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Online Robust Lagrangian Support Vector Machine against Adversarial Attack

Procedia Computer Science 2018年 139卷 173-181页

作者： Yue Ma Yiwei He Yingjie Tian School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 100049 China Key Laboratory of Big Data Mining and Knowledge management Beijing 100190 China School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China

In adversarial environment such as intrusion detection and spam filtering, the adversary-intruder or spam advertiser may attempt to produce contaminate training instance and manipulate the learning of classifier. In order to keep good classification performance, many robuster learning methods have been proposed to deal with the adversarial attack. Support Vector Machines(SVMs) is a kind of successful approach in the adversarial classification tasks and the investigation of robust SVMs is very popular. However, in many real application, the data including stain instance is coming dynamically. Batch learning which needs retraining when encountering new samples, will consume more computing resources. In this paper, we propose a robust Lagrangian support vector machine (RLSVM) with modified kernel matrix and explore the online learning algorithm on it. The experimental results show the robustness of RLSVM against label noise produced by adversaries under the online adversarial environment.

关键词： adversarial attack poison attack label noise online learning Lagrangian SVM

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The effect of differential temperatures on the latent heat in the nucleation of CdSe quantum dots

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Journal of Semiconductors 2017年第4期38卷 14-17页

作者： Licai Hao Zhongchen Bai Shuijie Qin Zhengping Zhang College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China Guizhou Province Key Laboratory for Photoelectric Technology and Application Guizhou UniversityGuiyang 550025China

This work studied the effect of differential temperatures on the latent heat in the nucleation of CdSe quantum dots（QDs）.The result showed that,by the formula of phase change,with increasing the reaction temperature,the latent heat in the nucleation of QDs *** QDs with the size-dispersion from 2.7 to 3.6 nm were synthesized via oleic acid-paraffin liquid system by controlling the reaction temperature from 180 to 220℃.Synthesized QDs were characterized by UV-vis absorption spectra and X-ray diffraction（XRD）.The result of UV-vis absorption spectra showed that with increasing of reaction temperature,the first absorption peak was red-shifted and the size of QD *** result of XRD showed that the synthesized QDs were zinc-blende structure.

关键词： latent heat CdSe quantum dots phase change zinc-blende structure

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Visual tracking via Boolean map representations

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Pattern Recognition 2018年 81卷 147-160页

作者： Kaihua Zhang Qingshan Liu Jian Yang Ming-Hsuan Yang Jiangsu Key Laboratory of Big Data Analysis Technology Nanjing University of Information Science and Technology Nanjing China The School of Computer Science and Engineering Nanjing University of Science and Technology China Electrical Engineering and Computer Science University of California Merced CA 95344 United States

In this paper, we present a simple yet effective Boolean map based representation that exploits connectivity cues for visual tracking. We describe a target object with histogram of oriented gradients and raw color features, of which each one is characterized by a set of Boolean maps generated by uniformly thresholding their values. The Boolean maps effectively encode multi-scale connectivity cues of the target with different granularities. The fine-grained Boolean maps capture spatially structural details that are effective for precise target localization while the coarse-grained ones encode global shape information that are robust to large target appearance variations. Finally, all the Boolean maps form together a robust representation that can be approximated by an explicit feature map of the intersection kernel, which is fed into a logistic regression classifier with online update, and the target location is estimated within a particle filter framework. The proposed representation scheme is computationally efficient and facilitates achieving favorable performance in terms of accuracy and robustness against the state-of-the-art tracking methods on the OTB50 and VOT2016 benchmark datasets.

