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IEEE International Conference on Cyber technology in Automation, Control, and Intelligent Systems

作者： Dinghui Wu Yanjie Zhai Wenzhong Gao Yanxia Shen Zhicheng Ji Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology Jiangnan University Wuxi Jiangsu China Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University Wuxi Jiangsu China Dept. of Electrical and Computer Engineering University of Denver Denver CO USA

ISBN: (纸本)9781479987313

Considering the pitch sensor fault of pitch systems in wind turbines, a multi-innovation observer based fault detection method is proposed. The pitch system can be modeled as a second order differential equation. And then the equation is transformed into a state space model. According to the state space model, a multi-innovation observer is designed to estimate the system state. The pitch sensor fault can be detected through the residual which is generated by comparing the state estimation with the output of an actual system. The simulation results show that the proposed approach is able to detect the pitch sensor fault effectively.

关键词： Wind turbines Observers Fault detection Technological innovation Fault diagnosis Shafts

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Fault-tolerant parallel computing for DEM data blocks with layered dependent relationships based on redundancy mechanism

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International Journal of High Performance Computing and Networking 2015年第4期8卷 337-344页

作者： Dou, Wanfeng Miao, Shoushuai Li, Yan School of Computer Science and Technology Nanjing Normal University Jiangsu Nanjing210023 China Research Center of Information Security and Privacy Technology Jiangsu Nanjing210097 China Virtual Geographic Environment Key Laboratory of the Ministry of Education Nanjing Normal University Jiangsu Nanjing210023 China

The objective of this paper is to build a quantitative method of data partition in parallelisation of digital terrain analysis (DTA) so as to guide the design of algorithms in parallel computing. According to the data-intensive characteristics of the digital elevation model (DEM), a data dependency model is proposed to describe the hierarchical relationships of data blocks. The parallel schedule policies and algorithms for the DEM are built according to the model. With the increase of computing scale in data or tasks, the reliability of the calculation must also be considered in parallel computing. A fault-tolerant parallel computing method is proposed based on the data dependence graph. Respectively, this paper puts forward parallel computing algorithms of two times redundant, three times redundant and partially redundant, with a discussion of their respective advantages. Finally, a visibility algorithm in DTA as an example is used to verify the validity of the strategies and methods. © 2015 Inderscience Enterprises Ltd.

关键词： Data handling

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Fast -norm-based single image blind deblurring: A comparative study 12

Fast -norm-based single image blind deblurring: A comparativ...

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12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015

作者： Shao, Wen-Ze Xie, Shi-Peng Ge, Qi Li, Hai-Bo Huang, Li-Li Wei, Zhi-Hui College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China Jiangsu Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Sci. and Tech. Nanjing210094 China School of Science Guangxi University of Science and Technology Liuzhou545006 China School of Computer Science and Technology Nanjing University of Science and Technology Nanjing210094 China

ISBN: (纸本)9781467376822

Single image blind deblurring has been intensively studied since Fergus et al.'s variational Bayes method in 2006. It is now commonly believed that the blur-kernel estimation accuracy is highly dependent on the pursed salient edge information from the blurred image, which stimulates numerous 0-approximating blind deblurring methods via kinds of techniques and tricks. This paper, however, focuses on the four recent daring attempts which are all based on the simple and direct 0-norm. A systematic comparative analysis is made towards those methods, clarifying their similarities and differences, and providing a benchmark evaluation on both the deblurring quality and computational efficiency. Results have demonstrated that the 0-norm alone is far enough to achieve top blind deblurring performance. Instead, details are to be paid with fairly more attention as working on the problem formulation as well as the algorithmic deduction. Besides, three possible extensions are analyzed on the most leading bi-l0-l2-norm regularization-based blind deblurring method. © 2015 IEEE.

关键词： Computational efficiency

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A feature selection algorithm based on Hoeffding inequality and mutual information

International Journal of Signal Processing, Image Processing...

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International Journal of Signal processing, Image processing and Pattern Recognition 2015年第11期8卷 433-444页

作者： Yin, Chunyong Feng, Lu Ma, Luyu Yin, Zhichao Wang, Jin School of Computer and Software Jiangsu Key Laboratory of Meteorological Observation and Information Processing Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China Nanjing No.1 Middle School Nanjing China

With the rapid development of the Internet, the application of data mining in the Internet is becoming more and more extensive. However, the data source’s complex feature redundancy leads that data mining process becomes very inefficient and complex. So feature selection research is essential to make data mining more efficient and simple. In this paper, we propose a new way to measure the correlation degree of internal features of dataset which is a mutation of mutual information. Additionally we also introduce Hoeffding inequality as constraint of constructing algorithm. During the experiments, we use C4.5 classification algorithm as test algorithm and compare HSF with BIF(feature selection algorithm based on mutual information). Experiments results show that HSF performances better than BIF[1] in TP and FP rate, what’s more the feature subset obtained by HSF can significantly improve the TP, FP and memory usage of C4.5 classification algorithm. © 2015 SERSC.

