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Trajectory data privacy protection based on differential privacy mechanism

IOP Conference Series: Materials Science and Engineering 2018年第1期351卷

作者： Ke Gu Lihao Yang Yongzhi Liu Niandong Liao School of Computer and Communication Engineering Changsha University of Science and Technology Changsha 410114 China Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology Changsha 410114 China

In this paper, we propose a trajectory data privacy protection scheme based on differential privacy mechanism. In the proposed scheme, the algorithm first selects the protected points from the user's trajectory data; secondly, the algorithm forms the polygon according to the protected points and the adjacent and high frequent accessed points that are selected from the accessing point database, then the algorithm calculates the polygon centroids; finally, the noises are added to the polygon centroids by the differential privacy method, and the polygon centroids replace the protected points, and then the algorithm constructs and issues the new trajectory data. The experiments show that the running time of the proposed algorithms is fast, the privacy protection of the scheme is effective and the data usability of the scheme is higher.

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Precise linearization optimal control of cell three-compartment transition model

Precise linearization optimal control of cell three-compartm...

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International Conference on Systems and Informatics (ICSAI)

作者： Zhaolei Diao Hui Lv Xianwen Fang Zhixiang Yin Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing (Dalian University) Dalian China School of Mathematics and Big Data Anhui University of Science and Technology Huainan China School of Computer Science and Technology Dalian University of Technology Dalian China

In this study, the problems of precise linearization and optimal control for the cell three-compartment transition model are investigated. According to the differential geometry theory of nonlinear system, three-compartment nonlinear affine model of intracellular and extracellular distribution of 1, 6-diphenyl-1, 3, 5-hexatriene (DPH) is established. A nonlinear state feedback expression is deduced by means of state feedback precise linearization method to realize the linearization of the nonlinear system. Furthermore, the state feedback coefficient is optimized by solving Riccati's equation. The obtained control law is simple and easy to implement. The numerical simulation results show that the feedback system constructed by the nonlinear control strategies has good stability characteristics, and the dynamic response characteristic is improved obviously.

关键词： Lipidomics Fluorescence Biomembranes Probes Nonlinear systems State feedback Optimal control

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Incentivizing the Biased Requesters: Truthful Task Assignment Mechanisms in Crowdsourcing

Incentivizing the Biased Requesters: Truthful Task Assignmen...

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IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： Jia Xu Hui Li Yanxu Li Dejun Yang Tao Li Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing Jiangsu China School of Computer Nanjing University of Posts and Telecommunications Nanjing Jiangsu China Department of Computer Science Colorado School of Mines Golden CO USA

ISBN: (纸本)9781509066001

Crowdsourcing has become an effective tool to utilize human intelligence to perform tasks that are challenging for machines. In the integrated crowdsourcing systems, the requesters are non- monopolistic and may show preferences over the workers. We are the first to design the incentive mechanisms, which consider the issue of stimulating the biased requesters in the competing crowdsourcing market. In this paper, we explore truthful task assignment mechanisms to maximize the total value of accomplished tasks for this new scenario. We present three models of crowdsourcing, which take the preferences of the requesters and the workload constraints of the workers into consideration. We design a task assignment mechanism, which follows the matching approach to solve the Valuation Maximizing Assignment (VMA) problem for each of the three models. Through both rigorous theoretical analyses and extensive simulations, we demonstrate that the proposed assignment mechanisms achieve computational efficiency, workload feasibility, preference (universal) truthfulness and constant approximation.

关键词： Crowdsourcing Computational modeling Cost accounting Mobile communication Aggregates Mechanical factors Knowledge engineering

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A parallel evolutionary extreme learning machine scheme for electrical load prediction

A parallel evolutionary extreme learning machine scheme for ...

