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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Lei Jin Zhaokang Wang Rong Gu Chunfeng Yuan Yihua Huang Department of Computer Science and Technology National Key Laboratory for Novel Software Technology Nanjing China

ISBN: (纸本)9781479941155

As a new area of machine learning research, the deep learning algorithm has attracted a lot of attention from the research community. It may bring human beings to a higher cognitive level of data. Its unsupervised pre-training step allows us to find high-dimensional representations or abstract features which work much better than the principal component analysis (PCA) method. However, it will face problems when being applied to deal with large scale data due to its intensive computation from many levels of training process against large scale data. The sequential deep learning algorithms usually can not finish the computation in an acceptable time. In this paper, we propose a many-core algorithm which is based on a parallel method and is used in the Intel Xeon Phi many-core systems to speed up the unsupervised training process of Sparse Autoencoder and Restricted Boltzmann Machine (RBM). Using the sequential training algorithm as a baseline to compare, we adopted several optimization methods to parallelize the algorithm. The experimental results show that our fully-optimized algorithm gains more than 300-fold speedup on parallelized Sparse Autoencoder compared with the original sequential algorithm on the Intel Xeon Phi coprocessor. Also, we ran the fully-optimized code on both the Intel Xeon Phi coprocessor and an expensive Intel Xeon CPU. Our method on the Intel Xeon Phi coprocessor is 7 to 10 times faster than the Intel Xeon CPU for this application. In addition to this, we compared our fully-optimized code on the Intel Xeon Phi with a Matlab code running on single Intel Xeon CPU. Our method on the Intel Xeon Phi runs 16 times faster than the Matlab implementation. The result also suggests that the Intel Xeon Phi can offer an efficient but more general-purposed way to parallelize the deep learning algorithm compared to GPU. It also achieves faster speed with better parallelism than the Intel Xeon CPU.

关键词： Training Neural networks Coprocessors Unsupervised learning Algorithm design and analysis Vectors Feature extraction

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OPTICAL FLOW BASED DYNAMIC CURVED VIDEO TEXT DETECTION

OPTICAL FLOW BASED DYNAMIC CURVED VIDEO TEXT DETECTION

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IEEE International Conference on Image Processing

作者： Palaiahnakote Shivakuamra Mohamed Lubani KokSheik Wong Tong Lu Faculty of Computer Science and Information Technology University of Malaya National Key Lab for Novel Software Technology Nanjing University

ISBN: (纸本)9781479957521

Text detection in video is a challenging problem as it is useful in several real time applications in the field of video indexing and retrieval. Unlike existing methods that generally focus on horizontal caption or graphics text, the proposed method focuses on detecting dynamic curved text in video. The method explores the characteristics of the optical flow of text, namely, constant velocity, uniform magnitude distribution and unique angle distribution, to identify text candidates with the help of k-means clustering algorithm. We propose an iterative procedure which finds the standard deviation of text candidates between the first and its successive frames, and it terminates when there is a sudden decrease in the standard deviation values. The proposed method eliminates false text candidates based on the characteristics of optical flow at component level while retaining the potential text candidates. Then, direction guided boundary growing is proposed to traverse curved text lines in video. Furthermore, the characteristics of optical flow of text are utilized at block level to eliminate false positives. Experiments are conducted with various videos, including video with static text, static and dynamic text, and dynamic text only, to evaluate the proposed method. The results are benchmarked with the existing methods to verify the superiority of our method over the existing methods in terms of recall, precision, F-measure and average processing time.

关键词： Optical flow Text candidates Direction guided boundary growing Curved dynamic text detection

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Kinect-based data-driven 3D modeling

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Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of computer-Aided Design and computer Graphics 2014年第11期26卷 1957-1965页

作者： Gong, Yusong Zhang, Yan Wen, Yan Sun, Zhengxing State Key Laboratory for Novel Software Technology Nanjing University Nanjing210093 China Department of Computer Science and Technology Nanjing University Nanjing210093 China

This paper presents a fast modeling method based on the highly noisy and incomplete scanned data from Kinect in a single view. We take full advantage of the abundant models of the same semantic class on the Internet to build a heuristic model based on the 3D point clouds and the corresponding RGB images. Our method includes three major phases: Firstly, we analyze the structure of the 3D point clouds and the RGB images based on the semantic segmentation of the candidate model to label the components of the scanned target;secondly, we search for candidate parts for the labeled parts in the target to get matched component information;lastly, we assemble the candidate parts to create the final 3D model. We demonstrate the efficiency and speed of our method in building models based on incomplete point clouds data from Kinect. ©, 2014, Institute of Computing technology. All right reserved.

