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2007 IEEE International Conference on Web Services, ICWS 2007

作者： Huipeng, Guo Jinpeng, Huai Huan, Li Ting, Deng Yang, Li Zongxia, Du State Key Lab. of Software Development Environment School of Computer Beihang University Beijing China

ISBN: (纸本)0769529240

With the fast development of Internet and rapid acceptance of Web Service technology, more and more service resources have emerged. Service composition which integrates the functionalities of different services is a promising technique for developing applications across multiple organizations. However, in a distributed, dynamic and autonomous environment, such as a service composition-based system, the availab.lity and reliability are big concerns in terms of nonfunctional properties. In this paper, we propose a novel service composition method, ANGEL, with the target of the improvement of system availab.lity. We adopt redundant mechanism in ANGEL and propose a model to improve the property of the service availab.lity. We model the multiple services selection problem based on redundant mechanism as a nonlinear mixed integer programming problem and therefore, we propose two heuristic algorithms to select multiple feasible services that have the same functions, but with better availab.lity. In order to maintain the availab.lity of composite services, we further introduce monitor and detection mechanisms. Through the comprehensive experiments, we find that our proposed techniques can indeed achieve better availab.lity as expected. © 2007 IEEE.

关键词： Availab.lity

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Accelerating locality preserving nonnegative matrix factorization 12

Accelerating locality preserving nonnegative matrix factoriz...

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21st ACM International Conference on Information and Knowledge Management, CIKM 2012

作者： Yao, Guanhong Deng, Cai State Key Lab. of CAD and CG College of Computer Science Zhejiang University Hangzhou China

ISBN: (纸本)9781450311564

Matrix factorization techniques have been frequently applied in information retrieval, computer vision and pattern recognition. Among them, Non-negative Matrix Factorization (NMF) has received considerable attention due to its psychological and physiological interpretation of naturally occurring data whose representation may be parts-based in the human brain. Locality Preserving Non-negative Matrix Factorization (LPNMF) is a recently proposed graph-based NMF extension which tries to preserves the intrinsic geometric structure of the data. Compared with the original NMF, LPNMF has more discriminating power on data representa- tion thanks to its geometrical interpretation and outstanding ability to discover the hidden topics. However, the computa- tional complexity of LPNMF is O(n3), where n is the number of samples. In this paper, we propose a novel approach called Accelerated LPNMF (A-LPNMF) to solve the com- putational issue of LPNMF. Specifically, A-LPNMF selects p (p j n) landmark points from the data and represents all the samples as the sparse linear combination of these landmarks. The non-negative factors which incorporates the geometric structure can then be efficiently computed. Experimental results on the real data sets demonstrate the effectiveness and efficiency of our proposed method. © 2012 ACM.

关键词： Non-negative matrix factorization

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Decreasing accelerated gradient descent method for nonnegative matrix factorization

Decreasing accelerated gradient descent method for nonnegati...

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2nd International Conference on Information Engineering and Applications, IEA 2012

作者： Liu, Furui State Key Lab. of CAD and CG College of Computer Science Zhejiang University Hangzhou China

ISBN: (纸本)9781447148555

In this paper, by bringing in a user defined nonnegative control matrix to form a new objective function, I modify the update rules correspondingly and propose a novel decreasing accelerated gradient descent method for nonnegative matrix factorization (DAGDM) which can make the matrix of the decomposition results achieve sparse. The control matrix also contains the weighting information, which puts different weight on different parts of the result matrix to be produced. This will provide a control interface of nonnegative matrix factorization to make a sparse and light basis matrix. Experimental results demonstrate the effectiveness of the proposed method. © 2013 Springer-Verlag.

关键词： Matrix factorization

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Collab.ratively modeling buildings from large-scale street-side and remote sensing images

Collaboratively modeling buildings from large-scale street-s...

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2nd International Conference on Multimedia Technology, ICMT 2011

作者： Hua, Wei Zhang, Wei State Key Lab. of CAD and CG College of Computer Science Zhejiang University Hangzhou China

ISBN: (纸本)9781612847740

This paper proposed an approach to rapidly generate 3D models for street-side buildings from street-side images, remote sensing images, and GPS information. Traditional modeling methods usually require a single user to fulfill all processes of 3D modeling, and lack efficient management on massive data. Thus, they are unsuitable for large-scale modeling. In order to overcome those drawbacks, we employ the pipeline idea. The modeling processes are divided into several steps, which are further assembled to form a pipeline elab.rately. We allocate computing resources into each step according to their requirements;on the other side, human resources are deployed into the pipeline to achieve team-work modeling. To demonstrate the effectiveness of ur approach, we developed a distributed prototype system for rapid large-scale urban 3D modeling. This system was tested to build an urban scene with more than 500, 000 street-side images. The results show great improvement on modeling efficiency compared with traditional methods, and it reveals a great prospect in applications. © 2011 IEEE.

