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An integratable verifiable secret sharing mechanism

International Journal of Network Security 2016年第4期18卷 617-624页

作者： Liu, Yanjun Chang, Chin-Chen Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University No. 111 Jiulong Rd Hefei230601 China Department of Computer Science and Information Engineering Asia University No. 500 Lioufeng Rd Wufeng Taichung413 Taiwan Department of Information Engineering and Computer Science Feng Chia University No. 100 Wenhwa Rd Seatwen Taichung413 Taiwan

Threshold secret sharing (SS), also denoted as (t, n) SS, has been used extensively in the area of information se- curity, such as for group authentication, cloud storage schemes, secure parallel communication and wireless mul- tipath routing protocols. However, a (t, n) SS cannot de- tect any deceptions among the dealer and shareholders. Veriable secret sharing (VSS) overcomes the weakness of (t, n) SS in such a way that it is able to detect cheaters by verifying the validity of shares or the correctness of the recovered secret under the condition that both shares and the secret are not compromised. Recently, two non- interactive VSSs based on Asmuth-Bloom's SS were pro- posed by Harn et al. and Liu et al., respectively. Both VSSs require shareholders to examine the range of values of some integers related to the secret before recovering the secret, which is a time-consuming operation. In this paper, we propose a novel integratable VSS mechanism that integrates the concepts of the generalized Chinese remainder theorem (GCRT), Shamir's SS and Asmuth- Bloom's SS. Our proposed VSS can verify that the secret reconstructed by any t or more shareholders is the same as the one that the dealer has generated. Analysis shows that our proposed VSS can provide perfect secrecy and better efficiency.

关键词： Hash functions

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ECNU at 2015 CDS Track:Two Re-ranking Methods in Medical information Retrieval 24

ECNU at 2015 CDS Track:Two Re-ranking Methods in Medical Inf...

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24th Text REtrieval Conference, TREC 2015

作者： Song, Yang He, Yun Hu, Qinmin He, Liang Shanghai Key Laboratory of Multidimensional Information Processing China Department of Computer Science & Technology East China Normal University Shanghai200241 China

This paper summarizes our work on the TREC 2015 Clinical Decision Support Track. We present a customized learning-to-rank algorithm and a query term position based re-ranking model to better satisfy the tasks. We design two learning-to-rank framework: the pointwise loss function based on random forest and the pairwise loss function based on SVM. The position based re-ranking model is composed of BM25 and a heuristic kernel function which integrates Gaussian, triangle, cosine and the circle kernel function. Furthermore, the Web-based query expansion method is utilized to improve the quality of the queries. © 2015 24th Text REtrieval Conference, TREC 2015 - Proceedings. All Rights Reserved.

关键词： Decision support systems

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Extended multi-structure local binary pattern for high-resolution image scene classification

Extended multi-structure local binary pattern for high-resol...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiaoyong Bian Chen Chen Qian Du Yuxia Sheng Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Department of Electrical Engineering University of Texas at Dallas Richardson TX USA Department of Electrical and Computer Engineering Mississippi State University Mississippi State USA School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

This paper presents a novel extended multi-structure local binary pattern (EMSLBP) approach for high-resolution image classification, generalizing the well-known local binary pattern (LBP) approach. In the proposed EMSLBP approach, three-coupled descriptors with multi-structure sampling are proposed to extract complementary features (pixel value and radial difference) from local image patches. The anisotropic features derived from elliptical sampling are also rotation invariant by averaging the histograms over rotational angles and combined with the isotropic features extracted from circular sampling. Experimental results show that the proposed method can effectively capture local spatial pattern and local contrast, consistently outperforming several state-of-the-art classification algorithms.

