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International Conference on Intelligent Transportation

作者： Ye Li Fei-Yue Wang Bo Li Bin Tian Fenghua Zhu Gang Xiong Kunfeng Wang Institute of Automation State Key Laboratory of Management and Control for Complex Systems Beijing China Chinese Academy of Sciences Cloud Computing Center Dongguan China

In traffic video surveillance systems, vehicles with various distances from the camera have different sizes, resolutions, and angles in traffic images. The common multi-scale method, which scales one vehicle template or the input image for detecting vehicles with different sizes, may fail to detect vehicles with various distances from the camera due to the change of the resolution and angle. To deal with this problem, we have proposed a multi-scale model including multiple templates with different scales and features. Our method includes two steps: constructing the multi-scale model and its probability model, and detecting vehicles from traffic images. In the first step, the multi-scale model is constructed by using three templates T 1 , T 2 , T 3 which represent vehicles with the short, medium, and long distance from the camera respectively. Each template contains one or some combination of sketch, texture, flatness, and color. In the second step, the three templates are applied for vehicle detection by using the template matching with local maximization operations. The main innovation of this paper is that the combination of multi-template and multi-scale method is applied to detect vehicles with various distances from the camera. To test our method, we have done several experiments on various traffic conditions. The experimental results show that our method effectively copes with vehicles with various distances from the camera and provides the detailed vehicle information after vehicle detection. Moreover, our method adapts to various weather conditions, slight pose variance, and slight occlusion.

关键词： Vehicles Vehicle detection Image color analysis Cameras Image edge detection Training Image resolution

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An empirical study of information diffusion in micro-blogging systems during emergency events

An empirical study of information diffusion in micro-bloggin...

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14th International Conference on Web-Age Information management, WAIM 2013

作者： Cui, Kainan Zheng, Xiaolong Zeng, Daniel Dajun Zhang, Zhu Luo, Chuan He, Saike School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan 523808 China

ISBN: (纸本)9783642395260

Understanding the rapid information diffusion process in social media is critical for crisis management. Most of existing studies mainly focus on information diffusion patterns under the word-of-mouth spread mechanism. However, to date, the mass-media spread mechanism in social media is still not well studied. In this paper, we take the emergency event of Wenzhou train crash as a case and conduct an empirical analysis, utilizing geospatial correlation analysis and social network analysis, to explore the mass-meida spread mechanism in social media. By using the approach of agent-based modeling, we further make a quantativiely comparison with the information diffusion patterns under the word-of-mouth spread mechanism. Our exprimental results show that the mass-meida spread mechanism plays a more important role than that of the word-of-mouth in the information diffusion process during emergency events. The results of this paper can provide significant potential implications for crisis management. © 2013 Springer-Verlag.

关键词： Information management

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Remembering Dave Waltz (1943-2012) IN MEMORIAM

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IEEE INTELLIGENT systems 2012年第4期27卷 86-88页

作者： Wang, Fei-Yue State Key Laboratory of Management and Control for Complex Systems

IEEE Intelligent systems remembers Dave Walz, a longtime member of its advisory board and a great friend.

关键词： Obituaries Waltz Dave IEEE Intelligent systems Dave Walz Advisory Board

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Forecasting complex group behavior via multiple plan recognition

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Frontiers of Computer Science 2012年第1期6卷 102-110页

作者： Xiaochen LI Wenji MAO Daniel ZENG State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Group behavior forecasting is an emergent re- search and application field in social computing. Most of the existing group behavior forecasting methods have heavily re- lied on structured data which is usually hard to obtain. To ease the heavy reliance on structured data, in this paper, we pro- pose a computational approach based on the recognition of multiple plans/intentions underlying group behavior. We fur- ther conduct human experiment to empirically evaluate the effectiveness of our proposed approach.

关键词： group behavior forecasting multiple planrecognition graph search

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University in the innovation system academia-industry collaborations and intellectual property rights

University in the innovation system academia-industry collab...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Helena Jin Gang Xiong Department of Industrial Engineering and Management School of Science Aalto University Espoo Finland The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

In a world where possessing raw materials or manufacturing commodities are not sufficient for long-term economic success, innovativeness and a knowledge-based economy form the basis for prosperity. In this report, we discuss the link between a nation's higher education system and its ability to bring about and foster innovativeness and economic growth. In particular, we will concentrate on the roles that universities play in the national innovation system. Some of the questions we address include: How strong a link is there between the education system and nation's innovativeness? How important is industry-academia collaboration? From the perspective of a knowledge-based economy, what would an ideal university be like? To answer these questions, we summarize key findings from the literature. The aim of this report is to present the key factors and decisions that should be considered in future higher education strategies.