关键词： Pipelines

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Level of detail and multi-resolution modeling for virtual prototyping

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International Journal of Image and Graphics 2001年第2期1卷 329-343页

作者： Pan, Zhigeng Zhang, Mingmin Zhou, K.U.N. Cheng, Chiyi Shi, Jiaoying State Key Lab of CAD and CG Zhejiang University Hangzhou310027 China Key Lab. of VR and Networked Multimedia Hangzhou Institute of Electronic Engineering Hangzhou China Department of Computer Zhejiang University Hangzhou310027 China

Reconciling scene realism with interactivity has emerged as one of the most important areas in making virtual reality feasible for large-scale CAD data sets consisting of several millions of primitives. Level of detail (LoD) and multi-resolution modeling techniques in virtual reality can be used to speed up the process of virtual design and virtual prototyping. In this paper, we present an automatic LoD generation and rendering algorithm, which is suitable for CAD models and propose a new multi-resolution representation scheme called MRM (multi-resolution model), which can support efficient extraction of fixed resolution and variable resolution for multiple objects in the same scene. MRM scheme supports unified selective simplifications and selective refinements over the mesh. Furthermore, LoD and multi-resolution models may be used to support real-time geometric transmission in collab.rative virtual design and prototyping. © 2001 World Scientific Publishing Company.

关键词： Virtual prototyping

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TCFOM: A robust traffic classification framework based on OC-SVM combined with MC-SVM

TCFOM: A robust traffic classification framework based on OC...

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2010 International Conference on Communications and Intelligence Information Security, ICCIIS 2010

作者： Lu, Gang Zhang, Hongli Sha, Xuefu Chen, Cheng Peng, Lizhi State Key Lab. of Computer Information Content Security Department of Computer Science Harbin Institute of Technology Harbin China

ISBN: (纸本)9780769542607

New application traffic occurring on Internet frequently challenges the traditional traffic classifiers based on machine learning. These classifiers always identify it inaccurately and assign it into one of their known classes forcibly, even though the extra class is lab.led as 'other' when training. In this case, the precision of identifying known classes is reduced. In this paper, a robust traffic classification framework based on OC-SVM combined with MC-SVM (TCFOM) is presented. We capture several kinds of application traffic, and carry out an experiment under supervised environment. Using the OC-SVM, the unknown traffic is classified into extra class lab.led as 'other'. The precision of identifying known traffic is improved. Using the unknown traffic identified, the new classifying model is set up. TCFOM can classify the unknown traffic and extend well. We compare TCFOM with three classifiers respectively based on SVM, RBF network, Naïve Bayes. Experimental results show that the robustness of TCFOM is best. © 2010 IEEE.

关键词： Learning systems

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Memory Access Complexity Analysis of SpMV in RAM (h) Model

Memory Access Complexity Analysis of SpMV in RAM (h) Model

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10th IEEE International Conference on High Performance Computing and Communications

作者： Yuan E Zhang Yun-quan Sun Xiangzheng Lab. of Parallel Computing ISCAS 100190 China Graduate University of Chinese Academy of Sciences 100190 China State Key Lab. of Computer Science CAS 100190 China

ISBN: (纸本)9780769533520

Sparse Matrix-Vector Multiplication is an important computational kernel in scientific applications, and CSR storage algorithm often performs poorly on modern computer systems. But the register-level blocking algorithm can optimize memory hierarchy access, reduce memory access time, and then improve the performance. RAM (h) is a computation model that has h-level memory hierarchies. It indicates that different implementation forms of the same algorithm can have different memory access complexity. In this paper, we try to analyze memory access compelxity of two implementation forms of SpMV(which are CSR storage algorithm and register-level blocking algorithm) and to predict the performance of SpMV through combining the memory access complexity analysis and the data movement/floating point operation ratio analysis. The performance data of two forms and Statistical results of miss number of L1, L2 and TLB on Pentium IV platform are listed. Model analytical results matched well with experimental results.

