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8th Pacific-Rim Symposium on Image and Video Technology (PSIVT)

作者： Liu, Jian Shang, Xiuqin Yang, Shuzhan Shen, Zhen Liu, Xiwei Xiong, Gang Nyberg, Timo R. Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Chinese Acad Sci Cloud Comp Ctr Dongguan 523808 Peoples R China Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China Peking Univ Coll Engn Dept Mech & Engn Sci MES Beijing 100871 Peoples R China Qingdao Acad Intelligent Ind Inst Smart Educ Syst Qingdao 266109 Peoples R China Chinese Acad Sci Beijing Engn Res Ctr Intelligent Syst & Technol Inst Automat Beijing 100190 Peoples R China Aalto Univ Sch Sci Dept Ind Engn & Management POB 11000 Aalto 00076 Finland

ISBN: (纸本)9783319927534;9783319927527

Point cloud data, as a basis for the three-dimensional data types has attracted more and more attention these years. compared with other types of three-dimensional data, point cloud data can be collected by simple ways, and it contains surface texture, surface color, and other types of features on the surface of the target object. Recently, in the field of cloud data processing, many new point cloud processing methods have been proposed on the basis of existed theory, among which, the most notable one is the newly proposed algorithm in the field of point cloud registration. In this paper, an improved point cloud registration algorithm based on classical ICP algorithm is proposed. In the classical ICP algorithm, the main part which limit the efficiency of the algorithm is the iterative search process of the corresponding point, the new algorithm proposed in this paper uses the 4-point coincidence algorithm to accelerate the corresponding point search process as an improvement to the classical ICP algorithm, and to verify its improvement by experiment.

关键词： Point cloud data Point cloud registration ICP algorithm 4-point consistent algorithm

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General formation control for multi-agent systems with double-integrator dynamics

arXiv

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arXiv 2018年

作者： Wang, Chen Xia, Weiguo Sun, Jinan Fan, Ruifeng Xie, Guangming State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing100871 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China National Engineering Research Center for Software Engineering Peking University Beijing100871 China

We study the general formation problem for a group of mobile agents in a plane, in which the agents are required to maintain a distribution pattern, as well as to rotate around or remain static relative to a static/moving target. The prescribed distribution pattern is a class of general formations that the distances between neighboring agents or the distances from each agent to the target do not need to be equal. Each agent is modeled as a double integrator and can merely perceive the relative information of the target and its neighbors. A distributed control law is designed using the limit-cycle based idea to solve the problem. One merit of the controller is that it can be implemented by each agent in its Frenet-Serret frame so that only local information is utilized without knowing global information. Theoretical analysis is provided of the equilibrium of the N-agent system and of the convergence of its converging part. Numerical simulations are given to show the effectiveness and performance of the proposed controller. Copyright © 2018, The Authors. All rights reserved.

关键词： Mobile agents

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A Parallel Transportation management and control System for Bus Rapid Transit Using the ACP Approach

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IEEE TRANSACTIONS ON intelligent TRANSPORTATION systems 2017年第9期18卷 2569-2574页

作者： Dong, Xisong Lin, Yuetong Shen, Dayong Li, Zhengxi Zhu, Fenghua Hu, Bin Fan, Dong Xiong, Gang Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Indiana State Univ Elect & Comp Engn Technol Dept Terre Haute IN 47809 USA Natl Univ Def Technol Coll Informat Syst & Management Changsha 410073 Hunan Peoples R China North China Univ Technol Beijing Key Lab Urban Intelligent Traff Control T Beijing 100144 Peoples R China Chinese Acad Sci Cloud Comp Ctr Dongguan 523808 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China Chinese Acad Sci Inst Automat Beijing Engn Res Ctr Intelligent Syst & Technol Beijing 100190 Peoples R China

