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IEEE Visual Communications and Image Processing (VCIP)

作者： Yongxin Ge Chen Min Martin Jagersand Dan Yang School of Software Engineering Chongqing University Chongqing P. R. China Ministry of Education Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing China Department of Computing Science University of Alberta Edmonton Canada

A novel active appearance model (AAM) search algorithm based on partial least squares (PLS) regression is proposed. PLS models the relationship between independent (texture residuals) and dependent (error in the model parameters) variables in the training phase by extracting from independent and dependent variables a set of orthogonal factors called latent variables respectively which have the maximum covariance. During search, the parameter updates with the best predictive power are extracted from the texture residuals. On the other hand, PLS is well suited for the low observation-to-variable ratio context, where the sample covariance matrix is likely to be singular, which is very common in AAM. Experiments show that the proposed method has better performance than the original AAM and comparable performance to AAM search based on Canonical correlation analysis (CCA-AAM) in terms of convergence speed, whilst affording superior computational efficiency.

关键词： Active appearance model Shape Databases Training Face Computational modeling Convergence

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Labeling algorithm using fingerprint similarity and query distance based on click-through data for optimizing search

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Journal of Computational Information Systems 2014年第21期10卷 9275-9282页

作者： Feng, Yong Liu, Jing Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing University Chongqing China College of Computer Science Chongqing University Chongqing China

Historical click-through data is very effective to improve performance of search engine. In this paper, labeling algorithm (LA) using fingerprint similarity and query distance based on click-through data is proposed. This strategy obtains relevant pages of query by two ways. One uses labels between query and page produced in bipartite graph. Another one treats relevant pages of similar queries as its own. Finally we calculate relevancy between queries and pages using fingerprint similarity and query distance. Based on AOL query logs, we conduct experiments on LA. Results show LA can greatly improve search with low computational complexity. Compared with other query log mining algorithms, LA achieves higher precision and lower hit location.

关键词： Search engines

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Wireshark window authentication based packet captureing scheme to pervent DDoS related security issues in cloud network nodes

Wireshark window authentication based packet captureing sche...

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IEEE International Conference on Software Engineering and service Sciences (ICSESS)

作者： Waqar Ali Jun Sang Hamad Naeem Rashid Naeem Ali Raza School of Software Engineering Chongqing University Chongqing China Ministry of Education Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing China Department of computer science International Islamic University Kuala lumpur Malaysia

DoS (Denial of service) attack forces a cloud network node to handle few unauthorized access that employ unwanted computing cycle. As a result, the cloud node response is slow as usual and resource on cloud network becomes unavailable. Some Dos attacks are Ping of Death, Teardrop, Snork, Locking authentication, SYN flooding, Operating System Attacks etc. The most vulnerable incident happen when the adversary is committed DDoS (Distributed Denial of service) attack with comprised cloud network. In this paper, the prevention techniques for DDoS (Distributed Denial of service) attack in cloud nodes were discussed, a dynamic window scheme in cloud nodes to determine a message verification to resolve unnecessary packet processing was proposed.

关键词： Computer crime service computing Computer science Software engineering Software Computers

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PFIME: Parallel automatic deep web data extraction based on hadoop

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Journal of Computational Information Systems 2014年第9期10卷 3863-3870页

作者： Feng, Yong Jia, Dongfeng Wang, Huijuan Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing University Chongqing 400030 China College of Computer Science Chongqing University Chongqing 400030 China

Increasingly, many data sources appear as online databases, which are hidden behind query forms, forming the Deep Web. Automatic Deep Web data extraction is a key step of Deep Web query result processing. Extracting the query results correctly is the precondition and guarantee of data integration. The paper [1] proposes a novel and unsupervised system, Filtering, Iterating, Matching, and Extracting (FIME), to automatically extract data from the Deep Web query result pages. Unfortunately, when the dataset size is huge, computational cost can be prohibitively expensive. In this work, we propose Parallel Automatic Deep Web Data Extraction algorithm (we call our parallel algorithm PFIME) on Hadoop. PFIME computes in a way that each machine executes an independent group of Extraction tasks. Through empirical study on a large dataset of Deep Web pages, we demonstrate that PFIME can achieve obvious linear speedup. Besides scalability, the empirical study demonstrates that PFIME is promising for supporting query recommendation for search engines. © 2014 Binary Information Press.

关键词： Search engines

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A Tumor Detection Method Based On WCE Image Textures

A Tumor Detection Method Based On WCE Image Textures

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2015 International Conference on Software, Multimedia and Communication Engineering(SMCE 2015)

作者： Shang-bo ZHOU Han YANG Cheng-liang WANG Jian-ying BAI Chao-qiang FAN Jie XU Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing University College of Computer Science Chongqing University Department of Gastroenterology Xinqiao HospitalChongqing Chongqing Jinshan Science & Technology Co Ltd.

Wireless capsule endoscopy(WCE) has been gradually applied in hospitals due to its great advantage. This paper addresses the problem of automatic detection of tumor for WCE images. Firstly, the Level Set Method is utilized to searching suspected tumors in WCE images. Fractional Fourier Transform(FRFT) is applied on the region of the suspected tumors. Then suspected tumor textures of frequency domain are analyzed with the Normalized Gray Level Co-occurrence Matrix(NGLCM) model. After the texture character is abstracted, we use it to determine whether a tumor appears in the image or not. The proposed method does not rely on any learning-based classifier, and it can save plenty of time in train samples. Extensive experiments validate that the proposed method achieves coverage of 95.6% and accuracy of 85.0% and is a promising tumor detection.

