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Dynamics of a congestion control model in a wireless access network

Nonlinear Analysis: Real World Applications 2013年第1期14卷 671-683页

作者： Dong, Tao Liao, Xiaofeng Huang, Tingwen State Key Lab. of Power Transmission Equipment and System Security College of Computer Science Chongqing University Chongqing 400044 China College of Software and Engineering Chongqing University of Posts and Telecommunications Chongqing 400065 China Texas AandM University at Qatar Doha P.O. Box 23874 Qatar

In this paper, a congestion control algorithm with heterogeneous delays in a wireless access network is considered. We regard the communication time delay as a bifurcating parameter to study the dynamical behaviors, i.e., local asymptotical stability, Hopf bifurcation and resonant codimension-two bifurcation. By analyzing the associated characteristic equation, the Hopf bifurcation occurs when the delay passes through a sequence of critical value. Furthermore, the direction and stability of the bifurcating periodic solutions are derived by applying the normal form theory and the center manifold theorem. In the meantime, the resonant codimension-two bifurcation is also found in this model. Some numerical examples are finally performed to verify the theoretical results. © 2012 Published by Elsevier Ltd.

关键词： Codimension-two bifurcation Congestion control Hopf bifurcation Stability Wireless access network

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Cross-media topic detection associated with hot search queries 13

Cross-media topic detection associated with hot search queri...

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5th International Conference on Internet Multimedia Computing and Service, ICIMCS 2013

作者： Xue, Zhe Jiang, Shuqiang Li, Guorong Huang, Qingming Zhang, Weigang University of Chinese Academy of Sciences Beijing 100049 China Key Lab. of Intell. Info. Process. Inst. of Comput. Tech. CAS Beijing 100049 China School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China

ISBN: (纸本)9781450322522

Although lots of work has been done since NIST proposed the problem of Topic Detection and Tracking (TDT), most of them focus on single media data. Topic detection for cross-media data hasn't been fully investigated. In this paper, we propose an effective method for cross-media topic detection. Unlike traditional topic detection methods that are mainly based on clustering, we consider using hot search queries as guidance to detect topics. Besides, we propose an improved co-clustering method which can be well suited for cross-media data clustering. First, we use queries to detect topics directly, and find the data associated with the topic. Second, we apply our co-clustering method to find the topics existing in the rest of data. Finally, the results obtained by the first two steps are threaded together as topics. Experiments show that our method can effectively detect topics for cross-media data. © 2013 ACM.

关键词： Cluster analysis

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Representation of image content with multi-scale segmentation

Representation of image content with multi-scale segmentatio...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jing Zhang Ya-Xin Zhao Da Li Zhi-Hua Chen Yu-Bo Yuan Department of Computer Science & Engineering East China University of Science & Technology Shanghai State Key Lab. for Novel Software TechnologyNanjing University P.R. China

ISBN: (纸本)9781479902590

Representation of image content is an important part of image annotation and retrieval, which has become a hot topic in computer vision recently. In order to represent image content more efficiently and accurately, grid based methods such as bag-of-words, were proposed and attracted more attention. However, how to segment images and which scale is the best one are still open problems. In this paper, we segment images into grids in several different scales and extract low-level features from every grid, then visual words are constructed by clustering. Through comparing and analyzing the experiment results based on Corel SK, we study the influence of multi-scale segmentation on representation of image content. Our research is helpful for choosing appropriate scales in different situations where image contents are represented, and meaningful to image classification and retrieval.

关键词： Image segmentation Abstracts

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Graph-Based image segmentation with bag-of-pixels

Graph-Based image segmentation with bag-of-pixels

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Zhi-Hua Chen Xiao-Long Xiao Yi Liu Jing Zhang Yu-Bo Yuan Department of Computer Science & Engineering East China University of Science & Technology Shanghai State Key Lab. for Novel Software Technology Nanjing University P.R. China

ISBN: (纸本)9781479902590

Image segmentation can help us with a better understanding of the image content, and thus plays an important role in many fields of image processing including image retrieval, object recognition and image compression. We propose a novel method based on an efficient Graph-Based segmentation after analyzing its irrationalities. The proposed method with bag-of-pixels is simple and effective. In the evaluation using a large public image database that contains a lot of natural images, our method out-performs the efficient graph-based segmentation method, yields better segmentation results and shortens the running time.