关键词： Semantics

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Design of the web log analysis system based on Hadoop

Design of the web log analysis system based on Hadoop

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2014 International Conference on Materials science and Computational Engineering, ICMSCE 2014

作者： Wei, Yong Qing Zhou, Guang Gang Xu, Di Chen, Yu Basic Education Department Shandong Police College China Department of Information Science and Engineering Shandong Normal University China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology China

ISBN: (纸本)9783038350996

As a result of rapid development, the Internet has become an indispensable tool in people's daily life, and web logs have been growing rapidly as well. How to deal with massive logs timely and extract information people need from the logs has become a problem;handling web log by single computer can not meet people's needs any more. Combining cloud computing and Hadoop technology, this paper established a new processing system for the collection of logs and remote parallelization analysis, which not only solved the issues of traditional systems that data handing and collection could not proceed simultaneously, but reduced the performance bottleneck of computing power and storage capacity, thereby saving much time and improving efficiency significantly. © (2014) Trans Tech Publications, Switzerland.

关键词： Computing power

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Cost Optimal Planning with LP-Based Multi-valued Landmark Heuristic 14

Cost Optimal Planning with LP-Based Multi-valued Landmark He...

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International Conference on Autonomous Agents and Multiagent Systems

作者： Lei Zhang Chong-Jun Wang Jun-Yuan Xie State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University

ISBN: (纸本)9781634391313

Landmark based heuristics are among the most accurate current known admissible heuristics for cost optimal planning. Disjunctive action landmarks can be considered as at-least-one constraints on the actions they contains. In many planning domains, there are many critical propositions which have to be established for a number of times. Previous landmarks fail to express this kind of general cardinality constraints. In this paper, we propose to generalize landmarks to multi-valued landmarks to model general cardinality constraints in cost optimal planning. We show existence of complete multi-valued landmark sets by explicitly constructing complete multi-valued action landmark sets for general planning tasks. However, it's computationally intractable to extract and exploit exact lower bounds of general multi-valued action landmarks. We devise a linear programming based multi-valued landmark heuristic h~(lpml) which extracts and exploits multi-valued landmarks using a linear programming solver. The heuristic h~(lpml) is guaranteed to be admissible and can be computed in polynomial time. Experimental evaluation on benchmark domains shows h~(lpml) beats state-of-the-art admissible heuristic in terms of heuristic accuracy and achieves better overall coverage performance at the cost of using more CPU time.

关键词： Algorithms Experimentation Heuristic search planning Landmark heuristics Cost optimal planning

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Virtual DOM coverage for effective testing of dynamic web applications 2014

Virtual DOM coverage for effective testing of dynamic web ap...

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23rd International Symposium on software Testing and Analysis, ISSTA 2014

作者： Zou, Yunxiao Chen, Zhenyu Zheng, Yunhui Zhang, Xiangyu Gao, Zebao State Key Laboratory for Novel Software Technology Nanjing University Nanjing210093 China Department of Computer Science Purdue University West LafayetteIN47907 United States Department of Computer Science University of Maryland College ParkMD20742 United States

ISBN: (纸本)9781450326452

Test adequacy criteria are fundamental in software testing. Among them, code coverage criterion is widely used due to its simplicity and effectiveness. However, in dynamic web application testing, merely covering server-side script code is inadequate because it neglects client-side execution, which plays an important role in triggering client-server interactions to reach important execution states. Similarly, a criterion aiming at covering the UI elements on client-side pages ignores the server-side execution, leading to insufficiency. In this paper, we propose Virtual DOM (V-DOM) Coverage, a novel criterion, for effective web application testing. With static analysis, we first aggregate all the DOM objects that may be produced by a piece of server script to construct a V-DOM tree. The tree models execution on both the client- And server-sides such that V-DOM coverage is more effective than existing coverage criteria in web application testing. We conduct an empirical study on five real world dynamic web applications. We find that V-DOM tree can model much more DOM objects than a web crawling based technique. Test selection based on V-DOM tree criterion substantially outperforms the existing code coverage and UI element coverage, by detecting more faults. Copyright 2014 ACM.

关键词： software testing

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Deceptive Problems of Particle Swarm Optimization Algorithm and Improvement of Their Performance

Deceptive Problems of Particle Swarm Optimization Algorithm ...