关键词： Wireless Capsule Endoscopy(WCE) Tumor Level Set Method(LSM) Texture feature

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Neuroadaptive Backstepping Tracking Control of Robotic Manipulators Considering Actuator Dynamics

Neuroadaptive Backstepping Tracking Control of Robotic Manip...

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第27届中国控制与决策会议

作者： Zhi Yang Wanting Lu Zan Yao Beibei Zhang Key Laboratory of Dependable Service in Cyber Physical Society (Chongqing University) Ministry of EducationSchool of AutomationChongqing University School of Information and Electronics Engineering Beijing Jiaotong University

This paper investigated two novel robust adaptive NN-based backstepping algorithms for the tracking problem of robotic rigid-link manipulators with uncertain kinematics,dynamics and actuator *** controllers are both designed based on the backstepping *** and external disturbances in the manipulator dynamics are compensated by radial basis function in every step of *** first control algorithm could guarantee the tracking error converges to a small neighborhood of zero;the second improved control algorithm demanding link accelerations information could make sure the tracking error goes to zero quickly and *** feasibility and effectiveness of the proposed methods are verified by simulation studies.

关键词： Robotic Manipulator,Actuator,RBF NN,Robust Adaptive Backstepping Control

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Predicting elections from social networks based on sub-event detection and sentiment analysis

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 8787卷

作者： Unankard, Sayan Li, Xue Sharaf, Mohamed Zhong, Jiang Li, Xueming School of Information Technology and Electrical Engineering The University of Queensland BrisbaneQLD4072 Australia Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing400044 China

Social networks are widely used by all kinds of people to express their opinions. Predicting election outcomes is now becoming a compelling research issue. People express themselves spontaneously with respect to the social events in their social networks. Real time prediction on ongoing election events can provide feedback and trend analysis for politicians and news analysts to make informed decisions. This paper proposes an approach to predicting election results by incorporating sub-event detection and sentiment analysis in social networks to analyse as well as visualise political preferences revealed by those social network users. Extensive experiments are conducted to evaluate the performance of our approach based on a real-world Twitter dataset. Our experiments show that the proposed approach can effectively predict the election results over the given baselines. © Springer International Publishing Switzerland 2014.

关键词： Forecasting

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Scan-Based Attack on Stream Ciphers: A Case Study on eSTREAM Finalists

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Journal of Computer Science & Technology 2014年第4期29卷 646-655页

作者：邹敏辉马坤吴剀劼沙行勉 College of Computer Science Chongqing University Department of Electrical and Computer Engineering University of Illinois at Chicago Chicago IL 60607 U.S.A. IEEE Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing UniversityMinistry of Education

Scan-based design for test （DFT） is a powerful and the most popular testing technique. However, while scan-based DFT improves test efficiency, it also leaves a side channel to the privacy information stored in the chip. This paper investigates the side channel and proposes a simple but powerful scan-based attack that can reveal the key and/or state stored in the chips that implement the state-of-the-art stream ciphers with less than 85 scan-out vectors.

关键词： scan-based attack stream cipher linear and non-linear feedback shift register scan-based design for test

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Cross-Speed Gait Recognition Using Speed-Invariant Gait Templates and Globality-Locality Preserving Projections

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IEEE Transactions on Information Forensics and Security 2015年第10期10卷 2071-2083页

作者： Huang, S. Elgammal, A. Lu, J. Yang, D. School of Software Engineering Chongqing University Chongqing401331 China Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing400044 China Department of Computer Science Rutgers University PiscatawayNJ08854 United States Advanced Digital Sciences Center Singapore138632 Singapore

We present a novel manifold-based approach for cross-speed gait recognition. In our approach, the walking action is considered as residing on a manifold, in the feature space, that is homomorphic to a unit circle. We employ thin plate spline (TPS) kernel-based radial basis function (RBF) interpolation to fit such manifold. TPS kernel-based RBF interpolation separates the learned coefficients into an affine component and a nonaffine component, which, respectively, encodes the dynamic and static characteristics of the gait manifold. We introduce the use of the nonaffine component as a cross-speed gait representation, and denote it speed invariant gait template (SIGT). We also propose an enhanced locality preserving projections (LPP) algorithm named globality LPP (GLPP) for reducing the dimension of SIGT. In GLPP, the graph Laplacians of intrasubject part and intersubjects part are separately constructed, and then to combine as a new graph Laplacian. Finally, a manifold learning-based classifier named normalized hypergraph classifier is employed for classification. Experimental results on two gait databases demonstrate the effectiveness of our proposed approach in comparison with the state-of-the-art gait recognition methods. © 2005-2012 IEEE.

关键词： Speed

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Automatic Deep web query results user satisfaction evaluation with click-through data analysis

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International Journal of Smart Home 2014年第5期8卷 25-32页

作者： Liu, Zhen Feng, Yong Wang, Huijuan College of Computer Science Chongqing University Chongqing China Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing University Chongqing China Chongqing Medicine Exchange Chongqing China

We browse through hundreds of Deep web pages everyday to find information of interest. We feel happy when Deep web browsing operations provide us with necessary information;otherwise, we feel bitter. Now, the measurement of this user satisfaction has become a hot research topic. In this paper, we propose a click-through-data-based and unsupervised user satisfaction evaluation system, CNEITE, to evaluate the user satisfaction of Deep Web query result pages. It applies query type classifying, navigational query evaluating, informational/transactional query evaluating to solve the challenging tasks. We evaluated our CNEITE system on the AOL data sets, experimental results show that CNEITE achieves higher classify precision than a widely used classify method , Dtree, and higher annotate answer accuracy than method proposed in [17]. © 2014 SERSC.

关键词： Websites

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