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On YASS’s Non-monotonic Security Performance

Circuits, Systems, and Signal processing 2014年第11期33卷 3527-3537页

作者： Yu, Lifang Zhao, Yao Ni, Rongrong Shi, Yun Qing Institute of Information Science Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Signal and Information Processing for High-end Printing Equipments Beijing Institute of Graphic Communication Beijing102600 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

Recently, researchers have discovered unexpected bumps in the detection rate curve of yet another steganographic scheme (YASS). We refer to this abnormal phenomenon as non-monotonic security performance. This paper first analyzes this abnormality and points out that it is caused by the non-uniformity in probability of coincidence of (Formula presented.) embedding blocks and (Formula presented.) JPEG blocks. Based on this observation, we propose that further randomizing data embedding positions can overcome the non-monotonic security performance. Experimental results have demonstrated a complete removal of bumps in the detection rate curve of YASS after further randomization. © 2014, Springer Science+Business Media New York.

关键词： Steganography

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Construction of extraction model for ontology concept of four diagnostics information

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Journal of Computational information Systems 2015年第7期11卷 2367-2376页

作者： Yuan, Feng Chen, Shouqiang Liu, Hong Xu, Liang School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Shandong Normal University Jinan China School of Information Engineering Shandong Management University Jinan China Center of Hear of the Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine Jinan China Shandong University of Traditional Chinese Medicine Jinan China

This paper is aimed at extraction of ontology concept from four diagnostics information. Due to the diversity and complexity of the four diagnostics information, there are still some difficulties when practicing ontology learning methods for TCM medical cases, so a new concept extraction method combining composite seed extraction and extended concept extraction is proposed for four diagnostics information corpus of TCM. Composite seed extraction refers to a method in which the mutual information is used to determine the appropriateness of word formation between seed and collocations by using seeds as headword to generate concepts. Extended concept extraction refers to a method in which the membership in the domain is used set the fitness function so as to extract extended concept with the assistance of artificial bee colony (ABC) algorithm. The candidate set of concepts is built by combining composite seed concept and extended concept. Through a confirmatory experiment on four diagnostics information corpus of TCM medical cases, this method is cautiously confirmed effective for concept extraction. Hence, this method has a certain reference value for ontology construction of four diagnostics information. ©, 2015, Binary information Press. All right reserved.

关键词： Extraction

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Sub-pixel change detection for urban land-cover analysis via multi-temporal remote sensing images

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Geo-Spatial information Science 2014年第1期17卷 26-38页

作者： Peijun DU Sicong LIU Pei LIU Kun TAN Liang CHENG Key Laboratory for Satellite Mapping Technology and Application of National Administration of Surveying Mapping and GeoinformationNanjing UniversityNanjing CityJiangsu ProvinceP.R.China Department of Information Engineering and Computer Science University of TrentoTrentoItaly Jiangsu Provincial Key Laboratory for Resources and Environment Information Engineering China University of Mining and TechnologyXuzhouJiangsu ProvinceP.R.China

Conventional change detection approaches are mainly based on per-pixel processing,which ignore the sub-pixel spectral variation resulted from spectral *** for medium-resolution remote sensing images used in urban landcover change monitoring,land use/cover components within a single pixel are usually complicated and heterogeneous due to the limitation of the spatial ***,traditional hard detection methods based on pure pixel assumption may lead to a high level of omission and commission errors inevitably,degrading the overall accuracy of change *** order to address this issue and find a possible way to exploit the spectral variation in a sub-pixel level,a novel change detection scheme is designed based on the spectral mixture analysis and decision-level *** spectral mixture model is selected for spectral unmixing,and change detection is implemented in a sub-pixel level by investigating the inner-pixel subtle changes and combining multiple composition *** proposed method is tested on multi-temporal Landsat Thematic Mapper and China–Brazil Earth Resources Satellite remote sensing images for the land-cover change detection over urban *** effectiveness of the proposed approach is confirmed in terms of several accuracy indices in contrast with two pixel-based change detection methods(*** vector analysis and principal component analysis-based method).In particular,the proposed sub-pixel change detection approach not only provides the binary change information,but also obtains the characterization about change direction and intensity,which greatly extends the semantic meaning of the detected change targets.