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Science and Information Conference (SAI)

作者： Peikun Chen Wanhua Li Yuzhong Chen Kun Guo Yuzhen Niu College of Mathematics and Computer Science Fuzhou University Fuzhou Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou Fujian Collaborative Innovation Center for Big Data Applications in Governments Fuzhou Fuzhou China

ISBN: (纸本)9781509054442

Application of cloud computing technologies in power system has made a great contribution to the establishment of smart grid. Among applications of smart grid, electrical load prediction plays an important role in efficient use of power resource. However, the exponential growth of data has posed a great challenge to the existing algorithms. In this paper, we firstly propose a novel parallel hybrid algorithm, combining the Improved Particle Swarm Optimization (PSO) with ELM, named PIPSO-ELM. Here a modified particle swarm optimization is presented to find the optimal number of hidden neurons as well as the corresponding input weights and hidden biases. Furthermore, in the iterative search process of PSO, an update strategy employs the mutation operator of evolutionary algorithms is introduced for further improving the global search capability and convergence speed of PSO. After that, to handle the large-scale dataset efficiently, the parallel implementation of PIPSO-ELM is achieved using Spark. Finally, extensive experiments on real-life electrical load data and comprehensive evaluation are conducted to verify the performance of PIPSO-ELM in electrical load prediction. Extensive experimental results demonstrate that PIPSO-ELM outperforms the compared algorithms in terms of stability, efficiency and scalability simultaneously.

关键词： Neurons Particle swarm optimization Algorithm design and analysis Prediction algorithms Smart grids Encoding Convergence

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Survey of key technologies on millimeter-wave CMOS integrated circuits

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IOP Conference Series: Materials Science and Engineering 2018年第1期351卷

作者： Fei Yu Lei Gao Lixiang Li Shuo Cai Wei Wang Chunhua Wang Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation & School of Computer and Communication Engineering Changsha University of Science and Technology Changsha 410114 China College of Information Science and Engineering Hunan University Changsha 410082 China

In order to provide guidance for the development of high performance millimeter-wave complementary metal oxide semiconductor (MMW-CMOS) integrated circuits (IC), this paper provides a survey of key technologies on MMW-CMOS IC. Technical background of MMW wireless communications is described. Then the recent development of the critical technologies of the MMW-CMOS IC are introduced in detail and compared. A summarization is given, and the development prospects on MMW-CMOS IC are also discussed.

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VideoGIS data retrieval based on multi-feature fusion

VideoGIS data retrieval based on multi-feature fusion

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International Conference on intelligent System and Knowledge Engineering, ISKE

作者： Haihong Dai Bin Hu Qian Cui Zhiqiang Zou College of Computer Nanjing University of Posts and Telecommunications Nanjing Jiangsu China College of Geographic Science Nanjing Normal University Nanjing China Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing Jiangsu China Key Laboratory of Virtual Geographic Environment (Nanjing Normal University) Ministry of Education Nanjing China

With the rapid development of smart cities and the advance of city safety and defense demands, the question that how to accurately discover and retrieve the data that users request from VideoGIS data faces a series of bottleneck problems. VideoGIS data retrieval is one of the important ways to solve above problems. In order to accelerate the rate of feature matching and improve the efficiency of the video retrieval, a new method of VideoGIS data retrieval based on multi-feature fusion is proposed in this paper. The method firstly use video frame difference based on Euclidean distance to extract the key frames under the spatial and temporal sampling of the video. On the basis of this, the global features (e.g. color, shape, texture) are fused by different weighted coefficients, then the feature vector, as the video multi-feature fusion representation, can be constructed by fusing the global features and local features. Based on the multi-feature fusion, correlation between video features is made full use. Compared with the method of single feature and two-feature fusion, the experimental results indicate that the proposed retrieval method has better retrieval effect.

关键词： Feature extraction Image color analysis data mining Correlation Euclidean distance Shape Streaming media

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REPDL: Research-oriented e-learning platform based on digital library

REPDL: Research-oriented e-learning platform based on digita...

