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Analyzing the characteristics of "East Turkistan" activities using text mining and network analysis

Zidonghua Xuebao/Acta Automatica Sinica 2014年第11期40卷 2456-2468页

作者： Fu, Ju-Lei Liu, Wen-Li Zheng, Xiao-Long Fan, Ying Wang, Shou-Yang College of Information System and Management National University of Defense Technology Changsha410073 China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Management and Control Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Cloud Computing Industrial Technology Innovation and Incubation Center Chinese Academy of Sciences Dongguan523808 China School of Systems Science Beijing Normal University Beijing100875 China

Open source intelligence, with rich content and sophisticated collection and analytical techniques, is an alternative data source in many anti-terrorism studies and has manifested significant applicable prospects. In this paper, we take the "East Turkistan" separatist activities as the research objects and collect the data from the world wide web by utilizing web crawlers. We adopt text analysis techniques to extract the information of four fundamental elements of "East Turkistan" separatist activities, including person, organization, time and place, and then construct multi-mode networks according to the relations between concepts. To analyze the characteristics of these networks, we first apply the approach of dimensional decomposition to separate the multimode networks into single vertex sub-networks and bipartite sub-networks, distinguish the importances of different types of nodes by measuring the centrality of each sub-network, and synthesize the centrality index of each sub-network to form an importance composite index (ICI). To further identify the core nodes of the four types of nodes in the network, we adopt the k-shell decomposition method to directly decompose the multi-mode network. We find that the results produced by these approaches presented above can be in accord with the actual ones. ©, 2014, Acta Automatica Sinica. All rights reserved.

关键词： Data mining

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Use the core clusters for the initialization of the clustering based on one-class support vector machine

Use the core clusters for the initialization of the clusteri...

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4th International Conference on Advances in Swarm Intelligence, ICSI 2013

作者： Gu, Lei Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China School of Computer Science and Technology Nanjing University of Posts and Telecommunications Nanjing 210023 China

ISBN: (纸本)9783642387142

The clustering method based on one-class support vector machine has been presented recently. Although this approach can improve the clustering accuracies, it often gains the unstable clustering results because some random datasets are employed for its initialization. In this paper, a novel initialization method based on the core clusters is used for the clustering algorithm based one-class support vector machine. The core clusters are gained by constructing the neighborhood graph and they are regarded as the initial datasets of the clustering algorithm based one-class support vector machine. To investigate the effectiveness of the proposed approach, several experiments are done on four datasets. Experimental results show that the new presented method can improve the clustering performance compared to the previous clustering algorithm based on one-class support vector machine and k-means approach. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Support vector machines

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An evolutionary semi-supervised subtractive clustering method by seeding

An evolutionary semi-supervised subtractive clustering metho...

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2012 International Conference on Information technology and Software Engineering, ITSE 2012

ISBN: (纸本)9783642345210

A semi-supervised subtractive clustering has been proposed recently. However, it performance depends greatly on the choice of the parameters of the mountain function and only proper parameters enable the clustering method to produce a better effect. In this paper, an evolutionary semi-supervised subtractive clustering method by seeding is presented. The novel approach uses the genetic algorithms for tuning the relative parameters of the subtractive clustering by minimizing the Davies Bouldin clustering validity index regarded as the fitness function. To investigate the effectiveness of our approach, several experiments are done three real datasets. Experimental results show that our proposed method can improve the clustering performance significantly compared to other two traditional semi-supervised clustering algorithms. © 2013 Springer-Verlag.

关键词： Genetic algorithms

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The roles of sampling zero dynamics in the discrete-time models for linear and nonlinear systems

The roles of sampling zero dynamics in the discrete-time mod...