关键词： Feature Selection

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Deep Label Distribution Learning for Apparent Age Estimation

Deep Label Distribution Learning for Apparent Age Estimation

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International Conference on computer Vision Workshops (ICCV Workshops)

作者： Xu Yang Bin-Bin Gao Chao Xing Zeng-Wei Huo Xiu-Shen Wei Ying Zhou Jianxin Wu Xin Geng School of Computer Science and Engineering Southeast University Nanjing China Key Laboratory of Computer Network and Information Integration Ministry of Education China National Key Laboratory for Novel Software Technology Nanjing University Nanjing China Southeast University Nanjing Jiangsu CN

In the age estimation competition organized by ChaLearn, apparent ages of images are provided. Uncertainty of each apparent age is induced because each image is labeled by multiple individuals. Such uncertainty makes this age estimation task different from common chronological age estimation tasks. In this paper, we propose a method using deep CNN (Convolutional Neural Network) with distribution-based loss functions. Using distributions as the training tasks can exploit the uncertainty induced by manual labeling to learn a better model than using ages as the target. To the best of our knowledge, this is one of the first attempts to use the distribution as the target of deep learning. In our method, two kinds of deep CNN models are built with different architectures. After pre-training each deep CNN model with different datasets as one corresponding stream, the competition dataset is then used to fine-tune both deep CNN models. Moreover, we fuse the results of two streams as the final predicted ages. In the final testing dataset provided by competition, the age estimation performance of our method is 0.3057, which is significantly better than the human-level performance (0.34) provided by the competition organizers.

关键词： Face Estimation Streaming media Training Hidden Markov models Uncertainty Standards

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An evolution-based robust social influence evaluation method in Online Social Networks

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8787卷 141-157页

作者： Zhu, Feng Liu, Guanfeng Liu, An Zhao, Lei Zhou, Xiaofang School of Computer Science and Technology Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China School of Information Technology and Electrical Engineering University of Queensland Brisbane4072 Australia

Online Social Networks (OSNs) are becoming popular and attracting lots of participants. In OSN based e-commerce platforms, a buyer’s review of a product is one of the most important factors for other buyers’ decision makings. A buyer who provides high quality reviews thus has strong social influence, and can impact a large number of participants’ purchase behaviours in OSNs. However, the dishonest participants can cheat the existing social influence evaluation models by using some typical attacks, like Constant and Camouflage, to obtain fake strong social influence. Therefore, it is significant to accurately evaluate such social influence to recommend the participants who have strong social influences and provide high quality product reviews. In this paper, we propose an Evolutionary-Based Robust Social Influence (EB-RSI) method based on the trust evolutionary models. In our EB-RSI, we propose four influence impact factors in social influence evaluation, i.e., Total Trustworthiness (TT), Fluctuant Trend of Being Advisor (FTBA), Fluctuant Trend of Trustworthiness (FTT) and Trustworthiness Area (TA). They are all significant in the influence evaluation. We conduct experiments onto a real social network dataset Epinions, and validate the effectiveness and robustness of our EB-RSI by comparing with state-of-the-art method, SoCap. The experimental results demonstrate that our EB-RSI can more accurately evaluate participants’ social influence than SoCap. © Springer International Publishing Switzerland 2014.

关键词： Social networking (online)

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Defense technology of Wormhole Attacks Based on Node Connectivity

Defense Technology of Wormhole Attacks Based on Node Connect...

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IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity)

作者： Jiu-hu Zheng Huan-yan Qian Lei Wang School of Information Technology Jiangsu Institute of Commerce Nanjing Jiangsu China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing Jiangsu China National Mobile Communications esearch Laboratory Southeast University Nanjing Jiangsu China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing Jiangsu China

ISBN: (纸本)9781509018949

After wormhole attacks the routing mechanism of wireless sensor network (WSN) is damaged, then the hop count and distance between nodes cannot be well matched, so that the WSN becomes the anisotropic sensor network, resulting in security treats for WSN. Considering that wormhole attacks can cause the changing of node connectivity, through the theoretical analysis and derivation, the paper has proposed a method which detects wormhole attacks with the connected relation of high connectivity nodes, and optimizes routing with the help of the normal nodes outside the wormhole. Simulation results show that the algorithm can well detect wormhole attacks and has better localization accuracy In addition, the effect is more obvious in the case of the wormhole nodes with large communication radius and long distance.

关键词： Wireless sensor networks Routing Probability Algorithm design and analysis Security Simulation computer science

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An improved DV-Hop positioning algorithm for wireless sensor network

An improved DV-Hop positioning algorithm for wireless sensor...

