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A granularity attribute reduction method based on binary discernibility matrix

International Journal of Advancements in computing technology 2012年第12期4卷 213-221页

作者： Chang, Tong Shifei, Ding Hong, Zhu Hongjie, Jia Jian, Wang School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Geomatics College Shandong University of Science and Technology Qingdao 266510 China

At present, most of the attribute reduction algorithms based on granularity are simply computing the granularity of knowledge. Repeated calculation will increase the time complexity. Binary discernibility matrix is used to express binary form, which has a clear ascension whether in space or in time than the traditional discernibility matrix efficiency. On the basis of granularity-based attribute reduction, a method is proposed to preprocess the dataset by using binary discernibility matrix. Firstly, find the core attribute and a minimal reduction. Then use the granularity thought to calculate each particle of the importance of attributes. Most important is joined to the reduction set, thereby achieving the attributes reduction. The example analysis shows that the method can improve the performance of the traditional attribute reduction algorithms effectively. It is a feasible approach to reduce attributes.

关键词： Rough set theory

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A support vector extraction method based on clustering membership

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content technology and its Applications 2012年第13期6卷 1-10页

作者： Qi, Bingjuan Ding, Shifei Huang, Huajuan Yu, Junzhao Wang, Jian School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing 100190 China Geomatics College Shandong University of Science and Technology Qingdao 266510 China

Traditional support vector machine has disadvantages of slow training speed and great time consumption when dealing with large-scale datasets. This paper proposes a support vector extraction method based on clustering membership, which preprocesses the training datasets and extracts all possible support vectors for SVM training according to the memberships. Considering the training datasets may be linear or nonlinear, this paper severally uses FCM and KFCM to extract support vectors. Experiment results show that the method proposed in this paper can improve the training speed greatly in the condition of maintaining the classification accuracy.

关键词： Support vector machines

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Analysis of heavy metals in marine sediment using a portable X-ray fluorescence spectrometer onboard an Autonomous Underwater Vehicle

Analysis of heavy metals in marine sediment using a portable...

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OCEANS - Europe

作者： Jeremy Breen Paulo de Souza Greg Timms John McCulloch Robert Ollington School of Computing and Information Systems University of Tasmania Hobart TAS Australia Intelligent Sensing and Systems Laboratory CSIRO Hobart TAS Australia Human Interface Technology Laboratory University of Tasmania Launceston TAS Australia

Research is being conducted into performing chemical analysis of marine sediments in situ using an Autonomous Underwater Vehicle (AUV) equipped with an X-ray Fluorescence (XRF) spectrometer and X-ray tube. This is for the purpose of identifying regions of high heavy metal concentrations. A housing has been designed to safely attach the XRF system to the AUV. Work has been done on analysing sediment samples taken from the Derwent Estuary, Hobart, Tasmania using the analysis techniques that will be used on-board the AUV during a mission.

关键词： Sediments Sensors Pollution measurement Zinc Fluorescence Underwater vehicles

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Twin support vector machines based on rough sets

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content technology and its Applications 2012年第20期6卷 493-500页

作者： Yu, Junzhao Ding, Shifei Jin, Fengxiang Huang, Huajuan Han, Youzhen School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing 100190 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing 100876 China Geomatics College Shandong University of Science and Technology Qingdao 266510 China

TWSVM(Twin Support Vector Machines) is based on the idea of GEPSVM (Proximal SVM based on Generalized Eigenvalues), which determines two nonparallel planes by solving two related SVM-type problems, so that its computing cost in the training phase is 1/4 of standard SVM. In addition to keeping the superior characteristics of GEPSVM, the classification performance of TWSVM significantly outperforms that of GEPSVM. In order to further improve the speed and accuracy of TWSVM, this paper proposes the twin support vector machines based on rough sets. Firstly, using the rough sets theory to reduce the attributes, and then using TWSVM to train and predict the new datasets. The final experimental results and data analysis show that the proposed algorithm has higher accuracy and better efficiency compared with the traditional twin support vector machines.