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Chinese Control Conference (CCC)

作者： Shan Liang Cheng Zeng Ishitobi Mitsuaki Jiaqi Zhong Key Laboratory of Dependable Service Computing in Cyber Physical SocietyMinistry of Education Chongqing University Chongqing P. R. China College of Automation Chongqing University Chongqing P. R. China Graduate School of Science and Technology Kumamoto University Kumamoto Japan

It is well-known that the occurrence of sampling zero dynamics is relevant to the problem of discrete-time and sampled-data control for linear and nonlinear continuous-time systems. In particular, the sampling zero dynamics play also a very important role in the linear and nonlinear discrete-time transfer function and controller design. Here we explore some worthwhile results on the asymptotic properties of sampling zero dynamics to gain important new insights into the effect of sampling for linear and nonlinear systems. These results also demonstrate that the discrete-time models have to account, to some extent, for the sampling zero dynamics when considering the discrete dynamics behavior of the real control systems.

关键词： Stability criteria Transfer functions Educational institutions Asymptotic stability Nonlinear dynamical systems

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Covariance free incremental principal component analysis with exact mean update

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Journal of Computational Information systems 2013年第16期9卷 6703-6710页

作者： Zeng, Xueqiang Li, Guozheng The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China Computer Center Nanchang University Nanchang 330029 China Department of Control Science and Engineering Tongji University Shanghai 201804 China

Incremental feature extraction is an essential data preprocessing technique for large-scale and streaming data mining. Among various covariance matrix-free Incremental Principal Component Analysis (IPCA) methods, Candid Covariance-free Incremental Principal Component Analysis (CCIPCA) is a state-of-the art algorithm. Since the training samples are required to be centred, CCIPCA applies an approximate centric alignment on the input data, where only the current sample is correctly centred and all historical data are not updated properly. In this paper, we propose a novel centred incremental principal component analysis algorithm with exact historical mean update, where not only the current sample is centred, but also all historical data are updated by the current mean correctly. Compared to CCIPCA, the proposed method converges more quickly, and the performance improvement is especially obvious when the data's inherent covariance is not stable. The experiments on real streaming dataset show that the proposed method is much superior to CCIPCA in convergence speed. © 2013 Binary Information Press.

关键词： Principal component analysis

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Online boosting tracking with fragmented model

Online boosting tracking with fragmented model

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19th International Conference on Advances in Multimedia Modeling, MMM 2013

作者： Shen, Dingcheng Zhang, Hua Xue, Yanbing Xu, Guangping Gao, Zan Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology 300384Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology 300384Tianjin China

ISBN: (纸本)9783642357275

We propose a novel method combining online boosting and fragment to overcome the drifting problem in on-line boosting tracking. We find that in previous on-line boosting method, the voting weights of the first few selectors are so big that the remainders can not affect the final strong classifier. This problem occurs because the voting weight of selectors are passing globally to adapt to the object variation, but usually only parts of object changes significantly in short time, and the changing part only affect its neighborhood, not the whole target area. So we divide the selector into fragments to get spatial information. The best weak classifier in each selector is combined linearly to get the final strong classifier and then find the location of the object in next frame. Experiments show robustness and generality of the proposed method. © Springer-Verlag 2013.

关键词： Computers

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Data interpolating over RFID data streams for missed readings

Data interpolating over RFID data streams for missed reading...

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

作者： Xiao, Yingyuan Jiang, Tao Li, Yukun Xu, Guangquan Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Key Laboratory of Computer Vision and System Tianjin University of Technology 300384 China School of Computer Science and Technology Tianjin University 300072 Tianjin China

ISBN: (纸本)9783642395260

While tracing objects or analyzing human activities with RFID data sets, the quality of RFID data is a crucial aspect. The raw RFID data streams, however, tend to be noisy, including missed readings and unreliable readings. Traditional data cleaning tends to focus on a small set of well-defined tasks, including transformation, matching, and duplicate elimination. In this paper, we focus on exploring efficient methods for interpolating missed readings. We propose a novel probabilistic interpolating method and three novel deterministic interpolating methods based on time interval, containment relationship and inertia of objects, respectively. We conduct extensive experiments and the experimental results demonstrate the feasibility and effectiveness of our methods. © 2013 Springer-Verlag.

关键词： Radio frequency identification (RFID)

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Research on domain ontology-based concept similarity calculation

Research on domain ontology-based concept similarity calcula...

