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arXiv 2017年

作者： Luo, Luo Chen, Cheng Zhang, Zhihua Li, Wu-Jun Zhang, Tong Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China National Engineering Lab for Big Data Analysis and Applications School of Mathematical Sciences Peking University 5 Yiheyuan Road Beijing100871 China National Key Laboratory for Novel Software Technology Collaborative Innovation Center of Novel Software Technology and Industrialization Department of Computer Science and Technology Nanjing University 163 Xianlin Avenue Nanjing210023 China Computer Science & Mathematics Hong Kong University of Science and Technology Hong Kong

The frequent directions (FD) technique is a deterministic approach for online sketching that has many applications in machine learning. The conventional FD is a heuristic procedure that often outputs rank deficient matrices. To overcome the rank deficiency problem, we propose a new sketching strategy called robust frequent directions (RFD) by introducing a regularization term. RFD can be derived from an optimization problem. It updates the sketch matrix and the regularization term adaptively and jointly. RFD reduces the approximation error of FD without increasing the computational cost. We also apply RFD to online learning and propose an effective hyperparameter-free online Newton algorithm. We derive a regret bound for our online Newton algorithm based on RFD, which guarantees the robustness of the algorithm. The experimental studies demonstrate that the proposed method outperforms state-of-the-art second order online learning algorithms. Copyright © 2017, The Authors. All rights reserved.

关键词： Heuristic methods

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Building Chinese affective resources in valence-arousal dimensions 15

Building Chinese affective resources in valence-arousal dime...

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15th Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016

作者： Yu, Liang-Chih Lee, Lung-Hao Hao, Shuai Wang, Jin He, Yunchao Hu, Jun Lai, K. Robert Zhang, Xuejie Department of Information Management Yuan Ze University Taiwan Department of Computer Science and Engineering Yuan Ze University Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taiwan Information Technology Center National Taiwan Normal University Taiwan School of Software Nanchang University Jiangxi China School of Information Science and Engineering Yunnan University Yunnan China

ISBN: (纸本)9781941643914

An increasing amount of research has recently focused on representing affective states as continuous numerical values on multiple dimensions, such as the valence-arousal (VA) space. Compared to the categorical approach that represents affective states as several classes (e.g., positive and negative), the dimensional approach can provide more fine-grained sentiment analysis. However, affective resources with valence-arousal ratings are still very rare, especially for the Chinese language. Therefore, this study builds 1) an affective lexicon called Chinese valence-arousal words (CVAW) containing 1,653 words, and 2) an affective corpus called Chinese valence-arousal text (CVAT) containing 2,009 sentences extracted from web texts. To improve the annotation quality, a corpus cleanup procedure is used to remove outlier ratings and improper texts. Experiments using CVAW words to predict the VA ratings of the CVAT corpus show results comparable to those obtained using English affective resources. ©2016 Association for Computational Linguistics.

关键词： Sentiment analysis

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Automatic Identification of Traffic Accidents based on Intelligent Identification

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Journal of Physics: Conference Series 2018年第6期1087卷

作者： Huihong Chen Shiming Li Chen Huihong (School of information engineering Guangzhou Panyu polytechnic University Guangzhou China 511483) Fujian Gutian people associate professor master mainly engaged in image recognition software development and big data research. *** Liu Shiming (Corresponding author) (School of management Guangzhou Panyu polytechnic University Guangzhou China 511483) Hubei Zaoyang people senior engineer doctor mainly engaged in safety early warning risk analysis and evaluation safety management. ***

The traffic accident process system is complex, by extracting the traffic accident information, the real-time state monitoring of the traffic accident image can be realized. A method of traffic accident information extraction and automatic recognition is proposed based on depth neural network and intelligent image analysis. The remote sensing method is used to collect the traffic accident image, the traffic accident remote sensing image is adaptively de-noised, and the block feature matching method is used to deal with the traffic accident image block fusion. The feature extraction of traffic accident state is carried out in the subspace component of traffic accident image, and the image feature classification of traffic accident is processed by using depth neural network classifier to realize image feedback recognition of traffic accident state feature quantity. A large number of traffic video images are selected for experiments. The simulation results show that the proposed method is more intelligent and accurate.