关键词： Feature extraction Histograms Nickel Image classification Support vector machines Training Image resolution

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Violent Interaction Detection in Video Based on Deep Learning

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Journal of Physics: Conference Series 2017年第1期844卷

作者： Peipei Zhou Qinghai Ding Haibo Luo Xinglin Hou Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 University of Chinese Academy of Sciences Beijing 100049 Key Laboratory of Opto-Electronic Information Processing CAS Shenyang 110016 The Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang 110016 Space star technology co. LTD Beijing 100086

Violent interaction detection is of vital importance in some video surveillance scenarios like railway stations, prisons or psychiatric centres. Existing vision-based methods are mainly based on hand-crafted features such as statistic features between motion regions, leading to a poor adaptability to another dataset. En lightened by the development of convolutional networks on common activity recognition, we construct a FightNet to represent the complicated visual violence interaction. In this paper, a new input modality, image acceleration field is proposed to better extract the motion attributes. Firstly, each video is framed as RGB images. Secondly, optical flow field is computed using the consecutive frames and acceleration field is obtained according to the optical flow field. Thirdly, the FightNet is trained with three kinds of input modalities, i.e., RGB images for spatial networks, optical flow images and acceleration images for temporal networks. By fusing results from different inputs, we conclude whether a video tells a violent event or not. To provide researchers a common ground for comparison, we have collected a violent interaction dataset (VID), containing 2314 videos with 1077 fight ones and 1237 no-fight ones. By comparison with other algorithms, experimental results demonstrate that the proposed model for violent interaction detection shows higher accuracy and better robustness.

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Autonomous migration of virtual machine based on OpenStack

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International Journal of Hybrid information technology 2016年第8期9卷 65-84页

作者： Zhou, Li Yu, Zhuoer Zhang, Jilin Wan, Jian Wu, Yusen School of Computer and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou China College of Electrical Engineering Zhejiang University Hangzhou310058 China School of Information and Electronic engineering Zhejiang University of Science & Technology Hangzhou310023 China Zhejiang Provincial Engineering Center on Media Data Cloud Processing and Analysis HangzhouZhejiang China

For the problem of compute nodes load unbalance leads to the overload node impact VM performance and the underload node waste electrical energy. Dynamic VM consolidation is an efficient approach for improving the utilization of servers and reducing energy costs. In this paper, we introduce dynamic consolidation into OpenStack and implement AMVM based on OpenStack. AMVM collect and analyze all performance data of VM and compute node in OpenStack. Then AMVM automatically schedules VM live migrate to the most appropriate node according to the real-time load of all compute nodes. Then we use hybrid-copy instead of pre-copy in AMVM to improve the efficiency of VM live migration. Finally, we analyze the performance of hybrid-copy, hybrid-copy can reduce page faults compared with post-copy and reduce total data transferred compared with pre-copy. © 2016 SERSC.

关键词： Virtual machine

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A new logistic map based chaotic biogeography-based optimization approach for cluster analysis

A new logistic map based chaotic biogeography-based optimiza...

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Changsha Hunan China School of Computer Science and Technology Nanjing Normal University Nanjing Jiangsu China Department of Electrical Engineering CUNY New York NY USA Department of Mechanical and Control Engineering Kyushu Institute of Technology Fukuoka Prefecture Japan School of Information Engineering Yangzhou University Yangzhou Jiangsu China School of Physics and Electronic Engineering Taizhou University Taizhou Zhejiang China School of Electronic Information Shanghai Dianji University Shanghai China School of Energy and Mechanical Engineering Nanjing Normal University Nanjing Jiangsu China Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University Quanzhou Fujian China

ISBN: (纸本)9781509034857

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization (CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： Genetic algorithms Optimization Clustering algorithms Particle swarm optimization Algorithm design and analysis Logistics Mathematical model

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Online hot event discovery based on Association Link Network

Online hot event discovery based on Association Link Network

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作者： Liu, Yang Luo, Xiangfeng Xuan, Junyu School of Computer Engineering and Science Shanghai University China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing China