关键词： change detection sub-pixel level processing multi-temporal images spectral mixture model back propagation neural network remote sensing

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Hidden space discriminant neighborhood embedding

Hidden space discriminant neighborhood embedding

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International Joint Conference on Neural Networks (IJCNN)

作者： Chuntao Ding Li Zhang Bangjun Wang School of Computer Science and Technology & Provincial Key laboratory for Computer Information Processing Soochow University Suzhou Jiangsu China

Discriminant neighborhood embedding (DNE) algorithm is one of supervised linear dimensionality reduction methods. Its nonlinear version kernel discriminant neighborhood embedding (KDNE) is expected to behave well on classification tasks. However, since KDNE constructs an adjacent graph in the original space, the adjacency graph could not represent the adjacent information in the kernel mapping space. By introducing hidden space, this paper proposes a novel nonlinear method for DNE, called hidden space discriminant neighborhood embedding (HDNE). This algorithm first maps the data in the original space into a high dimensional hidden space by a set of nonlinear hidden functions, and then builds an adjacent graph incorporating neighborhood information of the dataset in the hidden space. Finally, DNE is used to find a transformation matrix which would map the data in the hidden space to a low-dimensional subspace. The proposed method is applied to ORL face and MNIST handwritten digit databases. Experimental results show that the proposed method is efficiency for classification tasks.

关键词： Joints Conferences Neural networks

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A programming related courses' E-learning platform based on online judge

A programming related courses' E-learning platform based on ...

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5th International Symposium on IT in Medicine and Education, ITME 2013

作者： Fang, Xiaonan Zhang, Huaxiang Sun, Yunchen School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan China

ISBN: (纸本)9789400776173

Coding practice is the most efficient way in learning of programming related courses. In this paper, we propose a programming related courses' E-learning platform based on online judge. This platform is designed according to B/S structure, and page optimization techniques such as Gzip are applied to boost the access speed. Teaching achievements prove that the platform can markedly improve the learning effect of programming related courses. © Springer Science+Business Media Dordrecht 2014.

关键词： E-learning

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Research on distributed data stream mining in Internet of things

Research on distributed data stream mining in Internet of th...

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2014 International Conference on Logistics Engineering, Management and computer Science, LEMCS 2014

作者： Xu, Liancheng Xun, Jiao School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan China

ISBN: (纸本)9789462520103

For mining useful data from mass data generated by Internet of things, analyses shortages of the traditional Apriori algorithm which has a lower mining efficiency and occupies the larger memory space. So, MapReduce model of cloud computing is introduced. In the mechanism of MapReduce, combine the architecture characteristics and key technology of Internet of Things, conduct distributedmining on data and information in environment of the Internet of Things, and the calculation model of distributed data stream mining is drawn. Performance analysis proves that the new data stream mining model overcomes difficulty of traditional data mining, and each link reflects the idea of distributed structure and improves mining efficiency obviously. © 2014. The authors - Published by Atlantis Press.

关键词： Cloud computing

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An adaptive haze removal based on dark channel prior and image decoding acceleration method

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ICIC Express Letters 2015年第3期9卷 775-781页

作者： Sun, Hong-Guang Fang, Chao Yang, Xi-Quan Yang, Feng-Qin Sun, Tie-Li Hung, Chih-Cheng School of Computer Science and Information Technology No. 2555 Jingyue Ave. Changchun China College of Humanities and Sciences Northeast Normal University No. 2555 Jingyue Ave. Changchun China Key Laboratory of Intelligent Information Processing of Jilin Universities No. 2555 Jingyue Ave. Changchun China School of Computing and Software Engineering Southern Polytechnic State University MariettaGA United States