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2012 2nd International Conference on Advanced Materials and Information technology Processing(AMITP 2012)

作者： Shu Wang Ling Chen Department of Computer Science Yangzhou University State Key Lab of Novel Software Technology Nanjing University

This paper introduces two instances of deceptive problems of particle swarm optimization(PSO).We theoretically prove that PSO can not converge to the global optimal solution of those two problems under certain *** addition,we empirically verified the correctness of our theoretical *** order to solve the two deceptive problems,we propose an algorithm ISA-PSO(inverse search area-PSO),which can change the particles' search direction and expand their search area at the appropriate *** experimental results show the effectiveness of our algorithm ISA-PSO.

关键词： Particle swarm optimization algorithm,Deceptive problems,Convergence

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Rotation-based learning: A novel extension of opposition-based learning

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8862卷 511-522页

作者： Liu, Huichao Wu, Zhijian Li, Huanzhe Wang, Hui Rahnamayan, Shahryar Deng, Changshou Computer School of Wuhan University Wuhan430072 China State Key Lab. Of Software Engineering Wuhan University Wuhan China College of Information Engineering Huanghuai University Zhumadian China School of Inform. Engin Nanchang Institute of Technology Nanchang China Department of Electrical Computer and Software Engineering University of Ontario Institute of Technology Oshawa Canada School of Information Science and Technology Jiujiang University Jiujiang Canada

Opposition-based learning (OBL) scheme is an effective mechanism to enhance soft computing techniques, but it also has some limitations. To extend the OBL scheme, this paper proposes a novel rotation-based learning (RBL) mechanism, in which a rotation number is achieved by applying a specified rotation angle to the original number along a specific circle in two-dimensional space. By assigning different angles, RBL can search any point in the search space. Therefore, RBL could be more flexible than OBL to find the promising candidate solutions in the complex search spaces. In order to verify its effectiveness, the RBL mechanism is embedded into differential evolution (DE) and the rotation-based differential evolution (RDE) algorithm is introduced. Experimental studies are conducted on a set of widely used benchmark functions. Simulation results demonstrate the effectiveness of RBL mechanism, and the proposed RDE algorithm performs significantly better than, or at least comparable to, several state-of-the-art DE variants. © Springer International Publishing Switzerland 2014.

关键词： Evolutionary algorithms

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MicroBlog orientation analysis based on sentiment symbol

MicroBlog orientation analysis based on sentiment symbol

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2014 International Conference on Manufacturing technology and Electronics Applications, ICMTEA 2014

作者： Liu, Pei Yu Zhang, Yan Hui Wei, Jing Xun Hou, Xiu Yan School of Information Engineering Shandong Yingcai University Jinan China Department of Information Science and Engineering Shandong Normal University China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology China

ISBN: (纸本)9783038353287

As a new social networking media, Micro-blog is recognized by more and more people gradually, the orientation analysis of Micro-blog short text messages has become a hotspot in the field of data mining. At present, the research of Micro-blog orientation analysis mainly concentrate in the text, without considering the impact of other emotional factors. By analyzing and studying Sina Micro-blog, this paper added new words and emoticons in the basis of traditional emotional dictionary to construct special Micro-blog dictionary. Meanwhile, it analyzed rhetoric and sentence to improve the effect of orientation analysis. The experimental results showed that the method in Micro-blog orientation analysis obtained better performance. © (2014) Trans Tech Publications, Switzerland.

关键词： Data mining

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Real-time collision detection with two-level spatial hashing on GPU 22

Real-time collision detection with two-level spatial hashing...

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22nd Pacific Conference on computer Graphics and Applications, PG 2014

作者： Hong, Yang Wu, Wen Chen, Hui Department of Computer and Information Science Faculty of Science and Technology University of Macau China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Beijing Key Lab of Human-Computer Interaction Institute of Software Chinese Academy of Science Beijing China

ISBN: (纸本)9783905674736

In this paper, a two-level parallel spatial hashing method is presented for real-time collision detection of deformable objects based on modern GPU architecture. The second-level of spatial hashing is used to improve the culling efficiency. Moreover, a novel encoding method on GPU is proposed to compensate the inflexibility of the GPU memory system. It can efficiently determine the colliding pairs of primitives between deformable objects. The experimental results show that our method can perform high culling efficiency with low memory cost. © The Eurographics Association 2014.

关键词： Graphics processing unit

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