关键词： Rough set theory

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A secure message delivery scheme with path tracking for delay tolerant networks

A secure message delivery scheme with path tracking for dela...

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IEEE International Conference on Communications in China (ICCC)

作者： Zhongtian Jia Muhammad Ali Raffay Lixiang Li Xiaodong Lin Yixian Yang Information Security Center Beijing University of Posts and Telecommunications China Shandong Provincial Key Laboratory of Network based Intelligent Computing University of Jinan Jinan China Faculty of Business and Information Technology Institute of Technology University of Ontario Oshawa ONT Canada

In delay tolerant networks (DTNs), message delivery is operated in an opportunistic way through store-carry and forward relaying, and every DTN node is in anticipation of cooperation for data forwarding from others. Unfortunately, there always exist some selfish nodes that are reluctant to contribute to this cooperative data forwarding procedure so as to save their valuable storage buffer, limited computation power and precious energy. In order to stimulate nodes' willingness to participate in data forwarding, a number of incentive schemes have been proposed recently. However, most existing incentive schemes simply ignore efforts of nodes involved in message delivery if messages delivered fail to reach their destinations. Due to the nature of DTN, such as intermittent connectivity, it is not unusual to have unreliable message delivery, which results in unrewarded or wasted efforts for participating nodes and may discourage them from participating in future data forwarding. Therefore, it is crucial to recognize contribution of every node involved in a data forwarding procedure even the message it helps to forward doesn't successfully reach its destination. However, how to track all delivery paths so as to give every intermediate node some incentive for their cooperative efforts of data forwarding is still an open research problem. To address this problem, we propose a secure message forwarding scheme with path tracking. The proposed method is end-to-end secure with data source and identity authentication. In addition, it can thwart some well known attacks including edge inserting attack, sibling inserting attack and free riding attack.

关键词： Nickel Public key Protocols Relays Joining processes

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Reconstructing 3D human poses from uncalibrated monocular images with strong perspective effects

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Journal of Computational information Systems 2012年第15期8卷 6437-6445页

作者： Chen, Shu Peng, Xiaoning School of Information Engineering Xiangtan Universtiy Xiangtan 411105 China Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Xiangtan 411105 China School of Information Science and Engineering Central South University Changsha 410083 China Department of Computer Science and Technology Huaihua College Huaihua 418008 China

This paper present a geometric method to reconstruct human motion pose from 2D point correspondences obtained from uncalibrated monocular images. The proposed algorithm can handle images with very strong perspective effects, which is guaranteed by the fact that only one scale factor corresponding to the root joint in the skeleton model is required estimating. To take fully advantage of this fact, a system of two nonlinear equations with two variables to estimate the scale factor of the root joint is established, and the scale factor of the root joint is optimized by the Gauss-Newton iterative scheme. At last, a framework to reconstruct human motion pose is presented. Quantitive analysis of the experiment results based on several real monocular video sequences shows the accuracy of the scale factor as well as the accuracy of the pose reconstruction. © 2012 Binary information Press.

关键词： Nonlinear equations

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STRUCTURED SPARSE LINEAR DISCRIMINANT ANALYSIS

STRUCTURED SPARSE LINEAR DISCRIMINANT ANALYSIS

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IEEE International Conference on Image Processing

作者： Zhen Cui Shiguang Shan Haihong Zhang Shihong Lao Xilin Chen School of Computer Science and Technology Huaqiao University Xiamen China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Omron Social Solutions Company Limited Kyoto Japan

Linear Discriminant Analysis (LDA) is an efficient image feature extraction technique by supervised dimensionality reduction. In this paper, we extend LDA to Structured Sparse LDA (SSLDA), where the projecting vectors are not only constrained to sparsity but also structured with a pre-specified set of shapes. While the sparse priors deal with small sample size problem, the proposed structure regularization can also encode higher-order information with better interpretability. We also propose a simple and efficient optimization algorithm to solve the proposed optimization problem. Experiments on face images show the benefits of the proposed structured sparse LDA on both classification accuracy and interpretability.