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Quantum homomorphic signature using coherent states 2

Quantum homomorphic signature using coherent states

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2nd IEEE International Conference on Computer and Communications, ICCC 2016

作者： Luo, Qingbin Yang, Guowu She, Kun Li, Xiaoyu Yuqi, Wang School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Edward S. Rogers Sr. Department of Electrical Computer Engineering Department University of Toronto TorontoONM5S 3G4 Canada Big Data Research Center and School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China College of Computer Minnan Normal University Zhangzhou China

ISBN: (纸本)9781467390262

In this paper, a novel scheme for quantum homomorphic signature based on coherent states is proposed, which is an effective approach to identity authentication for multiple streams to enhance the security of quantum networks. The state used for signature are arbitrarily close in trace distance to states of O(log2n), if the length of the nodes' messages is n-bit. The scheme analysis shows that the scheme is a quantum group homomorphic signature scheme and the signature is unforgeable. © 2016 IEEE.

关键词： Quantum theory

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A secure access and associate deleting scheme for multi-replica in multi-cloud environment

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International Journal of High Performance Systems Architecture 2016年第3期6卷 143-152页

作者： Xiong, Jinbo Li, Suping Li, Xuan Zhang, Yuanyuan Jin, Biao Faculty of Software Fujian Normal University Fuzhou China Fujian Provincial Key Laboratory of Network Security and Cryptology Fujian Normal University Fuzhou China Fujian Engineering Research Center Public Service Big Data Mining and Application Fuzhou China

With the rapid development of cloud services in multi-cloud environment, it is convenient to generate multi-replica for user's data stored in multi-cloud servers. On the one hand, multi-replica is able to improve data availability and users' experience. But on the other hand, it becomes increasingly easy to disclose sensitive data and brings serious challenges to security and privacy for user's data and its multi-replica. In order to tackle the above issues, in this paper, we propose a secure access and associate deleting scheme for multi-replica (MADS) in multi-cloud environment, which is based on symmetric encryption algorithm, attribute-based encryption and replica location technology. We construct a novel multi-layered key structure, called multi-way search key tree (MSKT) that ensures no key material will be revealed, yet the data owner is able to control the master key and manage other keys by performing some tree operations. We also propose a data replica associated model, which is able to associate all the data replicas in multi-cloud environment. Comprehensive comparison and security analysis demonstrate that the proposed MADS scheme is effective and secure. Copyright © 2016 Inderscience Enterprises Ltd.

关键词： Sensitive data

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A Multi-replica Associated Deleting Scheme in Cloud

A Multi-replica Associated Deleting Scheme in Cloud

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International Conference on Complex, Intelligent and software Intensive Systems, CISIS

作者： Yuanyuan Zhang Jinbo Xiong Xuan Li Biao Jin Suping Li Xu An Wang Fujian Provincial Key Laboratory of Network Security and Cryptology Fujian Normal University Fuzhou China Fujian Engineering Research Center of Public Service Big Data Mining and Application Fuzhou China Faculty of Software Fujian Normal University Fuzhou China Fujian Eng. Res. Center of Public Service Big Data Min. & Applic. Fuzhou China Engineering University of CAPF Xi'an China

ISBN: (纸本)9781509009886

Rapid development of cloud storage services produces a tremendous amount of user data outsourcing to cloud servers. Therefore, it is easy to generate data multi-replica, which is able to improve data availability and users' experience. However, when the management of data is poor, the sensitive information will be disclosed more easily. This may bring serious security and privacy challenges for both user's data and its multi-replica in cloud environment. In order to tackle the above issues, in this paper, we propose a multi-replica associated deleting scheme (MADS) in cloud environment. We first introduce a replica associated model to organize all of data replicas among different cloud servers. Furthermore, we propose the MADS scheme which is consists of data storage algorithm, replica generation algorithm, replica deletion and feedback algorithm. Finally, we employ Amazon S3 to implement MADS and the results indicate that the proposed scheme is available and effective.