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2nd International Conference on Engineering and technology Innovation 2012, ICETI 2012

作者： Li, Wenjie Shi, Shasha Liu, Si Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology 300384 Tianjin China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology 300384 Tianjin China

ISBN: (纸本)9783037856123

Similarity computing of ontological concept has made rapid progress in the field of data mining, information processing and artificial intelligence and becoming one of the hot research field of information technology, particularly the idea of the semantic Web was proposed in 2000, the concept of semantic similarity has gotten more attention, while also facilitating its further development and application in information retrieval. Considering the deficiencies of existing concept similarity algorithm, this paper design the method to reduce the candidate set of domain concept, and put forward a similarity calculation model based on the concept name, instances, properties, and semantic structure of domain ontology. Integrated several main influencing factors, the experiments show the proposed algorithm can express the impact of various factors on the similarity in the calculation concept similarity of domain ontology. By comparing with the traditional similarity method and expertise experience value, the experiment result shows that the effectiveness and correctness of the concept similarity calculation model. © (2013) Trans Tech Publications, Switzerland.

关键词： Data mining

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An evaluation approach based on word-of-mouth for trust models in recommendation systems

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Computer Modelling and New Technologies 2014年第11期18卷 605-609页

作者： Jiang, Feng Gao, Min Xia, Hui Xiong, Qingyu Wen, Junhao College of Civil Engineering Chongqing University Chongqing China College of Construction Engineering Chongqing Technology and Business Institute Chongqing China School of Software Engineering Chongqing University Chongqing China Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing China

Recommendation systems have been recognized as an effective approach to heavy information load. In recommendation systems, trust/reputation has attracted increasing attention because it helps to improve the precision of recommendation and the robustness of systems to shilling attacks. Recommendation system oriented trust models, mostly rating-based, used to build the reputation and trustiness among users. They are often evaluated in terms of how accurately they help to predict user ratings and how robustly they resist shilling attacks. However, those evaluation techniques disregard the trust values themselves: how accurately they calculate the trust values themselves is not measured. To solve the problem, in this work, we propose an approach to measure the trust values based on electronic word-of-mouth (eWoM) theory. The eWoM believes a user is reliability if he is of good public praise. In our approach, firstly, according to eWoM, the reliability value of a user can be judged by other users' votes - whether the user's ratings or feedbacks are positive or negative. Secondly, the trust values of users can be calculated by a trust model. Finally, we compare trust values and reliability values. As a case study, we propose a simple rating-based trust model and then evaluate the trust model based on the proposed evaluation approach and Amazon dataset.

关键词： Recommender systems

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Design of a new solution for the wheeled hopping robot

Design of a new solution for the wheeled hopping robot

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UKACC International Conference on Control (CONTROL)

作者： Jingjing Liu Hongbo Wang Hongnian Yu Lili Zhang Luige Vladareanu Adrian Bruja Gal I. Alexandru Parallel Robot and Mechatronic System Laboratory of Hebei Province Key Laboratory of Advanced Forging & Stamping Technology and Science of Ministry of Education Yanshan University Qinhuangdao China College of Electrical Engineering Yanshan University Qinhuangdao China School of Design Engineering and Computing Bournemouth University Poole UK Robotics and Mechatronic Department Institute of Solid Mechanics Bucharest Romania

In recent years many researchers are trying to combine wheeled movement with legged movement or hopping movement to strengthen the robots adaptability to environment. Hybrid robots are playing a more and more important role in our modern life. However, their controls are mostly complicated. So in this paper we present a new solution for the wheeled hopping robot. Based on the mechanical design, this robot has two movement modes: wheeled and hopping movement mode. While the center of gravity of the mechanism is under the wheels center, the wheeled hopping robot which is like a tumbler can keep its stability even when the wheels' velocity is zero. In this paper, we firstly introduce the description and design of the wheeled hopping robot. Then we explain how to choose the robot parameters and lastly we describe, how the robot through hopping, successfully traverses obstacles and ditches.

关键词： Mobile robots Shafts Wheels Springs Robot kinematics Force

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