关键词： Image edge detection Image segmentation Abstracts Streaming media

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CLSIFT: An Optimization Study of the Scale Invariance Feature Transform on GPUs

CLSIFT: An Optimization Study of the Scale Invariance Featur...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Weiyan Wang Yunquan Zhang Long Guoping Shengen Yan Haipeng Jia School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China State Key Laboratory of Computing Science Institute of Software Chinese Academy of Sciences Lab. of Parallel Software and Computational Science Institute of Software Chinese Academy of Sciences

Scale Invariance Feature Transform (SIFT) is quite suitable for image matching because of its invariance to image scaling, rotation and slight changes in illumination or viewpoint. However, due to high computation complexity it's technically challenging to deploy SIFT in real time application situations. To address this problem, we propose CLSIFT, an OpenCL based highly speeded up and performance portable SIFT solution. Important optimization techniques employed in CLSIFT such as: (1) For less global memory traffic, independent logical functions are merged into the same kernel to reuse data. (2) loop buffers are introduced in for data and intermediate results reusing. (3)Task queue used to schedule threads in the same branch to remove branch divergences. (4) Data partition is based on the statics patterns for workload balance among workgroups. (5) Overlap of CPU time and better parallel strategies are used too. With all mentioned efforts, CLSIFT processes lena. jpg at 74.2 FPS and 43.4FPS respectively on NVidia and AMD GPUS, much higher than CPU's nearly 10 FPS and the known fastest SIFTGPU's 39.8 FPS and 13FPS. Moreover in a quantitative comparison approach we analyze those successful strategies beating SIFTGPU, a famous existing GPU implementation. Additionally, we observe and conclude that NVidia GPU achieves better occupancy and performance due to some factors. Finally, we summarize some techniques and empirical guiding principles that may be shared by other applications on GPU.

关键词： Graphics processing units inst.uction sets Kernel Accuracy Histograms Optimization Memory management

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Semi-supervised learning with local and global consistency by geodesic distance and sparse representation 1

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3rd Sino-Foreign-Interchange Workshop on Intelligent science and Intelligent Data Engineering, IScIDE 2012

作者： Gui, Jie Zhao, Zhongqiu Hu, Rongxiang Jia, Wei Intelligent Computing Lab. Hefei Institute of Intelligent Machines Chinese Academy of Sciences Hefei Anhui 230031 China State Key Laboratory for Novel Software Technology Nanjing University China College of Computer Science and Information Engineering Hefei University of Technology China Institue of Energy Safety Chinese Academy of Sciences Hefei Anhui 230031 China

ISBN: (数字)9783642366697

ISBN: (纸本)9783642366680

In many practical data mining applications, such as web categorization, key gene selection, etc., generally, unlab.led training examples are readily availab.e, but lab.led ones are fairly expensive to obtain. Therefore, in recent years, semi-supervised learning algorithms such as graph-based methods have attracted much attention. However, most of these traditional methods adopted a Gaussian function to calculate the edge weights of the graph. In this paper, a novel weight for semi-supervised graph-based methods is proposed. The new method adds the lab.l information from problem into the target function, and adopts the geodesic distance rather than Euclidean distance as the measure of the difference between two data points when conducting the calculation. In addition, we also add class prior knowledge from problem into semi-supervised learning algorithm. Here we address the problem of learning with local and global consistency (LGC). It was found that the effect of class prior knowledge was probably different between under high lab.l rate and low lab.l rate. Furthermore, we integrate sparse representation (SR) in LGC algorithm. Experiments on a UCI data set show that our proposed method outperforms the original algorithms. © Springer-Verlag 2013.

关键词： Learning algorithms

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Support vector machine with customized kernel

Support vector machine with customized kernel

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10th International Symposium on Neural Networks, ISNN 2013

作者： Chen, Guangyi Bui, Tien Dai Krzyzak, Adam Liu, Weihua Department of Computer Science and Software Engineering Concordia University 1455 de Maisonneuve West Montreal QC H3G 1M8 Canada State Key Lab. of Virtual Reality Technology and Systems Beihang University No 37 Xueyuan Rd. Haidian District Beijing ZipCode 100191 China

ISBN: (纸本)9783642390647

In the past two decades, Support Vector Machine (SVM) has become one of the most famous classification techniques. The optimal parameters in an SVM kernel are normally obtained by cross validation, which is a time-consuming process. In this paper, we propose to learn the parameters in an SVM kernel while solving the dual optimization problem. The new optimization problem can be solved iteratively as follows: (a) Fix the parameters in an SVM kernel;solve the variables α i in the dual optimization problem. (b) Fix the variables α i;solve the parameters in an SVM kernel by using the Newton-Raphson method. It can be shown that (a) can be optimized by using standard methods in training the SVM, while (b) can be solved iteratively by using the Newton-Raphson method. Experimental results conducted in this paper show that our proposed technique is feasible in practical pattern recognition applications. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Support vector machines

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Invariant object recognition using radon and fourier transforms

Invariant object recognition using radon and fourier transfo...

