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6th China Conference of Wireless Sensor Networks, CWSN 2012

作者： Li, Peng Wang, Ruchuan Zhou, Yanting Dai, Qiuyu College of Computer Nanjing University of Posts and Telecommunications Nanjing Jiangsu 210003 China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing Jiangsu 210003 China Key Lab. of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Jiangsu Province Nanjing Jiangsu 210003 China College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing Jiangsu 210003 China

ISBN: (纸本)9783642362514

According to the significant impact on the accuracy rate of detection of current immune algorithms brought by incorrect classification of signal, it proposes network malicious code dendritic cell immune algorithm based on fuzzy weighted support vector machine. It summarizes and compares the pros and cons of the four methods, which are basic artificial intelligence immune algorithm, detection of unknown viruses based on immunity theory, malicious code immunity based on cryptography and automated intrusion response based on danger theory. It elaborates the process of the algorithm of the proposed immune algorithm, discusses a variety of input and output signals, gives the samples of the actual input signals, applies the coefficient of variation method to determine the values of the weights so as to enhance the discrimination ability of signal processing results, describes the principle and algorithm steps of fuzzy weighted support vector machine clustering method within immune algorithm proposed. By comparing the fuzzy aggregation before and after the immunization program experiments, it draws the conclusion that the proposed immune algorithm can optimize the input signal, fuzzy clustering the signal and the antigen, so as to bring down the number of immunization strategies and reduce the immune response time, as a result it improve the efficiency and performance of the immune system. © 2013 Springer-Verlag.

关键词： Cells

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Optimal pricing for improving efficiency of taxi systems

Optimal pricing for improving efficiency of taxi systems

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23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

作者： Gan, Jiarui An, Bo Wang, Haizhong Sun, Xiaoming Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China Oregon State University Corvallis OR 97331 United States

ISBN: (纸本)9781577356332

In Beijing, most taxi drivers intentionally avoid working during peak hours despite of the huge customer demand within these peak periods. This dilemma is mainly due to the fact that taxi drivers' congestion costs are not reflected in the current taxi fare structure. To resolve this problem, we propose a new pricing scheme to provide taxi drivers with extra incentives to work during peak hours. This differs from previous studies of taxi market by considering market variance over multiple periods, taxi drivers' profit-driven decisions, and their scheduling constraints regarding the interdependence among different periods. The major challenge of this research is the computational intensiveness to identify optimal strategy due to the exponentially large size of a taxi driver's strategy space and the scheduling constraints. We develop an atom schedule method to overcome these issues. It reduces the magnitude of the problem while satisfying the constraints to filter out infeasible pure strategies. Simulation results based on real data show the effectiveness of the proposed methods, which opens up a new door to improving the efficiency of taxi market in megacities (e.g., Beijing).

关键词： Traffic congestion

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Community evolution in dynamic social networks

Community evolution in dynamic social networks

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3rd International Conference on Materials Science and information technology, MSIT 2013

作者： Wang, Gang Lei, Yu Li Wang, Chong Jun Qiao, Shao Jie Department of Computer Science and Technology Sichuan Police College Luzhou Sichuan 646000 China National Key Laboratory for Novel Software Technology Nanjing University Nanjing Jiangsu 210093 China School of Information Science and Technology Southwest Jiaotong University Chengdu Sichuan 610031 China

ISBN: (纸本)9783037857700

This paper proposed a framework and an algorithm for identifying communities in dynamic social networks. In order to handle the drawbacks of traditional approaches for social network analysis, we utilize the community similarities and infrequent change of community members combined with community structure optimization to develop a Group-based social community identification model to analyze the change of social interaction network with multiple time steps. According to this model, we introduced a greed-cut algorithm and depth-search-first approach and combine them to develop a new algorithm for dynamic social interaction network recognition (called ADSIN). In addition, we conduct experiments on the dataset of Southern Women, the experiment results validate the accuracy and effectiveness of ADSIN. © (2013) Trans Tech Publications, Switzerland.