关键词： Visual tracking Boolean map Logistic regression Intersection kernel

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A holistic approach to aligning geospatial data with multidimensional similarity measuring

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International Journal of Digital Earth 2018年第8期11卷 845-862页

作者： Li Yu Peiyuan Qiu Xiliang Liu Feng Lu Bo Wan State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingPeople’s Republic of China National Science Library Chinese Academy of SciencesBeijingPeople’s Republic of China Fujian Collaborative Innovation Center for Big Data Applications in Governments FuzhouPeople’s Republic of China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application NanjingPeople’s Republic of China Faculty of Information Engineering China University of GeosciencesWuhanPeople’s Republic of China

Semantically aligning the heterogeneous geospatial datasets(GDs)produced by different organizations demands efficient similarity matching ***,the strategies employed to align the schema(concept and property)and instances are usually not reusable,and the effects of unbalanced information tend to be neglected in GD *** solve this problem,a holistic approach is presented in this paper to integrally align the geospatial entities(concepts,properties and instances)***,lexical,structural and extensional similarity metrics are designed and automatically aggregated by means of approval *** presented approach is validated with real geographical semantic webs,Geonames and *** with the well-known extensional-based aligning system,the presented approach not only considers more information involved in GD alignment,but also avoids the artificial parameter setting in metric *** reduces the dependency on specific information,and makes the alignment more robust under the unbalanced distribution of various information.

关键词： Geospatial data data alignment similarity matching semantic web

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Real-Time Fine-Grained Air Quality Sensing Networks in Smart City: Design, Implementation and Optimization

arXiv

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arXiv 2018年

作者： Hu, Zhiwen Bai, Zixuan Bian, Kaigui Wang, Tao Song, Lingyang National Engineering Laboratory for Big Data Analysis and Applications School of Electronics Engineering and Computer Science Peking University Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing China

—Driven by the increasingly serious air pollution problem, the monitoring of air quality has gained much attention in both theoretical studies and practical implementations. In this paper, we present the architecture, implementation and optimization of our own air quality sensing system, which provides real-time and fine-grained air quality map of the monitored area. As the major component, the optimization problem of our system is studied in detail. Our objective is to minimize the average joint error of the established real-time air quality map, which involves data inference for the unmeasured data values. A deep Q-learning solution has been proposed for the power control problem to reasonably plan the sensing tasks of the power-limited sensing devices online. A genetic algorithm has been designed for the location selection problem to efficiently find the suitable locations to deploy limited number of sensing devices. The performance of the proposed solutions are evaluated by simulations, showing a significant performance gain when adopting both strategies. Copyright © 2018, The Authors. All rights reserved.

关键词： Reinforcement learning

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Research on the motivation to contribution and influencing factors of university students——a semi-structured interview based on qualitative research

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IOP Conference Series: Materials Science and engineering 2019年第5期563卷

作者： Yueyao Li Sanhong Deng Yue Zhang School of Information Management Nanjing University Nanjing 210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing University Nanjing 210023 China

Due to the lack of theoretical knowledge and practical experience, the university students have many deficiencies in contribution. We conducted semi-structured interviews with 28 undergraduate and postgraduate students of Nanjing Agricultural University. At the same time, we used descriptive statistics and cross-analysis methods to analyse the motivations of college students' initial contribution and the influencing factor of their choice. Based on this, this paper puts forward some suggestions for the initial submission of college students, and the journals are also provided for reference in the selection of manuscripts.

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Polarization-multiplexed, dual-comb all-fiber mode-locked laser

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Photonics Research 2018年第9期6卷 853-857页

作者： XIN ZHAO TING LI YA LIU QIAN LI ZHENG ZHENG School of Electronic and Information Engineering Beihang University Yunnan Key Laboratory of Opto-Electronic Information Technology School of Physics and Electronic Information TechnologyYunnan Normal University Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang University Collaborative Innovation Center of Geospatial Technology

Mode-locked fiber lasers that can simultaneously generate two asynchronous ultrashort pulse trains could play an attractive role as the alternative light sources for low-complexity dual-comb metrology applications. Although a few multiplexing schemes to realize such lasers have been proposed and demonstrated, here we investigate the lasing characteristics of a passively mode-locked fiber laser with a finite amount of intracavity birefringence. By introducing a section of polarization-maintaining(PM) fiber into the otherwise-non-PM-single-mode cavity, dual asynchronous pulses with nearly orthogonal states of polarization are generated. With a repetition rate difference of hundreds of hertz, the pulses have well-overlapped spectra and show typical features of polarization-locked vector solitons. It is demonstrated that under an anomalous or net normal dispersion regime, either dual vector solitons or dual dissipative vector solitons can be generated, respectively. Such polarization-multiplexed single single-cavity dual-comb lasers could find further uses in various applications in need of simple dual-comb system solutions.