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10th International Symposium on Neural Networks, ISNN 2013

作者： Chen, Guangyi Bui, Tien Dai Krzyzak, Adam Zhao, Yongjia Department of Computer Science and Software Engineering Concordia University 1455 de Maisonneuve West Montreal QC H3G 1M8 Canada State Key Lab. of Virtual Reality Technology and Systems Beihang University No 37 Xueyuan Rd. Haidian District Beijing ZipCode 100191 China

ISBN: (纸本)9783642390647

In this paper, an invariant algorithm for object recognition is proposed by using the Radon and Fourier transforms. It has been shown that this algorithm is invariant to the translation and rotation of pattern images. The scaling invariance can be achieved by the standard normalization techniques. Our algorithm works even when the center of the pattern object is not aligned well. This advantage is because the Fourier spectra are invariant to spatial shift in the radial direction whereas existing methods assume the centroids are aligned exactly. Experimental results show that the proposed method is better than the Zernike's moments, the dual-tree complex wavelet (DTCWT) moments, and the auto-correlation wavelet moments for one aircraft database and one shape database. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Object recognition

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Large scale microscopic traffic simulation of 3D digital cities

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Chang'an Daxue Xuebao (Ziran Kexue Ban)/Journal of Chang'an University (Natural science Edition) 2013年第3期33卷 62-68页

作者： Liu, You-Quan Zhao, Xiang-Mo Li, Guang-Xi Wu, En-Hua School of Information Engineering Chang'an University Xi'an 710064 Shaanxi China State Key Laboratory of Computer Science Institute of Software of CAS Chinese Academy of Sciences Beijing 100190 China Faculty of Science and Technology University of Macau Macao 000853 China The Eleventh Inst. of the Sixth Res. Academy of China Aerospace Science and Technology Corporation Xi'an 710100 Shaanxi China

In order to simulate the microscopic traffic situation of large cities, based on current fast development of graphics hardware, the road structure was separated into road segments and intersections, which were connected together with signal lights;an improved constraint based follow the leader method was given to update vehicles position with different speed limitations of different lanes considered. Accordingly a heterogeneous many-core based three dimensional microscopic traffic simulation framework was implemented with C++, which was tested with different scenes. The results indicate that such design can make the system more flexible and closer to the reality with potential collision avoided, and can also present a more realistic detailed appearance;moreover such kind of heterogeneous architecture can improve the microscopic traffic simulation efficiency greatly, suitable for large scale 3D city scene. Both the cost of three dimensional rendering and the cost from simulation become higher with the increasing of vehicle number, however the rendering procedure is more likely to be the bottleneck of the whole system. The test also verifies the scalab.lity of the system.

关键词： Three dimensional computer graphics

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Sparse signal analysis using Ramanujan sums

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9th International Conference on Intelligent Computing, ICIC 2013

作者： Chen, Guangyi Krishnan, Sridhar Liu, Weihua Xie, Wenfang Department of Computer Science and Software Engineering Concordia University Montreal QC H3G 1M8 Canada Department of Computer and Electrical Engineering Ryerson University Toronto ON Canada State Key Lab. of Virtual Reality Technology and Systems Beihang University No 37 Xueyuan Rd. Haidian District 100191 Beijing China Department of Mechanical and Industrial Engineering Concordia University Montreal QC H3G 1M8 Canada

ISBN: (纸本)9783642394812

In this paper, we perform sparse signal analysis by using the Ramanujan Sums (RS). The RS are orthogonal in nature and therefore offer excellent energy conservation. Our analysis shows that the RS can compress the energy of a periodic impulse chain signal into fewer number of RS coefficients than the Fourier transform (FT). In addition, the RS are faster than the FT in computation time because we can calculate the RS basis functions only once and save them to a file. We can retrieve these RS basis functions for our calculation inst.ad of computing them online. To process a signal of 128 samples, we spend 1.0 millisecond for the RS and 5.82 milliseconds for the FT by using our unoptimized Matlab.code. © 2013 Springer-Verlag.

关键词： Signal analysis

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