Bus rapid transit (BRT) has been proved to be an effective tool to improve mass transit services. However, BRT's adaptive operations like management and scheduling under different scenarios are too complicated to implement using traditional methods. The ACP approach, which is based on holism and complex system theory and consists of artificial systems (A), computational experiments (C) and parallel execution (P), offers an efficient new method to cope with these complex systems, including BRT. In this paper, the parallel transportation management and control system for BRT (PTMS-BRT) is presented, which is designed and implemented using the ACP approach. PTMS-BRT integrates such functions as BRT's monitoring, warning, forecasting, incident management, and real-time scheduling, to provide its operations smoother, safer, more efficient, and reliable. It has been piloted successfully in Guangzhou BRT to demonstrate it as another successful example of parallel transportation systems.

关键词： Bus rapid transit (BRT) ACP approach parallel transportation system dynamic perception artificial transportation system

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Hierarchical and Networked Vehicle Surveillance in ITS: A Survey

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IEEE TRANSACTIONS ON intelligent TRANSPORTATION systems 2017年第1期18卷 25-48页

作者： Tian, Bin Morris, Brendan Tran Tang, Ming Liu, Yuqiang Yao, Yanjie Gou, Chao Shen, Dayong Tang, Shaohu Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Nevada Dept Elect & Comp Engn Las Vegas NV 89154 USA Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100190 Peoples R China Natl Univ Def Technol Coll Informat Syst & Management Changsha 410073 Hunan Peoples R China North China Univ Technol Beijing Key Lab Urban Intelligent Traff Control T Sch Mech & Elect Engn Beijing 100041 Peoples R China

Traffic surveillance has become an important topic in intelligent transportation systems (ITSs), which is aimed at monitoring and managing traffic flow. With the progress in computer vision, video-based surveillance systems have made great advances on traffic surveillance in ITSs. However, the performance of most existing surveillance systems is susceptible to challenging complex traffic scenes (e.g., object occlusion, pose variation, and cluttered background). Moreover, existing related research is mainly on a single video sensor node, which is incapable of addressing the surveillance of traffic road networks. Accordingly, we present a review of the literature on the video-based vehicle surveillance systems in ITSs. We analyze the existing challenges in video-based surveillance systems for the vehicle and present a general architecture for video surveillance systems, i.e., the hierarchical and networked vehicle surveillance, to survey the different existing and potential techniques. Then, different methods are reviewed and discussed with respect to each module. Applications and future developments are discussed to provide future needs of ITS services.

关键词： Behavior understanding computer vision networked surveillance system traffic surveillance vehicle detection vehicle tracking

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A Novel Approach for Traffic Signal control: A Recommendation Perspective

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IEEE intelligent TRANSPORTATION systems MAGAZINE 2017年第3期9卷 127-135页

作者： Zhao, Yifei Gao, Hang Wang, Shuai Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Inst Smart Educ Syst Qingdao 266109 Peoples R China Qingdao Acad Intelligent Ind Qingdao Peoples R China Xi An Jiao Tong Univ Xian Shaanxi Peoples R China Natl Univ Def Technol Changsha Hunan Peoples R China

Traffic Signal control is an effective mean of solving urban traffic problems by providing appropriate signal timings for road intersections. In this paper, we propose a novel approach originated from methods and applications of recommendation systems to select the most suitable signal timings for various traffic demands. Specifically, we use the idea of computational experiments and the well-known recommendation technology called Collab.rative Filtering to find the best signal timings from a database filled with large amounts of traffic data. When the database is not large enough for some special traffic situations, traditional approaches are adopted. Corresponding data with good performance will be recorded.