关键词： Servers Cloud computing Memory Security data privacy Metadata

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Erratum to: An improved block-based matching algorithm of copy-move forgery detection

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Multimedia Tools and Applications 2017年第12期77卷 15111-15111页

作者： Lai, Yuecong Huang, Tianqiang Lin, Jing Lu, Henan School of Mathematics and Computer Science Fujian Normal University Fuzhou China Faculty of Software Fujian Normal University Fuzhou China Fujian Engineering Research Center of Public Service Big Data Mining and Application Fujian Normal University Fuzhou China

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Micro-Expression Recognition based on 2D Gabor Filter and Sparse Representation

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Journal of Physics: Conference Series 2017年第1期787卷

作者： Hao Zheng Key Laboratory of Trusted Cloud Computing and Big Data Analysis School of Information Engineering Nanjing XiaoZhuang University Nanjing China MOE Key Laboratory of Computer Network and Information Integration School of Computer Science and Engineering Southeast University Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

Micro-expression recognition is always a challenging problem for its quick facial expression. This paper proposed a novel method named 2D Gabor filter and Sparse Representation (2DGSR) to deal with the recognition of micro-expression. In our method, 2D Gabor filter is used for enhancing the robustness of the variations due to increasing the discrimination power. While the sparse representation is applied to deal with the subtlety, and cast recognition as a sparse approximation problem. We compare our method to other popular methods in three spontaneous micro-expression recognition databases. The results show that our method has more excellent performance than other methods.

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Image segmentation using membrane computing: A literature survey 11th

Image segmentation using membrane computing: A literature su...

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Yahya, Rafaa I. Shamsuddin, Siti Mariyam Yahya, Salah I. Hasan, Shafatnnur Al-Salibi, Bisan Al-Khafaji, Ghada Faculty of Computing Universiti Teknologi Malaysia UTM SkudaiJohor81310 Malaysia Department of Computer College of Science University of Al-Mustansiriyah Baghdad Iraq UTM Big Data Center Ibnu Sina Institute for Scientific and Industrial Research Universiti Teknologi Malaysia UTM SkudaiJohor81310 Malaysia Department of Software Engineering Koya University Iraq School of Computer Sciences Universiti Sains Malaysia USM GelugorPenang11800 Malaysia Department of Computer Science College of Science Baghdad University Baghdad Iraq

ISBN: (纸本)9789811036101

Membrane computing, a recent branch of natural computing, has been gaining momentum attention in the last few decades due to its massive parallelism and efficient computation. Many researchers in the field of membrane computing have proposed sophisticated techniques inspired by cell biology for computer science applications, especially when they considered cell organization in tissues, organs, and most recently, from the organization of neurons. The interdisciplinary applications of membrane computing include, but not limited to computer science, biology, biomedicine, bioinformatics and several other fields such as mathematics, artificial intelligence, automation, economics, to name but a few. Their applications are pertaining to computer graphics, approximate optimization, cryptography, parallel computing and image processing. Hence, in this paper we present an up to date comprehensive literature review pertaining to the application of membrane computing in the area of digital image analysis, especially image segmentation, comprehensively and systematically. We thoroughly investigate the recent advancement in the field of image segmentation using membrane system. Furthermore, we highlight the merits and demerits of various software tools and methods. Finally, we suggest some intuitive future directions in light of the current limitations. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Image segmentation

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The Beauty of Geometry: A touch-operation-based DGS for mathematics education

The Beauty of Geometry: A touch-operation-based DGS for math...

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International Conference on Computer Science & Education (ICCSE)

作者： Baoling Chen Yong Huang Yongsheng Rao Ying Hu Ying Wang Chuanjun Zhang School of Computer Science and Educational Software Guangzhou University Guangzhou China Guizhou Provincial Academician Workstation of Educational Big Data Technology and Educational Mathematics Guiyang China GuangDong Provincial Engineering Technology Research Center for Mathematical Educational Software Guangzhou China Network and Modern Education Technology Center Guangzhou University Guangzhou China South China Institute of Software Engineering Guangzhou University Guangzhou China Guizhou Provincial Educational Science Academy Guiyang China

ISBN: (纸本)9781509022199

The Beauty of Geometry, a touch-operation-based Dynamic Geometry software (DGS) we develop for mathematics education by Objective-C, is introduced. The paper starts with the main contents of the Beauty of Geometry, including Intelligent drawing, Dynamic geometry, Geometric transformations, Animation, Measurement and Sharing, then we talk about the features of the system from three aspects, and consider a concrete example to show it how to make geometry learning be more simple and intuitive, finally we make a conclusion that the exploring of the touch-operation-based DGS is still in the initial stage, and propose what to do next to make the Beauty of Geometry smart and friendly.

关键词： Geometry software Education Thumb Mobile handsets

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