关键词： Structural optimization

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Frequent itemset mining over stream data: Overview

Frequent itemset mining over stream data: Overview

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IET International Conference on information and Communications Technologies, IETICT 2013

作者： Qu, Z.G. Niu, X.X. Deng, J. McArdle, C. Wang, X.J. Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 China School of Electronic Engineering Dublin City University Dublin Ireland Key Laboratory of Network and Information Attack and Defence Technology of MOE Beijing University of Posts and Telecommunications Beijing 100876 China

ISBN: (纸本)9781849196536

During the past decade, stream data mining has been attracting widespread attentions of the experts and the researchers all over the world and a large number of interesting research results have been achieved. Among them, frequent itemset mining is one of main research branches of stream data mining with a fundamental and significant position. In order to further advance and develop the research of frequent itemset mining, this paper summarizes its main challenges and corresponding algorithm features. Based on them, current related results are divided into two categories: data-based algorithms and task-based algorithms. According to its taxonomy, the related methods belonging to the different categories and sub-categories are comprehensively introduced for better understanding. Finally, a brief conclusion is given.

关键词： Data mining

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Feature selection as maximum-weight independent set

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ICIC Express Letters, Part B: Applications 2013年第4期4卷 1053-1058页

作者： Zhao, Huinan Wang, Jisong Lu, Yinghua Sun, Hui Wang, Jianzhong College of Humanities and Sciences Northeast Normal University No. 2555 Jingyue Street Changchun 130117 China College of Computer Science and Information Technology Northeast Normal University No. 2555 Jingyue Street Changchun 130117 China Key Laboratory of Intelligent Information Processing of Jilin Universities Northeast Normal University No. 2555 Jingyue Street Changchun 130117 China National Engineering Laboratory for Druggable Gene and Protein Screening Northeast Normal University No. 2555 Jingyue Street Changchun 130117 China

Feature selection is a particularly important step in analyzing the data such as image, text and video. It aims to select the most important features from the original data so that the performances of classification and recognition will be improved. Many feature selection methods have been proposed in the past decades. However, these methods always focus on the importance of the features or the correlation among the features independently. Moreover, how to determine the optimal number of selected features is also a hard task. In order to overcome these limitations, we propose a novel feature selection framework termed feature selection as maximum-weight independent set (FS-MWIS). In our approach, we use the theory of the maximum-weight independent set to select the subset of features with the maximum importance and minimum redundancy. Meanwhile, the optimal number of features selected by our framework can be automatically determined. The performances of our algorithm are tested and compared with other algorithms on two face databases. Extensive experiments show the superiority and effectiveness of our proposed algorithm. © 2013 ISSN 2185-2766.

关键词： Feature Selection

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An improved breast mass segmentation method for mammography based on dynamic programming

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ICIC Express Letters, Part B: Applications 2013年第5期4卷 1189-1195页

作者： Zhao, Dawei Yu, Lili Lu, Yinghua Sun, Hui Wang, Jianzhong College of Humanities and Sciences Northeast Normal University No. 2555 Jingyue Street Changchun 130117 China College of Computer Science and Information Technology Northeast Normal University No. 2555 Jingyue Street Changchun 130117 China Key Laboratory of Intelligent Information Processing of Jilin Universities Northeast Normal University No. 2555 Jingyue Street Changchun 130117 China National Engineering Laboratory for Druggable Gene and Protein Screening Northeast Normal University No. 2555 Jingyue Street Changchun 130117 China

Breast mass segmentation is often regarded as a critical step in breast cancer identification. In this paper, we propose a new mass segmentation approach by modifying the local cost function in the dynamic programming algorithm [1]. The modified local cost function in our method can effectively reflect the edge characteristics, and obtain more accurate segmentation result. In addition, maximum margin criterion is used to generate optimization features from the original feature set. The effectiveness of the proposed method is verified on MIAS and DDSM mammography image databases. We use an overlap criterion to evaluate the accuracy of our proposed segmentation method. The mean average of overlap percentage for original dynamic programming is 0.71, and for improved dynamic programming approach is 0.74. Moreover, the improvement of the mass classification result based on the proposed segmentation method also proves the superiority of our algorithm. © 2013 ISSN 2185-2766.