关键词： Databases Delays Classification algorithms Roads complex systems

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Exploring the optimal granularity for market segmentation in RTB advertising via computational experiment approach

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ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS 2017年 24卷 68-83页

作者： Qin, Rui Yuan, Yong Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Qingdao Acad Intelligent Ind Inst Parallel Econ Qingdao Peoples R China Natl Univ Def Technol Res Ctr Mil Computat Expt & Parallel Syst Changsha Hunan Peoples R China Chinese Acad Sci Beijing Engn Res Ctr Intelligent Syst & Technol Inst Automat Beijing Peoples R China

Real Time Bidding (RTB) is a novel business model of online computational advertising, developing rapidly with the integration of Internet economy and big data analysis. It evolves the business logic of online ad-delivery from buying "ad-impressions" in websites or ad slots to directly buying the best-matched "target audiences", and thus can help advertisers achieve the precision marketing. As a critical part of RTB advertising markets, Demand Side Platforms (DSPs) play a central role in matching advertisers with their target audiences via cookie-based data analysis and market segmentation, and their segmentation strategies (especially the choice of granularity) have key influences in improving the effectiveness and efficiency of RTB advertising markets. 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. With the computational experiment approach, we designed three experimental scenarios to validate our proposed model, and the experimental results show that: 1) market segmentation has the potential of improving the total revenue of all the advertisers;2) with the increasing refinement of the market segmentation granularity, the total revenue has a tendency of a rise first and followed by a decline;3) 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 to DSPs' market segmentation decisions. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Real Time Bidding Demand Side Platforms Market segmentation Computational experiment

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Analysis of Cyber Interactive Behaviors Using Artificial Community and Computational Experiments

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2017年第6期47卷 995-1006页

作者： Wang, Xiao Zheng, Xinhu Zhang, Xinzhan Zeng, Ke Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Shandong Peoples R China Univ Minnesota Dept Comp Sci & Engn Minneapolis MN 55455 USA Xi An Jiao Tong Univ Sch Software Engn Xian Peoples R China

An artificial community is constructed for studying cyber interactive behavior of message publishing by considering impacts from individual's psychological state and social environment. The bottom-up multiagent approach is applied to model the interactions between individuals, and the evolution and organization of collective cyber behaviors. The cyber message publishing behaviors in response to online topics is demonstrated in the artificial community, where each agent perceives the state of the topics and make decisions to operate on specific themes with particular message publishing mechanisms. The mechanisms are designed in line with the analysis of statistical results of 10 years data from Tianya. cn, which are further validated through the artificial community using computational experimental leverages. Experimental results illuminate that the individual's post publishing behavior is dominated by agent's psychological states, while the comment publishing behavior is more susceptible to the agent's social environment expressing the collective efforts of topics and other agents in the community. The artificial community has been used to test the impact of several factors (e.g., individual's psychological state, number of initial agents, and number of new added agents) to individual's message publishing mechanism and to cyber collective behavior patterns. It provides a software-defined social lab.ratory for social and cyber behavior studies with computational experimental measures.

关键词： Artificial community computational experiments cyber interactive behavior message publishing mechanisms multiagent-based modeling (MAM)

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Maximizing Time-discounted Influential Sustainability in Social Networks

Maximizing Time-discounted Influential Sustainability in Soc...

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IEEE International Conference on systems, Man, and Cybernetics (SMC)

作者： Zeng, Shuai Ni, Xiaochun Li, Juanjuan Yuan, Yong Wang, Shuai Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266000 Shandong Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781538616451

In social marketing practice, it is usually important to anticipate the long-term impact of the target application to maintain a long-lasting marketing effect, whereas a new product or technology should spread as quickly as possible to establish a competitive advantage. To find a balance between them, we tackle this challenge by modelling the problem as an issue of time-discounted influential sustainability. Given a threshold mu, the goal of the problem is finding a small subset of nodes as seeds and deciding the optimal timing to activate each seed that could maximize the time-discounted number of iterations, each of which actives more than mu nodes. We prove that solving the problem is NP-hard and the objective function is non-negative, non-monotonic, and non-submodular. Therefore we propose a greedy approach to approximately solve this problem. Our experimental results demonstrate that our solution outperforms two baseline algorithms. In order to provide meaningful advices for advertisers on selecting proper initial seed users, we further analyze and compare the performance of four seeding strategies on three typical types of social networks.