关键词： Educational institutions Intellectual property Collaboration Technological innovation Industries Companies Economics

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A unified TDMA-based scheduling protocol for Vehicle-to-Infrastructure communications

A unified TDMA-based scheduling protocol for Vehicle-to-Infr...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Rongqing Zhang Jinsung Lee Xia Shen Xiang Cheng Liuqing Yang Bingli Jiao State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China School of Electronics Engineering and Computer Science Peking University Beijing China

In this paper, we propose a unified TDMA-based scheduling protocol for Vehicle-to-Infrastructure (V2I) communications. In the proposed TDMA-based scheduling protocol, the roadside infrastructure collects the information from the vehicles within its communication coverage through a control channel at the beginning of each transmission frame and then decides how to allocate the time slots to the vehicles for their data transmission requests based on a new designed weight-factor-based scheduler. The provided weight factor jointly takes into consideration the channel quality of communication links, the speed based fairness among vehicles, and different access categories. Simulation results verify the efficiency of the proposed scheduling protocol in terms of the network throughput performance, the fairness among the vehicles, and different accessing priorities of different access categories.

关键词： Vehicles Protocols Throughput IEEE 802.11 Standards Multiaccess communication Scheduling algorithms Data communication

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Automatic Road Detection for Highway Surveillance Using Frequency-Domain Information

Automatic Road Detection for Highway Surveillance Using Freq...

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IEEE International Conference on Service Operations and Logistics, and Informatics

作者： Qing-Jie Kong Lucidus Zhou Gang Xiong Fenghua Zhu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences

ISBN: (纸本)9781479905287

Video detection is one of the primary collection means of traffic states in Parallel traffic management systems (PtMS). In order to accurately and automatically obtain road areas in highway surveillance videos, this paper presents an automatic detection algorithm based on the frequency-domain information of video images. This algorithm uses the frequency-domain feature that is produced by the vehicles passing through road areas in videos, to realize automatic segmentation and recognition of the road areas. The experiment comparing with the traditional vehicle-tracking-based method, which uses the information in the time-space domain, illustrates the advantages of the proposed algorithm.

关键词： Road detection Visual surveillance Frequency information

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Discovering Seasonal Patterns of Smoking Behavior Using Online Search Information

Discovering Seasonal Patterns of Smoking Behavior Using Onli...

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IEEE International Conference on Intelligence and Security Informatics

作者： Zhu Zhang Xiaolong Zheng Daniel Dajun Zeng Kainan Cui Chuan Luo Saike He Scott Leischow The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences The School of Electronic and Information Engineering Xi'an Jiaotong University Mayo Clinic in Arizona

ISBN: (纸本)9781467362146

Discovering temporal patterns and changes in tobacco use has important practical implications in tobacco control. This paper presents one of the first comprehensive international studies of seasonal smoking patterns based on online searches performed. Using periodogram and cross-correlation, we find that smoking-related search behavior shows strong seasonality effect across countries. In addition, there are significant pairwise associations between such seasonality in different countries.

关键词： Behavior informatics Search behavior Smoking Seasonality

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OCC model-based emotion extraction from online reviews

OCC model-based emotion extraction from online reviews

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IEEE International Conference on Intelligence and Security Informatics, ISI

作者： Luwen Huangfu Wenji Mao Daniel Zeng Lei Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Automation Chinese Academy of Sciences Beijing Beijing CN

ISBN: (纸本)9781467362146

Extracting emotions from online reviews is crucial to many security-related applications as well as applications in other domains. Traditional approaches to emotion extraction have mainly focused on mining the polarities of opinions or using annotated data to extract emotion types. Emotion theories, which identify the underlying cognitive structure and emotional dimensions that are key to generate emotions, have almost been totally ignored in previous work. To facilitate the automatic extraction of emotions from textual data, in this paper, we propose an emotion model based approach to emotion extraction from online reviews. Informed by the widely used OCC emotion model, we employ a statistical method to extract emotion words with their dimension values from texts, and implement OCC model to obtain emotions based on the emotion-dimension dictionary. We conduct an empirical study using security-related news reviews. The experimental results demonstrate the effectiveness of our proposed approach.

关键词： Dictionaries Data mining Computational modeling Syntactics Intelligent systems Statistical analysis Psychology

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Boundary value problems for stochastic budget distribution in search advertisements

Boundary value problems for stochastic budget distribution i...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Rui Qin Yanwu Yang Feiyue Wang Daniel Zeng The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Automation Chinese Academy of Sciences Beijing Beijing CN

ISBN: (纸本)9781479905287

In sponsored search auctions, advertisers have to distribute the budget to a series of temporal slots in order to maximize the expected revenue. There exists a budget demand for each temporal slot, which can not be known exactly by the advertiser due to some uncertainties in the search marketing environments. The estimation of the value range of budget demand in a temporal slot seriously affects the advertising performance. In this paper we study the effect of the value range on the revenue and conduct some experiments to validate our model and identified properties with the real-world data collected from practical advertising campaigns. Experimental results show that, under a certain condition, (a) the higher estimation of the upper bound and the lower bound might increase the expected revenue, and (b) the expected revenue is positively proportional to the mean value of the value range and is negatively proportional to the size.

关键词： Estimation Advertising Upper bound Stochastic processes Random variables Search problems Data models

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