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3rd International Workshop on Structured Object-Oriented Formal Language and Method, SOFL+MSVL 2013

作者： Yan, Lu Li, Xiaohong Feng, Ruitao Feng, Zhiyong Hu, Jing Tianjin Key Laboratory of Cognitive Computer and Application School of Computer Science and Technology Tianjin University Tianjin China

ISBN: (纸本)9783319049144

Web applications are threatened seriously by SQL injection attacks. Even though a number of methods and tools have been put forward to detect or prevent SQL injections, there is a lack of effective method for detecting second-order SQL injection which stores user inputs into the back-end database. This paper proposes a detecting solution that combines both static and dynamic methods for second-order SQL injection. This solution first analyzes source code to find out the vulnerable data item pair which probably has second-order SQL injection vulnerability and then transforms it into an effective test sequence. After that, test sequence and malicious inputs are combined together for testing. Assessment of this solution in four applications and practical use show its effectiveness in the detection of second-order SQL injection. © 2014 Springer International Publishing Switzerland.

关键词： Static analysis

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The research of the recommendation algorithm in online learning

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous Engineering 2015年第4期10卷 71-80页

作者： Yu, Ruiguo Cai, Zhiyong Du, Xiuping He, Muwen Wang, Zan Yang, Binlan Chang, Peng School of Computer Science and Technology Tianjin University Tianjin China Tianjin Key Laboratory of Cognitive Computing and Application Tianjin China School of Education Tianjin University Tianjin China School of Computer and Software Tianjin University Tianjin China Information and Network Center Tianjin University Tianjin China

Recommendation algorithm is a kind of method in information filtering and has been widely applied on Internet. Collaborative filtering is widely used in the recommendation systems and has turned out to be successful. With the growth of the resources, it is difficult for users to find learning resources that suit for themselves. The recommendation algorithm is required to analyze the behavior of the users and then recommend object of learning. Online judge is a kind of the online learning. People can evaluate their programming ability through online judge. The performance of the different recommendation algorithms is analyzed in this paper and it is proposed that the item-based collaborative filtering recommendation algorithms should be applied into the online learning system. Based on the algorithm, we propose that by pre-processing the data and using user data that have solve large number of problems, we can get a better recommendation result. © 2015 SERSC.

关键词： Collaborative filtering

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Anomaly Detection Based on Regularized Vector Auto Regression in Thermal Power Plant

Anomaly Detection Based on Regularized Vector Auto Regressio...

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2015年第4届力学与控制工程国际学术会议

作者： Yi-Ming Wei Hao Yu Wen-Jun Wang Yue-Heng Sun Jian Wang Zhan-Jie Song School of Electronic Information Engineering Tianjin University Tianjin Key Laboratory of Cognitive Computing and Application School of Computer Science and Technology Tianjin University School of Science and Institute of TV and Image Information Tianjin University

Anomaly detection has gained widespread interest especially in the industrial conditions. Contextual anomalies means that sensors of industrial equipment are interrelated and a sensor data instance called anomalous should be in a specific context. In this paper we propose a scheme for temporal sensor data monitor and anomaly detection in thermal power plant. The scheme is based on Regularized Vector Auto Regression, which is used to capture the linear interdependencies among multiple time series. The advantage is that the RVAR model does not require too much knowledge about the forces influencing a variable. The only prior knowledge needed is a list of variables which can be hypothesized to affect each other. Experimental results show that the proposed scheme is efficient compared with other methods such as SVM, BPNN and PCA.

