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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Vitor N. Coelho Frederico G. Guimarães Agnaldo J. R. Reis Igor M. Coelho Bruno N. Coelho Marcone J. F. Souza Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Departament of Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Department of Control Engineering and Automation Universidade Federal de Ouro Preto Ouro Preto MG Brazil Institute of Computing Universidade Federal Fluminense Niteri RJ Brazil Department of Computer Science Universidade Federal de Ouro Preto Ouro Preto MG Brazil

Improving the use of energy resources has been a great challenge in the last years. A new complex scenario involving a decentralized bidirectional communication between energy suppliers, distribution system and consumption is nowadays becoming reality. Sometimes cited as the largest and most complex machine ever built, Electric Grids (EG) are been transformed into Smart Grids (SG). Hence, the load forecasting problem has become more difficulty and more autonomous load predictors are needed in this new conjecture. In this paper a novel method, so-called MSES, bio-inspired by Evolution Strategies (ES) combined with Multi-Start (MS) procedure is described. This procedure is mainly based on a self-adaptive algorithm to calibrate the parameters of the fuzzy rules. MSES was implemented in C++ via OptFrame framework. Our main goal is to evaluate the performance of this algorithm in a grid environment. Real data from an electric utility have been used in order to test the proposed methodology. The obtained results are fully described and analyzed.

关键词： Forecasting Vectors Prediction algorithms Predictive models Training Standards Adaptation models

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Discriminative spatial codebook generation for image classification

Discriminative spatial codebook generation for image classif...

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2013 7th International Conference on Image and Graphics, ICIG 2013

作者： Zhang, Chunjie Xiong, Wei Liu, Jing Fang, Liang Zhang, Weigang Huang, Qingming School of Computer and Control Engineering University of Chinese Academy of Sciences 100049 Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences P.O. Box 2728 Beijing China School of Civil Engineering Suzhou University of Science and Technology Suzhou 215011 China School of Computer Science and Technology Harbin Institute of Technology at Weihai Weihai 264209 China

ISBN: (纸本)9780769550503

Codebook plays an important role in the bag-of-visual-words (BoW) model for image classification. However, the traditional codebook generation procedure ignores the spatial information. Although a lot of works have been done to consider the spatial information for codebook generation, most of them rely on fixed region selection or partition of images, hence are not able to cope with the variations of images. To solve this problem, in this paper, we propose a novel discriminative spatial coding algorithm which can automatically generate and select the most representative codebooks for image representation. This is achieved by first generate a number of spatial codebooks through over-complete image partition with overlap. Second, for each local feature to be encoded, the most discriminative codebook is selected by jointly minimizing the encoding error and the codebook's spatial distance. Experimental results on several public image datasets show the effectiveness of the proposed discriminative spatial coding method for efficient image classification. © 2013 IEEE.

关键词： Image classification

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Learning grasps for unknown objects in cluttered scenes

Learning grasps for unknown objects in cluttered scenes

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IEEE International Conference on Robotics and automation (ICRA)

作者： David Fischinger Markus Vincze Yun Jiang Automation an Control Institute Vienna University of Technology Vienna Austria Department of Computer Science Cornell University Ithaca NY USA

In this paper, we propose a method for grasping unknown objects from piles or cluttered scenes, given a point cloud from a single depth camera. We introduce a shape-based method - Symmetry Height Accumulated Features (SHAF) - that reduces the scene description complexity such that the use of machine learning techniques becomes feasible. We describe the basic Height Accumulated Features and the Symmetry Features and investigate their quality using an F-score metric. We discuss the gain from Symmetry Features for grasp classification and demonstrate the expressive power of Height Accumulated Features by comparing it to a simple height based learning method. In robotic experiments of grasping single objects, we test 10 novel objects in 150 trials and show significant improvement of 34% over a state-of-the-art method, achieving a success rate of 92%. An improvement of 29% over the competitive method was achieved for a task of clearing a table with 5 to 10 objects and overall 90 trials. Furthermore we show that our approach is easily adaptable for different manipulators by running our experiments on a second platform.