关键词： Dynamic programming

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未来视频技术专题(英文)

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China Communications 2013年第5期 8-10页

作者：陈熙霖朱秀昌王桥胡栋 Ming-Ting SUN the Institute of Computing Technology Chinese Academy of Sciences (CAS) the IEEE Transactions on Image Processing the Journal of Computer Science and Technology the Chinese Journal of Computers College of Communications and Information Engineering NUPT Image Processing and Image Communications Key Laboratory of Information Industrial Ministry and Jiangsu Province Signal and Information Processing Laboratory Southeast University

In the past few years, video has become one of the most powerful engines to push communications forward. The increasing of digital video technology requires larger and larger bandwidth for various applications, such as IPTV, VOD, video phone, mobile search, etc. The goal of this Feature Topic column is to present and highlight the latest progress and future video-related technologies. We hope this

关键词： IEEE over

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A graph-based multi-hop cooperative MIMO scheme for heterogeneous WSN

A graph-based multi-hop cooperative MIMO scheme for heteroge...

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6th China Conference of Wireless Sensor Networks, CWSN 2012

作者： Li, Zhetao Xie, Da Pei, Tingrui Choi, Youngjune Li, Renfa College of Information Engineering Xiangtan University Xiangtan 411105 China School of Computer National University of Defense Technology Changsha 410073 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan 411105 China Department of Information and Computer Engineering Ajou University Suwon 443749 Korea Republic of School of Computers and Communications Hunan University Changsha 410082 China

ISBN: (纸本)9783642362514

A Graph-based multi-hop cooperative MIMO transmission scheme (GM-MIMO) aimed at optimizing the network lifetime and saving energy for heterogeneous wireless sensor networks (WSN) is proposed. In GM-MIMO, clusters are established based on geographical position. Graph theory is applied to find an optimal forwarding path. For taking the presence of node heterogeneity into consideration, GM-MIMO obtains maximum network lifetime. Simulation results show that GM-MIMO makes a significant performance improvement in terms of network lifetime and survival rate of nodes. © 2013 Springer-Verlag.

关键词： Graph theory

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A MANOVA of historical and unhistorical factors for traffic volume forecasting

A MANOVA of historical and unhistorical factors for traffic ...

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2nd International Conference on Transportation information and Safety: Improving Multimodal Transportation Systems - information, Safety, and Integration, ICTIS 2013

作者： Shan, Zhenyu Qiu, Renbo Xia, Yingjie Hangzhou Institute of Service Engineering Hangzhou Normal University #222 Wenyi Road Zhejiang 310012 China Hangzhou Normal University China Provincial Key Laboratory for Computer Information Processing Technology Hangzhou Normal University Soochow University Soochow China Zhejiang Center for ITS Engineering and Technology China

ISBN: (纸本)9780784413036

Traffic congestion has become a serious social problem. One way to ease traffic congestion is traffic volume forecasting, which is helpful to support decision-making for management or provide better route selection for passengers. Nowadays, the historical traffic flow data are used as the original input data for predictor training in forecasting and proves helpful for forecasting. However, other non-historical factors, such as weather condition and holidays, can also influence traffic volume and are often ignored in recent forecasting researches. This paper applied a Multivariate analysis of variance (MANOVA) for analyzing the relation between traffic volume and the unhistorical factors. The experiments are carried out on the data collected from a section of a national road, which show that weather conditions and holidays are helpful for traffic forecasting. © 2013 American Society of Civil Engineers.

关键词： Traffic congestion

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Moving vehicle detection and tracking in traffic images based on horizontal edges

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Telkomnika - Indonesian Journal of Electrical Engineering 2013年第11期11卷 6477-6483页

作者： Zhu, Hongjin Fan, Honghui Guo, Shuqiang School of Computer Engineering Jiangsu University of Technology Changzhou 213001 Jiangsu China Key Laboratory of Cloud Computing Intelligent Information Processing of Changzhou City China School of Information Engineering Northeast Dianli University Jilin 132012 Jilin China

This paper presents a moving vehicle detection and tracking system, which comprising of Horizontal Edges method and Local Auto Correlation. Horizontal Edges characteristic can be strengthened and the influence of weather condition is reduced by using Local Auto Correlation, so the detection rate of extracting and tracking moving vehicles with horizontal edge can be raised. Local Auto Correlation images are generated for vehicle detection and based on Horizontal Edges method. The distance of the gravity center of Horizontal Edges is used to track vehicles in traffic video. We verify the system using a variety of weather (in fog, car shadow existence, morning and evening) traffic video. Experimental results have shown that the high detection rate of moving vehicles be obtained by using the proposed method. © 2013 Universitas Ahmad Dahlan.

关键词： Tracking (position)

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