关键词： Anomaly Detection Based on Regularized Vector Auto Regression in Thermal Power Plant Vector

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Image decomposing for inpainting using compressed sensing in DCT domain

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Frontiers of computer Science 2014年第6期8卷 905-915页

作者： Qiang LI Yahong HAN Jianwu DANG School of Computer Science and Technology Tianjin University Tianjin 300072 China Tianjin Key Laboratory of Cognitive Computing and Application Tianjin University Tianjin 300072 China School of Information Science Japan Advanced Institute of Science and Technology Ishikawa 923-1192 Japan

Inpainting images with occlusion or corruption is a challenging task. Most existing algorithms are pixel based, which construct a statistical model from image features. However, in these algorithms, the frequency component is not sufficiently addressed. In this paper, we propose a novel algorithm that utilizes compressed sensing （CS） in frequency domain to reconstruct corrupted images. In order to reconstruct image, we first decompose the image into two functions with different basic characteristics - structure component and textual component. We seek a sparse representation for the functions and use the DCT coefficients of this representation to generate an over-complete dictionary. Experimental results on real world datasets demonstrate the efficacy of our method in image inpainting. We compare our method with three state-of-the-art inpalnting algorithms and demonstrate its advantages in terms of both quantitative and qualitative aspects.

关键词： image inpainting compressed sensing image decomposing discrete cosine transform

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Spatial interpolation and temperature information visualization

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9th FTRA InternationalConference on Future Information technology, FutureTech 2014

作者： Wang, Linhui Che, Ming Li, Jia Tianjin Key Laboratory of Cognitive Computing and Application School of Computer Science and Technology Tianjin University Tianjin China

ISBN: (纸本)9783642550379

Spatial interpolation on temperature field has gained increased interest in recent years. In this paper we investigate the interpolation accuracy of three frequently used methods (i.e. Inverse-Distance Weighting, Thin Plate Spline and Ordinary Kriging) on the United States temperature data using cross-validation technique. Our results indicate that Ordinary Kriging method has higher interpolation accuracy than other two methods. Finally, an elevation optimization is added to Ordinary Kriging and we can find that it increases interpolation accuracy even further. Based on the interpolated data, this paper also gives a two-dimensional visualization of temperature data and temperature difference data on United States. © 2014 Springer-Verlag Berlin Heidelberg.

关键词： Interpolation

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A real-world web cross-media dataset containing images, texts and videos 14

A real-world web cross-media dataset containing images, text...

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6th International Conference on Internet Multimedia Computing and Service, ICIMCS 2014

作者： Liu, Yanbin Han, Yahong School of Computer Science and Technology Tianjin University China Tianjin Key Laboratory of Cognitive Computing and Application China

ISBN: (纸本)9781450328104

During recent years, the amount of multimedia data on social websites is growing exponentially. It is observed that multimedia data corresponding to the same semantic concept usually appears in different media types and from heterogeneous data sources. In order to synchronize and leverage these diverse forms of media data for multimedia applications, we present a real-world web dataset collected from Google, Flickr and YouTube for cross-media research. The dataset includes 41,387 text files, 65,371 images and 30,818 videos (about 1091 hours) which are correlated semantically with each other by 335 representative visual concepts. Widely-used features are extracted for each media type and all of them are publicly available. To evaluate the performance of our dataset, experiments on baseline recognition, feature evaluation and domain adaptation are performed. The experimental results indicate that it is possible to perform multiple cross-media tasks based on our proposed dataset. Copyright 2014 ACM.

关键词： Semantics

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BP-CF hybrid recommendation algorithm: Implementation and analysis

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ICIC Express Letters, Part B: applications 2015年第1期6卷 227-232页

作者： Yu, Ruiguo Zhang, Minjie Wang, Zan Yuan, Zhenxia School of Computer Science and Technology Tianjin University No. 92 Weijin Road Nankai District Tianjin China Tianjin Key Laboratory of Cognitive Computing and Application Tianjin University No. 92 Weijin Road Nankai District Tianjin China School of Computer Software Tianjin University No. 92 Weijin Road Nankai District Tianjin China

Recommendation algorithm makes personalized recommendation by applying knowledge discovery. Among all recommendation algorithms, the k-nearest neighbor collaborative filtering (CF) is the most widely used. However, the sparsity problem makes the accuracy hardly to improve. In this paper we implement BP neural networks (simplified as BP)-CF hybrid algorithm to use the significant part of the rating matrix maximumly. By modelling with the relatively dense part of rating matrix using BP neural networks, we reduce the MAE on MovieLens dataset from 0.77 to 0.68.

关键词： Collaborative filtering

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A new iterative modularity-based method for graph clustering on scalable networks

A new iterative modularity-based method for graph clustering...