关键词： Polarization-multiplexed dual-comb all-fiber mode-locked laser

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Multi-Dimension Training Scheme to Improve the Innovation Capacity of Postgraduate and Undergraduate Students Collaboratively

Multi-Dimension Training Scheme to Improve the Innovation Ca...

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Frontiers in Education (FIE) Conference

作者： Xiaolong Xu Jianhua Shen Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China College of Communication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781538611753;9781538611746

This Innovative Practice Work in Progress Paper presents a multi-dimension training scheme to improve the innovation capacity of postgraduate and undergraduate students collaboratively. The current training of postgraduate and undergraduate education schemes cannot form a mutually beneficial relation, not suitable for the training of innovation capacity on postgraduate and undergraduate students collaboratively. There are various problems that need to be addressed. The main strategy of the proposed scheme is utilizing real research programs to establish an integrated team mixed with both postgraduate and undergraduate students, focusing on stimulating their innovation capacity in scientific research. In the scheme, we designed a multi-level joint training mechanism based on the mixed pedagogy, the collaborative resource pool platform, the multi-role and team-based innovation talent incubation mechanism, and the preparatory postgraduate student selection and training goal achievement evaluation mechanism. We applied the scheme to the training process of postgraduate students from the majors of Software engineering, Computer Software and Theory, Computer Application, Computer Technology and Electronic Information engineering, and undergraduate students from the majors of Computer Science and Technology, Information Security and Communication engineering in Nanjing University of Posts and Telecommunications. The training results approve the feasibility and effectiveness of the scheme.

关键词： Training Technological innovation Collaboration Software Telecommunications Business

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Strict pattern matching under non-overlapping condition

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Science China(Information Sciences) 2017年第1期60卷 5-20页

作者： Youxi WU Cong SHEN He JIANG Xindong WU School of Computer Science and Engineering Hebei University of Technology Hebei Province Key Laboratory of Big Data Calculation School of Computer Science and Technology Tianjin University School of Software Dalian University of Technology School of Computer Science and Information Engineering Hefei University of Technology School of Computing and Informatics University of Louisiana at Lafayette

Pattern matching(or string matching) is an essential task in computer science, especially in sequential pattern mining, since pattern matching methods can be used to calculate the support(or the number of occurrences) of a pattern and then to determine whether the pattern is frequent or not. A state-of-the-art sequential pattern mining with gap constraints(or flexible wildcards) uses the number of non-overlapping occurrences to denote the frequency of a pattern. Non-overlapping means that any two occurrences cannot use the same character of the sequence at the same position of the pattern. In this paper, we investigate strict pattern matching under the non-overlapping condition. We show that the problem is in P at first. Then we propose an algorithm, called NETLAP-Best, which uses Nettree structure. NETLAP-Best transforms the pattern matching problem into a Nettree and iterates to find the rightmost root-leaf path, to prune the useless nodes in the Nettree after removing the rightmost root-leaf path. We show that NETLAP-Best is a complete algorithm and analyse the time and space complexities of the algorithm. Extensive experimental results demonstrate the correctness and efficiency of NETLAP-Best.

关键词： pattern matching sequential pattern mining gap constraint flexible wildcard non-overlapping occurrence Nettree

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Research on Influencing Factors of College Students' Intention of Online Health Information Behavior Based on Social Cognitive Theory

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Journal of Physics: Conference Series 2019年第2期1213卷

作者： Jia Kong Sanhong Deng Yue Zhang School of Information Management Nanjing University Nanjing 210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing University Nanjing 210023 China

Based on the Social Cognition Theory, we constructed the influencing factors model of college students' intention of online health information behavior from three levels of individual, society and information systems, which was analyzed by using the PLS-SEM. Research shows that self-efficacy, information service quality, social support, information literacy and information quality significantly influence college students' intention of online health information behavior. However, the influence of perceived risk and information system quality is not significant.

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