关键词： Face Face recognition Databases Linear discriminant analysis Optimization Training Algorithm design and analysis

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Adaptive loop filter with temporal prediction

Adaptive loop filter with temporal prediction

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Picture Coding Symposium, PCS

作者： Xinfeng Zhang Ruiqin Xiong Siwei Ma Wen Gao Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Institute of Digital Media Peking University Beijing China

In this paper, we propose a method to improve adaptive loop filter (ALF) efficiency with temporal prediction. For one frame, two sets of adaptive loop filter parameters are adaptively selected by rate distortion optimization. The first set of ALF parameters is estimated by minimizing the mean square error between the original frame and the current reconstructed frame. The second set of filter parameters is the one that is used in the latest prior frame. The proposed algorithm is implemented in HM3.0 software. Compared with the HM3.0 anchor, the proposed method achieves 0.4%, 0.3% and 0.3% BD bitrate reduction in average for high efficiency low delay B, high efficiency low delay P and high efficiency random access configuration, respectively. The encoding and decoding time increase by 1% and 2% on average, respectively.

关键词： Adaptive filters Wiener filter Filter banks Encoding Rate-distortion Image reconstruction Decoding

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Rough fuzzy subspaces based on subspaces in the vector space

Rough fuzzy subspaces based on subspaces in the vector space

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IEEE International Conference on Granular computing (GRC)

作者： Mingfen Wu Tao Chen School of Computer Science Wuyi University Guangdong China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science Wuyi University China

Rough set theory and fuzzy set theory are complementary generalizations of classical set *** paper concerns with rough sets,fuzzy sets and vector *** construct a rough fuzzy sets model based on a congruence of a vector space and it is assumed that the knowledge about a vector space should be restricted by a ***, we research fuzzy subs paces of the vector space over a field, and get a series of properties. Specifically,we construct the minimum fuzzy subspace containing two fuzzy subspaces in a vector space. Secondly, we define concepts of the lower(upper) approximations of fuzzy subsets with respect to a subspace, and give some properties of the lower and the upper approximations of fuzzy subsets. Finally, we focus on fuzzy subspaces of the vector space, and define the lower(upper) rough fuzzy subspaces and the rough fuzzy subspaces of the vector space. We obtain that a fuzzy subspace is certainly a rough fuzzy subspace, the intersection and sum of two fuzzy subspaces are also rough fuzzy subs paces and other valuable results.

关键词： Educational institutions Vectors Fuzzy logic

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Image sets alignment for Video-Based Face Recognition

Image sets alignment for Video-Based Face Recognition

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Zhen Cui Shiguang Shan Haihong Zhang Shihong Lao Xilin Chen School of Computer Science and Technology Huaqiao University Xiamen China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing China Omron Social Solutions Company Limited Kyoto Japan

Video-based Face Recognition (VFR) can be converted to the matching of two image sets containing face images captured from each video. For this purpose, we propose to bridge the two sets with a reference image set that is well-defined and pre-structured to a number of local models offline. In other words, given two image sets, as long as each of them is aligned to the reference set, they are mutually aligned and well structured. Therefore, the similarity between them can be computed by comparing only the corresponded local models rather than considering all the pairs. To align an image set with the reference set, we further formulate the problem as a quadratic programming. It integrates three constrains to guarantee robust alignment, including appearance matching cost term exploiting principal angles, geometric structure consistency using affine invariant reconstruction weights, smoothness constraint preserving local neighborhood relationship. Extensive experimental evaluations are performed on three databases: Honda, MoBo and YouTube. Compared with competing methods, our approach can consistently achieve better results.

关键词： Manifolds Face Image matching Face recognition Image reconstruction Video sequences Computational modeling

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