关键词： Grasping Manipulators Training Accuracy Support vector machines Grippers

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Supervised DNA barcode species classification:analysis, comparison and results

Supervised DNA barcode species classification:analysis, comp...

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Firth International Barcode of Life Conference(第五届国际生命条形码大会)

作者： Emanuel Weitschek Giulia Fiscon Giovanni Felici Department of Computer Controland Management EngineeringSapienza UniversityItaly Institute of Systems Analysis and Computer ScienceNational Research CouncilItaly Department of Computer Science and Automation University Roma TreItaly Institute of Systems Analysis and Computer Science National Research CouncilItaly Institute of Systems Analysis and Computer ScienceNational Research CouncilItaly

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Nonlinear analysis of dynamical complex networks 2014

Abstract and Applied Analysis

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Abstract and Applied Analysis 2014年第1期2014卷

作者： Wang, Zidong Shen, Bo Dong, Hongli Hu, Jun He, Xiao Ding, Derui Department of Computer Science Brunel University Uxbridge Middlesex UB8 3PH United Kingdom Communication Systems and Networks (CSN) Research Group Faculty of Engineering King Abdulaziz University Jeddah 21589 Saudi Arabia School of Information Science and Technology Donghua University Shanghai 200051 China College of Electrical and Information Engineering Northeast Petroleum University Daqing 163318 China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin 150001 China Department of Applied Mathematics Harbin University of Science and Technology Harbin 150080 China Department of Automation Tsinghua University Beijing 100084 China Department of Applied Mathematics Anhui Polytechnic University Wuhu 241000 China

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Cooperative Data Dissemination via Space-Time Network Coding in Vehicular Networks

Cooperative Data Dissemination via Space-Time Network Coding...

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IEEE Global Communications Conference

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

ISBN: (纸本)9781479913510

In this paper, we for the first time consider the space-time network coding (STNC) to propose a novel cooperative data dissemination strategy in the time-division multiple access (TDMA) manner for the vehicle network, to overcome the short-comings of the traditional network coding (NC) techniques with carrier sense multiple access/collision avoidance (CSMA/CA) protocol, i.e., high signal detection complexity and channel collision problem. An optimal relay selection strategy in the procedure of cooperative data dissemination is proposed to maximize the average system capacity for the data dissemination. In a addition, a suboptimal relay selection strategy is put forward to reduce the computation complexity and thus makes the developed data dissemination strategy more practical. Compared with the non-cooperative data dissemination, the proposed cooperative data dissemination via STNC has better performance in terms of the average system capacity, the average user equipment (UE) capacity, and the average data dissemination delay.

关键词： STNC first time average system capacity

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A New Pruning Method for Resolving Conflicts in Actionable Behavioral Rules

A New Pruning Method for Resolving Conflicts in Actionable B...

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IEEE International Conference on Intelligence and Security Informatics

作者： Peng Su Dan Zhu Daniel Zeng School of Mathematics and Computer Science Dali University College of Business Iowa State University State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781467362146

Among the most important and distinctive actionable knowledge are actionable behavioral rules that can directly and explicitly suggest specific actions to take to influence the behavior in the users' best interest. However, in mining such rules, it often occurs that different rules may suggest the same actions with different expected utilities, which we call conflicting rules. To resolve the conflicts, a previous pruning method was proposed. However, inconsistency of the measure for rule pruning may hinder its performance. To overcome this problem, we develop a new pruning method to achieve rule pruning in actionable rule discovery. We conduct several experiments to test our proposed approach and evaluate the sensitivity of the weight parameter. Empirical results based on a benchmark terrorism dataset indicate that our approach outperforms those from previous research.

关键词： Actionable behavioral rules Rule pruning Conflicting rules

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Undo the codebook bias by linear transformation for visual applications 13

Undo the codebook bias by linear transformation for visual a...