In this paper, we propose an adaptive haze removal method based on dark channel prior. The dark channel value is compensated for estimating the transmission;the atmospheric light will be re-estimated through the analysis of the characteristics of images. Images are usually degraded with haze due to the object absorption and atmospheric scattering. The experiments show that the images recovered by the proposed method are better than other existing methods and recovered images are closer to real images. Meanwhile, the Mean Square Error (MSE) is used to verify the proposed approach for the images recovered which are taken from the FRIDA database. Through the comparison of Inverse Discrete Cosine Transforms (IDCT) of haze images and haze-free images, the statistics of the comparison shows that the haze images consume more computation time. To improve the time complexity, the Graphics processing Unit (GPU) was used to increase the computing efficiency. © 2015, ICIC International.

关键词： Graphics processing unit

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An efficient algorithm for hamilton cycle based on the enlarged rotation-extension technique

An efficient algorithm for hamilton cycle based on the enlar...

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International MultiConference of Engineers and computer Scientists, IMECS 2014

作者： Du, Lizhi College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan430065 China

ISBN: (纸本)9789881925336

Algorithm studies on the Hamilton cycle are mainly based on the Rotation-Extension method developed by Posa. However, due to the deficiency of Posa's method, all these products are only efficient for much denser graphs or sparse but regular graphs. By many years' study, we developed the "Enlarged Rotation-Extension" technique which utterly changed and expanded the Posa's original one and can surmount its deficiency. Based on this technique, our algorithm can quickly calculate randomly produced un-directed graphs with up to ten thousand vertices on personal computer, no matter dense or sparse, the correctness is one hundred percent. We also calculated the data of hamilton cycles on a famous web site and we still got one hundred percent correctness.

关键词： Computational complexity

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Augment dependency-to-string translation with fixed and floating structures 25

Augment dependency-to-string translation with fixed and floa...

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25th International Conference on Computational Linguistics, COLING 2014

作者： Xie, Jun Xu, Jinan Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China School of Computer and Information Technology Beijing Jiaotong University China School of Computing Dublin City University Ireland

ISBN: (纸本)9781941643266

In this paper, we propose an augmented dependency-to-string model to combine the merits of both the head-dependents relations at handling long distance reordering and the fixed and floating structures at handling local reordering. For this purpose, we first compactly represent both the head-dependent relation and the fixed and floating structures into translation rules;second, in decoding we build "on-the-fly" new translation rules from the compact translation rules that can incorporate non-syntactic phrases into translations, thus alleviate the non-syntactic phrase coverage problem of dependency-to-string translation (Xie et al., 2011). Large-scale experiments on Chinese-to-English translation show that our augmented dependency-to-string model gains significant improvement of averaged +0.85 BLEU scores on three test sets over the dependencyto- string model.

关键词： Syntactics

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An Efficient Image Enhancement Method Based on Image Saliency Detection for Portrait Photo

An Efficient Image Enhancement Method Based on Image Salienc...

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2014 International Conference on Advanced computer Science and Engineering(ACSE 2014)

作者： Si-qi WU Yao HU Wei-yu YU School of Electronic and Information Engineering South China University of Technology Provincial Key Laboratory for Computer Information Processing Technology Soochow University

The portrait region of portrait photo may be too dark due to backlight during the process of photo taking. Aiming at this problem, we propose a new image enhancement method based on histogram-based contrast method(HC) image saliency detection. Portrait area in portrait photo is the most salient region, thus we first use HC to measure saliency and then extract the portrait area from the portrait photo with the help of saliency map. We simply enhance the portrait region, keeping the background unchanged. Experiment results prove that proposed algorithm is able to compress the dynamic range of the original image and yield pleasing enhancement result.

关键词： Image enhancement Image saliency detection Portrait photo

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