关键词： social marketing influence sustainability information diffusion seeding strategy

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Estimating Sink Parameters of Stochastic Functional-Structural Plant Models Using Organic Series-Continuous and Rhythmic Development

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FRONTIERS IN PLANT SCIENCE 2018年 9卷 1688-1688页

作者： Kang, Mengzhen Hua, Jing Wang, Xiujuan de Reffye, Philippe Jaeger, Marc Akaffou, Selastique Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst LIAMA Beijing Peoples R China Qingdao Acad Intelligent Ind Innovat Ctr Parallel Agr Qingdao Peoples R China Beijing Engn Res Ctr Intelligent Syst & Technol Beijing Peoples R China Univ Montpellier CNRS Amap Unit CIRADINRAIRD Montpellier France Univ Jean Lorougnon Guede Dept Seeds & Seedlings Prod Daloa Ivory Coast Cote Ivoire

Functional-structural plant models (FSPMs) generally simulate plant development and growth at the level of individual organs (leaves, flowers, internodes, etc.). Parameters that are not directly measurable, such as the sink strength of organs, can be estimated inversely by fitting the weights of organs along an axis (organic series) with the corresponding model output. To accommodate intracanopy variability among individual plants, stochastic FSPMs have been built by introducing the randomness in plant development;this presents a challenge in comparing model output and experimental data in parameter estimation since the plant axis contains individual organs with different amounts and weights. To achieve model calibration, the interaction between plant development and growth is disentangled by first computing the occurrence probabilities of each potential site of phytomer, as defined in the developmental model (potential structure). On this basis, the mean organic series is computed analytically to fit the organ-level target data. This process is applied for plants with continuous and rhythmic development simulated with different development parameter sets. The results are verified by Monte-Carlo simulation. Calibration tests are performed both in silico and on real plants. The analytical organic series are obtained for both continuous and rhythmic cases, and they match well with the results from Monte-Carlo simulation, and vice versa. This fitting process works well for both the simulated and real data sets;thus, the proposed method can solve the source-sink functions of stochastic plant architectures through a simplified approach to plant sampling. This work presents a generic method for estimating the sink parameters of a stochastic FSPM using statistical organ-level data, and it provides a method for sampling stems. The current work breaks a bottleneck in the application of FSPMs to real plants, creating the opportunity for broad applications.

关键词： greenlab inverse method source-sink parameters functional-structural plant model stochastic development parameter estimation

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Optimization of light intensity in a controlled ecological life support system based on a knowledge- and data-driven modeling approach

Optimization of light intensity in a controlled ecological l...

引用

Chinese Automation Congress (CAC)

作者： Fan Xing-Rong Wang Xiujuan Hua Jing Wang Haoyu Kang Mengzhen Chongqing Univ Posts & Telecommun Elect Informat & Networking Res Inst Chongqing 400065 Peoples R China CASIA LIAMA State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Sci Qingdao Peoples R China

ISBN: (纸本)9781538635247

A controlled Ecological Life Support System (CELSS) is necessary for the long-term manned space exploration. A primary goal of plant research for CELSS is to generate the largest amount of edible biomass possible for the least amount of electrical energy used. A key factor for implementing crop production systems will be the development of energy-efficient lighting approaches. Artificial lighting is essential in plant production in a CELSS, and energy reduction is one of the most important problems to be solved. The objective of this study is to provide a scheme of light intensity control in order to determine the most suitable light intensity in CELSS for plant cultivation, which can minimum the energy consumption and meet the demand of plant production and oxygen for the crew based on a knowledge-and data-driven modeling approach. The results indicate that the optimization method can increase 11.5% light use efficiency compared to the previous experimental set. Moreover, the biomass production increases under the optimized light intensity. This approach provides a computational basis for life-time optimization of cabin design and experimental setup of CELSS.

关键词： Optimization knowledge-and data-driven modeling CELSS Light intensity Energy consumption

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