Online hot event discovery has become a flourishing frontier where online document streams are monitored to discover newly occurring events or assigned to previously detected events. However, hot events have the nature to evolve, and their inherent topically related words are also likely to evolve. It makes event discovery a challenging task for traditional-mining approaches. Combining word association and semantic community, Association Link Network (ALN) organizes the loosely distributed associated resources. This paper presents an ALN-based novel online hot event discovery approach. Technically, this approach is enacted around three stages. In the first stage, we extract significant features to represent the content of each document from the online document stream. During the second stage, we classify the online document stream into topically related detected events considering event evolution in the form of ALN. At the third stage, we create an ALN-based event detection algorithm, which is used to timely discover newly occurring hot events. The online datasets used in our empirical studies are acquired from Baidu News, which spans a range of 1315 hot events and 236,300 documents. Experimental results demonstrate the hot events discovery ability with respect to high accuracy, good scalability, and short runtime. © 2015 John Wiley & Sons, Ltd.

关键词： Semantics

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A Parallel Algorithm to Construct BISTs on Parity Cubes

A Parallel Algorithm to Construct BISTs on Parity Cubes

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International Conference on information Science and Control Engineering (ICISCE)

作者： Yan Wang Jianxi Fan Wenjun Liu Yuejuan Han Provincial Key Laboratory for Computer Information Processing Technology Soochow University School of Computer Science and Technology Soochow University Suzhou China

ISBN: (纸本)9781467368513

Independent spanning trees(ISTs) have applications in interconnection networks such as reliable communication protocols, and secure message distribution, etc. In this paper, we use BIST to denote the IST isomorphic to binomial-like tree. We propose an algorithm to construct n BISTs and the algorithm can be parallelized on PQ n to run in O(N) time, where N = 2 n .

关键词： Broadcasting Hypercubes computer science Reliability computer network reliability Built-in self-test

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Picture array generation using flat splicing operation

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Journal of Computational and Theoretical Nanoscience 2016年第6期13卷 3568-3577页

作者： Pan, Linqiang Nagar, Atulya K. Subramanian, K.G. Song, Bosheng School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou Henan450002 China Department of Mathematics and Computer Science Faculty of Science Liverpool Hope University LiverpoolL16 9JD United Kingdom Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei430074 China

The operation of splicing on words was introduced by Tom Head while proposing a theoretical model of DNA recombination. Subsequent investigations on splicing on linear and circular strings of symbols have resulted in a number of theoretical properties. A different kind of splicing on two words, referred to as flat splicing, has been considered recently. This operation is extended to flat splicing on picture arrays, thus defining a new model of generation of digitized pictures, which is called as array flat splicing system (AFS). Results on the generative power of AFS in comparison with certain well-known picture array defining models and certain non-closure results are obtained. Copyright © 2016 American Scientific Publishers. All rights reserved.

关键词： Nanoscience

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Pedestrian detection and counting based on ellipse fitting and object motion continuity for video data analysis 11th

Pedestrian detection and counting based on ellipse fitting a...

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11th International Conference on Intelligent Computing, ICIC 2015

作者： Wang, Yaning Zhang, Hong College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China

ISBN: (纸本)9783319221793

In order to detect and count pedestrians in different kinds of scenes, this paper put forward a method of solving the problem on video sequences captured from a fixed camera. After preprocessing operations on the original video sequences (Gaussian mixture modeling, three-frame-differencing, image binaryzation, Gaussian filtering, dilation and erosion) we extract the relatively complete pedestrian contours. Then we use the least square ellipse fitting method on those contours that has been extracted, the center of the ellipse is undoubtedly regarded as the tracking point of a pedestrian. With those points, a pedestrian matching pursuit and counting algorithm based on object motion continuity is used for tracking and counting pedestrians, this method can be better used in those scenes which are sparse and rarely obscured. Experiments validate that our pedestrian matching pursuit and counting algorithm has obvious superiorities: good real-time performance and high accuracy. © Springer International Publishing Switzerland 2015.

关键词： Geometry

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