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IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)

作者： Xiaolong Xu Kun Wang Yan Deng Tao Li School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Graduate School Nanjing University of Posts and Telecommunications Nanjing China Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China

In accordance with the researchers, students, and faculty' need to use the digital library for efficient literature investigation and knowledge learning, this paper proposes REPDL, a research-oriented e-learning platform based on digital library. REPDL includes the structural literature organization and reading route planning mechanism based on knowledge map, the personalized research progress management, the key information marker & sharing mechanism, and the Fine-grained multi-dimensional cooperative research network and multi-level communication mechanism. The design of REPDL is in accordance with the constructivism-based learning theory. The main target is to further integrate the massive literature resources and the communication channels of digital library, comprehensively use various advanced technologies such as data mining, artificial intelligence, machine learning, visualization technology and social networking, in order to provide the researcher-oriented professional knowledge architecture and the hierarchical literature navigation services to high-level learners, reduce the learners' cognitive load, and effectively prevent disorientation during learning. With REPDL, especially with the automatically personalized manage research progress and the key information marker interface, the literature reading can be more efficient and more satisfy personalized requirements of learners. The researcher cooperative communication network and positioning function of REPDL ensures that learners at different research phases can conduct clearer knowledge communications on multiple levels.

关键词： Conferences Education Knowledge engineering Libraries

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Image representation based on multi-features

Image representation based on multi-features

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International Conference on intelligent System and Knowledge Engineering, ISKE

作者： Xianzhong Long Lei Chen Qun Li College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing Jiangsu China School of Computer Science & Technology Nanjing University of Posts and Telecommunications Nanjing China

As one kind of popular application in computer vision, image clustering has attracted many attentions. Some machine learning algorithms have been widely employed, such as K-Means, Non-negative Matrix Factorization (NMF), Graph regularized Non-negative Matrix Factorization (GNMF) and Locally Consistent Concept Factorization (LCCF). These methods possess respective strength and weakness. The common problem existing in these clustering algorithms is that they only use one kind of feature. However, different kinds of features complement each other and can be used to improve performance results. In this paper, in order to make use of the complementarity between different features, we propose an image representation method based on multi-features. Clustering results on several benchmark image data sets show that the proposed scheme outperforms some classical methods.

关键词： Clustering algorithms Image representation Feature extraction Optimization Symmetric matrices Machine learning algorithms Signal processing algorithms

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A Low-Area Overhead Secure Scan Architecture Resisting Scan-Based Attacks for Crypto Chips

A Low-Area Overhead Secure Scan Architecture Resisting Scan-...

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2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017

作者： Weizheng, Wang Jincheng, Wang Shuo, Cai Peng, Liu Tieqiao, Liu College of Computer and Communication Engineering Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology Changsha Hunan410114 China College of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China College of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China Information Science and Engineering Department Hunan University Changsha410082 China Management School Hangzhou Dianzi University Hangzhou310018 China

ISBN: (纸本)9789881404732

Scan design is a widely used design-for-testability (DFT) technique that improves the controllability and observability of integrated circuits (ICs) resulting in the facilitation of the testing. However, it can also be used to access secret information of crypto chips, and thus threaten dramatically the security of the cipher keys. In this paper, we propose a secure scan DFT architecture to thwart scan-based side-channel attacks. This architecture provides the scan chain reset mechanism, and thus can prevent these attacks based on mode switching. Meanwhile, the secret key is isolated from scan chains of an advanced encryption standard (AES) design in the test mode. Therefore, it can also halt the test-mode-only scan attacks. The proposed secure scan DFT technique ensures the security without compromising the testability of original chip. Most important of all, the secure scan test is implemented with extremely low hardware overhead.

关键词： Design for testability

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Corrigendum to “Manifold Adaptive Kernelized Low-Rank Representation for Semisupervised Image Classification”

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Complexity 2018年第1期2018卷

作者： Yong Peng Wanzeng Kong Feiwei Qin Feiping Nie School of Computer Science Hangzhou Dianzi University Hangzhou 310018 *** Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing 210023 *** Center for OPTical IMagery Analysis and Learning (OPTIMAL) Northwestern Polytechnical University Xi’an 710072 ***

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