptive Dynamic K-means Clustering

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Optimizing Market Segmentation Granularity in RTB Advertising: A Computational Experimental Study

Optimizing Market Segmentation Granularity in RTB Advertisin...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Rui Qin Yong Yuan Fei-Yue Wang Beijing Engineering Research Center of Intelligent Systems and Technology Beijing China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China

ISBN: (纸本)9781509039371

Real Time Bidding (RTB) is a novel business model of online computational advertising with the integration of Internet economy and big data analysis. It can help advertisers achieve the precision marketing through the market segmentation strategies of Demand Side Platforms (DSPs). Based on a mathematical programming approach, this paper studied DSPs' strategies for market segmentation, and established a selection model of the granularity for segmenting RTB advertising markets. We proposed to validate our model using the computational experiment approach, and the experimental results show that: 1) with the increasing refinement of the market segmentation granularity, the total revenue has a tendency of a rise first followed by a decline, 2) the optimal granularity of market segmentation will be significantly influenced by the number of advertisers on the DSP, but less influenced by the number of ad requests. Our findings show the crucial role of market segmentation on the RTB advertising effect, and indicate that the DSPs should adjust their market segmentation strategies according to their total number of advertisers. Our findings also highlight the importance of advertisers as well as the characteristics of the target audiences in DSPs' market segmentation decisions.

关键词： Digital signal processing Computational modeling Advertising Numerical models Big data complex systems Automation

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Exploring Optimal Frequency Caps in Real Time Bidding Advertising

Exploring Optimal Frequency Caps in Real Time Bidding Advert...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

ISBN: (纸本)9781509039371

Benefited from the high-speed development of Internet and the popularization of big data technology, Real Time Bidding (RTB) emerged and developed quickly, and has become one of the most important and popular model for online computational advertising. In the pay-per-impression based RTB advertising, frequency capping is undoubtedly one of the most crucial issues faced by advertisers and Demand Side Platforms (DSPs), since there are generally vast amount of ad requests in RTB markets, among which many may be triggered by the same target audience. As such, choosing the optimal frequency cap considering all the advertisers becomes a critical issue faced by DSPs. Considering that displaying one advertisement multiple number of times to the same user will diminish the advertising effect, we introduce the concept of discount factor and establish an optimization model of frequency capping to seek for the optimal frequency cap for each advertiser. We also design some experiments to validate our proposed model by utilizing the computational experiment approach, and the experimental results show that the optimal frequency cap can be influenced by the values of the discount factors, and higher value of the discount factor can deduce the advertising effect of larger frequency cap. Moreover, when the discount factors of the advertisers take different values, there also exists an optimal frequency cap, at which the advertisers can get the expected maximum revenue in the long run.

关键词： Advertising Digital signal processing Computational modeling Big data Time-frequency analysis Radio spectrum management Real-time systems

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AR and ESE Methods for Traffic Incident Analysis on Urban Arterials 15

AR and ESE Methods for Traffic Incident Analysis on Urban Ar...

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15th COTA International Conference of Transportation Professionals: Efficient, Safe, and Green Multimodal Transportation, CICTP 2015

作者： Yang, Zhen-Zhen Gao, Liang Gao, Zi-You Guo, Sheng-Min State Key Laboratory of Rail Traffic Control and Safety MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology Beijing Jiaotong University Beijing100044 China

ISBN: (数字)9780784479292

ISBN: (纸本)9780784479292

Analyzing traffic incidents is an important part of traffic incident management (TIM). In this paper, a traffic incident analysis method based on the accumulative ratio (AR) and extended spectral envelope (ESE) methods is presented. AR is used to analyze the spatial-Temporal evolution of a bottleneck caused by a traffic incident. The ESE method is used to detect key time points in the progression. An empirical study of a typical traffic incident on the 4th Ring Road East in Beijing was carried out and shows that the proposed methods can effectively trace the bottleneck and discover the key time points, which can provide a theoretical basis for traffic incident management. © ASCE.

关键词： Multimodal transportation

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