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International Conference on Machine Tool technology and Mechatronics Engineering, ICMTTME 2014

作者： Cui, Yi Tong Zhang, Bing Yi Rao, Guo Zheng School of Computer Science and Technology Tianjin University Tianjin China Tianjin Key Laboratory of Cognitive Computing and Application Tianjin China

ISBN: (纸本)9783038352464

Due to the advancement of technology, modern networks such as social networks, citation networks, Web networks have been extremely large, reaching millions of nodes in a network. But most of the existing graph clustering algorithms can only tackle with small or medium-size networks. In this paper, we introduce a new method which can achieve high graph clustering quality for large scale networks by optimizing the modularity function. It is based on the iterative idea and takes good advantage of the exsiting multilevel local search heuristics. After introducing this modularity-based method, we evaluate its performance by applying it to several well-known network datasets. With a cost of more but acceptable time, it outperforms the best algorithms in the literature in the case of modularity optimization quality. © 2014, Trans Tech Publications, Switzerland.

关键词： Iterative methods

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Extraordinary Hall resistance and unconventional magnetoresistance in Pt/LaCoO3 hybrids

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Physical Review B 2015年第16期92卷 165114-165114页

作者： T. Shang Q. F. Zhan H. L. Yang Z. H. Zuo Y. L. Xie Y. Zhang L. P. Liu B. M. Wang Y. H. Wu S. Zhang Run-Wei Li Key Laboratory of Magnetic Materials and Devices Ningbo Institute of Material Technology and Engineering Chinese Academy of Sciences Ningbo Zhejiang 315201 China Laboratory of Magnetic Materials and Application Technology Ningbo Institute of Material Technology and Engineering Chinese Academy of Sciences Ningbo 315201 China Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 117583 Singapore Department of Physics University of Arizona Tucson Arizona 85721 USA

We report an investigation of transverse Hall resistance and longitudinal resistance on Pt thin films sputtered on epitaxial LaCoO3 (LCO) ferromagnetic insulator films. The LaCoO3 films were deposited on several single crystalline substrates [LaAlO3,(La,Sr)(Al,Ta)O3, and SrTiO3] with (001) orientation. The physical properties of LaCoO3 films were characterized by the measurements of magnetic and transport properties. The LaCoO3 films undergo a paramagnetic to ferromagnetic (FM) transition at Curie temperatures ranging from 40 to 85 K, below which the Pt/LCO hybrids exhibit significant extraordinary Hall resistance up to 50 mΩ and unconventional magnetoresistance ratio Δρ/ρ0 about 1.2×10−4, accompanied by the conventional magnetoresistance. The observed spin transport properties share some common features as well as some unique characteristics when compared with well-studied Y3Fe5O12-based Pt thin films. Our findings call for new theories since the extraordinary Hall resistance and magnetoresistance cannot be consistently explained by the existing theories.

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An unsupervised model for classification and recognition of household appliances

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Journal of Computational Information Systems 2014年第1期10卷 403-410页

作者： Liu, Li Ding, Jiaman Zhong, Jiayu Fu, Xiaodong Lv, Yang Yunnan Provincial Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming 650500 China State-Province Joint Laboratory of Digital Home Interactive Applications School of Information Science and Technology Sun Yat-Sen University Guangzhou 510006 China

Detecting and monitoring the numerous household appliances in smart home is significant for home energy management, because the large various household appliances are complicated to identify and control. This paper proposes an intelligent unsupervised model for the classification and recognition of household appliances. The key idea in this work is to integrate appliance and activity recognition mechanism for effective management and operation within a domestic location. We first present the corresponding classification list of household appliances w. r. t their respective usage patterns and basic power factors. Then, the communication services among various appliances are established to recognize complex appliances and monitor the variation of their states. Finally, the proposed method is applicable for an inexpensive, unsupervised controlling of electrical appliances in a real-time way. Experimental results show that our method effectively provides a financially viable and easily applicable solution for gathering information and monitoring status of diverse household appliances. Copyright © 2014 Binary Information Press.

关键词： Domestic appliances

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