关键词： SpMV sparse matrix-vector multiplication RAM (h) model memory access complexity

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An experimental facial synthesis system using graph cut and gradient domain fusion

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1st International Conference on Technologies for E-Learning and Digital Entertainment (Edutainment 2006)

作者： Jiang, Xiaohong Dai, Fen Jiang, Hanqing College of Computer Science and Technology Zhejiang University China State Key Lab. of CAD and CG Zhejiang University China

ISBN: (纸本)3540334238

Based on the newly appeared image editing and image processing techniques, a novel interactive, computer-assisted system is proposed for facial synthesis. This paper presents the architecture of this facial synthesis system and gives a detailed description of the four key modules. The techniques used in these modules are also particularized. First, graph cut algorithm is used to automatically select region. Then gradient domain fusion is used to get better result. Finally, k-means method is used to improve efficiency. The experimental results show that our experimental facial synthesis system can produce visually good synthesized face images.

关键词： K-means clustering objective stroke background stroke automatic region selection energy minimization graph cut gradient domain fusion

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Context-based requirement modeling for self-adaptive service software

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Journal of Computational Information Systems 2012年第24期8卷 10131-10140页

作者： Liu, Wei Feng, Zaiwen School of Computer Science and Engineering Hubei Key Laboratory of Intelligence Robot Wuhan Institute of Technology Wuhan 430073 China State Key Lab. of Software Engineering Wuhan University Wuhan 430072 China

Service-oriented self-adaptation software (SoSAS) utilizes services as fundamental elements for developing applications that have the capability to autonomously modify their behavior at run-time in response to changes in their environment. While a few techniques have been developed to support the modeling and analysis of requirements for self-adaptive systems, limited attention has been paid to the description of service requirements and uncertainty in requirements of SoSAS. In this paper, we propose a context-based requirement representing and modeling framework as a fundamental of self-adaptation evolution. We introduce a context snapshot model to represent uncertainty in requirement with domain knowledge;goal-oriented context requirement to model user requirements and process-oriented context requirement to model service requirements;and finally, propose means-c-end analysis to relate user and service requirement with context condition. We illustrate and evaluate our approach through three scenarios of city intelligent traffic domain in the support tool ConUSER. © 2011 by Binary Information Press.

关键词： Uncertainty analysis

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A GPU-based high-throughput image retrieval algorithm 5

A GPU-based high-throughput image retrieval algorithm

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5th Workshop on General-Purpose Computation on Graphics Processing Units, GPGPU-5 - Held in Cooperation with ACM ASPLOS XVII

作者： Zhu, Feiwen Chen, Peng Yang, Donglei Zhang, Weihua Chen, Haibo Zang, Binyu State Key Lab. of ASIC and System Fudan University China Parallel Processing Institute Fudan University China Architecture Key Lab. Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9781450312332

With the development of Internet and cloud computing, multimedia data, such as images and videos, has become one of the most common data types being processed. As the scale of multimedia data being still increasing, it is vitally important to efficiently extract useful information from such a huge amount of multimedia data. However, due to the complexity of the core algorithms, multimedia retrieval applications are not only data intensive but also computationally intensive. Therefore, it has been a major challenge to accelerate the processing speed of such applications to satisfy the real-time requirement. As Graphic Processing Unit (GPU) has entered the general-propose computing domain (GPGPU), it has become one of the most popular accelerators for the applications with real-time requirements. In this paper, we parallelize a widely-used image retrieval algorithm called SURF on GPGPU, which is the core algorithm for many video and image retrieval applications. We first analyze the parallelism within SURF to guarantee that there are sufficient tasks being mapped to the large-scale computation resources in GPGPU. We then exploit some inherent GPGPU characteristics, such as 2D memory, to further boost the performance. Finally, we provide some optimization to the cooperation between CPU and GPGPU, which is generally ignored in previous designs. Experimental results show that our parallelization and optimization achieve a throughput of 340.5 frames/s on a NVIDIA GTX295 GPGPU, which is 15X faster than the maximal optimized CPU version. Compared to CUDA SURF, a state-of-the-art parallelization of SURF on GPGPU, our system achieves a speedup by a factor of 2.3X. © 2012 ACM.

关键词： Graphics processing unit

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