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21st ACM International Conference on Multimedia, MM 2013

作者： Zhang, Chunjie Zhang, Yifan Wang, Shuhui Pang, Junbiao Liang, Chao Huang, Qingming Tian, Qi School of Computer and Control Engineering University of Chinese Academy of Sciences 100049 Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China Key Lab of Intell. Info. Process Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China College of Computer Science and Technology Beijing University of Technology 100124 Beijing China School of Computer National Engineering Research Center for Multimedia Software Wuhan University 430072 Wuhan China Department of Computer Sciences University of Texas at San Antonio San Antonio TX 78249 United States

ISBN: (纸本)9781450324045

The bag of visual words model (BoW) and its variants have demonstrate their effectiveness for visual applications and have been widely used by researchers. The BoW model first extracts local features and generates the corresponding codebook, the elements of a codebook are viewed as visual words. The local features within each image are then encoded to get the final histogram representation. However, the codebook is dataset dependent and has to be generated for each image dataset. This costs a lot of computational time and weakens the generalization power of the BoW model. To solve these problems, in this paper, we propose to undo the dataset bias by codebook linear transformation. To represent every points within the local feature space using Euclidean distance, the number of bases should be no less than the space dimensions. Hence, each codebook can be viewed as a linear transformation of these bases. In this way, we can transform the pre-learned codebooks for a new dataset. However, not all of the visual words are equally important for the new dataset, it would be more effective if we can make some selection using sparsity constraints and choose the most discriminative visual words for transformation. We propose an alternative optimization algorithm to jointly search for the optimal linear transformation matrixes and the encoding parameters. Image classification experimental results on several image datasets show the effectiveness of the proposed method. Copyright © 2013 ACM.

关键词： Linear transformations

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Fast Multi-Operator Image Resizing and Evaluation

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Journal of computer science & Technology 2012年第1期27卷 121-134页

作者： Wei-Ming Dong Guan-Bo Bao Xiao-Peng Zhang Jean-Claude Paul Sino-French Laboratory for Computer Science Automation and Applied Mathematics/National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China National Institute for Research in Computer Science and Control Domaine de Voluceau Rocquencourt Le Chesnay 78153France

Current multi-operator image resizing methods succeed in generating impressive results by using image similarity measure to guide the resizing process. An optimal operation path is found in the resizing space. However, their slow resizing speed caused by inefficient computation strategy of the bidirectional patch matching becomes a drawback in practical use. In this paper, we present a novel method to address this problem. By combining seam carving with scaling and cropping, our method can realize content-aware image resizing very fast. We define cost functions combing image energy and dominant color descriptor for all the operators to evaluate the damage to both local image content and global visual effect. Therefore our algorithm can automatically find an optimal sequence of operations to resize the image by using dynamic programming or greedy algorithm. We also extend our algorithm to indirect image resizing which can protect the aspect ratio of the dominant object in an image.

关键词： image resizing multi-operator operator cost indirect resizing

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An empirical analysis of social interaction on tobacco-oriented social networks

An empirical analysis of social interaction on tobacco-orien...

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2013 International Conference for Smart Health, ICSH 2013

作者： Liang, Yunji Zheng, Xiaolong Zeng, Daniel Dajun Zhou, Xingshe Leischow, Scott School of Computer Science Northwestern Polytechnical University Xi'an China Department of Management Information System University of Arizona Tucson AZ United States State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan China Mayo Clinic in Arizona Phoenix AZ United States

ISBN: (纸本)9783642398438

Social media is widely utilized in the tobacco control campaigns. It is a great challenge to evaluate the efficiency of tobacco control policies on social network sites and find gaps among tobacco-oriented social networks. In this paper, we construct three tobacco-oriented social networks according to user interaction on Facebook tobacco-related fan pages. We further investigate the interaction patterns including temporal distribution and interaction patterns to reveal the differences of tobacco-oriented social networks. Our empirical analysis demonstrates that: 1) the user interaction on the pro-tobacco fan pages is more active. Fan pages for tobacco promotion are more successful in obtaining more user attention. 2) The gap between tobacco promotion and tobacco control is widening. These empirical results can provide us significant insights into understanding the evolutionary patterns of social interaction in tobacco-oriented social networks and further help the government departments of tobacco control to make reasonable decisions. © 2013 Springer-Verlag.

关键词： Tobacco

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