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

作者： Jiuhu Zheng Huanyan Qian Lie Wang School of Information Technology Jiangsu Institute of Commerce Nanjing Jiangsu China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing Jiangsu China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing Nanjing Jiangsu China National Mobile Communications esearch Laboratory Southeast University Nanjing Jiangsu China Ministry of Education Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications) Nanjing Jiangsu China

In the view of the DV-Hop positioning algorithm which relies on the distance vector and beacon nodes, several aspects are improved: the average hop distance and hop count are corrected; a method to detect the abnormal distribution of beacon nodes is used to avoid the influence of the abnormal distribution on the positioning performance. The proposed algorithm is simple and effective. Simulation results show that compared with the traditional DV-Hop algorithm, the performance of the proposed algorithm is greatly improved. The performance is even even superior to that of the algorithm mentioned in literature [10].

关键词： Wireless sensor networks Mobile communication Hardware Maximum likelihood estimation Mathematical model computer science Broadband communication

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Ranking based activity trajectory search

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8786卷 170-185页

作者： Chen, Wei Zhao, Lei Jiajie, Xu Zheng, Kai Zhou, Xiaofang School of Computer Science and Technology Soochow University China Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University China School of ITEE The University of Queensland Brisbane Australia

With the proliferation of the GPS-enabled devices and mobile techniques, there has been a lot of work on trajectory search in the last decade. Previous trajectory search has focused on spatio-temporal features and text descriptions. Different from them, we study a novel problem of searching trajectories with activities and corresponding ranking information. Given a query q, which is attached with a set of activities and a threshold of distance, the results of ranking based activity trajectory search (RTS) are k trajectories such that the given activities are performed with the highest ranking within the threshold of distance. In addition, we also extend the query with an order, i.e., order-sensitive ranking based activity trajectory search (ORTS), which takes both the order of activities in a query q and the order of trajectories into account. It is challenging to answer RTS and ORTS efficiently due to the structural complexity of trajectory data with ranking information. In this paper, a hybrid index AC-tree and its optimized variant RAC-tree are proposed to achieve higher efficiency. Extensive experiments verify the high efficiency and scalability of the proposed algorithms. © Springer International Publishing Switzerland 2014.

关键词： Trajectories

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Erratum to: Search for supersymmetry in final states with two same-sign or three leptons and jets using 36 fb−1 of = 13 TeV pp collision data with the ATLAS detector

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Journal of High Energy Physics 2019年第8期2019卷 1-19页

作者： Aaboud, M. Aad, G. Abbott, B. Abdinov, O. Abeloos, B. Abidi, S. H. AbouZeid, O. S. Abraham, N. L. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B. S. Adachi, S. Adamczyk, L. Adelman, J. Adersberger, M. Adye, T. Affolder, A. A. Afik, Y. Agatonovic-Jovin, T. Agheorghiesei, C. Aguilar-Saavedra, J. A. Ahlen, S. P. Ahmadov, F. Aielli, G. Akatsuka, S. Akerstedt, H. Åkesson, T. P. A. Akilli, E. Akimov, A. V. Alberghi, G. L. Albert, J. Albicocco, P. Alconada Verzini, M. J. Alderweireldt, S. C. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Ali, B. Aliev, M. Alimonti, G. Alison, J. Alkire, S. P. Allbrooke, B. M. M. Allen, B. W. Allport, P. P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A. A. Alstaty, M. I. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M. G. Amadio, B. T. Amaral Coutinho, Y. Amelung, C. Amidei, D. Amor Dos Santos, S. P. Amoroso, S. Amundsen, G. Anastopoulos, C. Ancu, L. S. Andari, N. Andeen, T. Anders, C. F. Anders, J. K. Anderson, K. J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Angerami, A. Anisenkov, A. V. Anjos, N. Annovi, A. Antel, C. Antonelli, M. Antonov, A. Antrim, D. J. Anulli, F. Aoki, M. Aperio Bella, L. Arabidze, G. Arai, Y. Araque, J. P. Araujo Ferraz, V. Arce, A. T. H. Ardell, R. E. Arduh, F. A. Arguin, J-F. Argyropoulos, S. Arik, M. Armbruster, A. J. Armitage, L. J. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Ashkenazi, A. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N. B. Augsten, K. Avolio, G. Axen, B. Ayoub, M. K. Azuelos, G. Baas, A. E. Baca, M. J. Bachacou, H. Bachas, K. Backes, M. Bagnaia, P. Bahmani, M. Bahrasemani, H. Baines, J. T. Bajic, M. Baker, O. K. Baldin, E. M. Balek, P. Balli, F. Balunas, W. K. Banas, E. Bandyopadhyay, A. Banerjee, Sw. Bannoura, A. A. E. Barak, L. Barberio, E. L. Barberis, D. Barbero, M. Barillari, T. Barisits, M-S Barkeloo, J. T. Barklow, T. Barlow, N. Barnes, S. L. Barnett, B. M. Barnett, R. M. Barnovska-Blenessy, Z Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman U.S.A. Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Department of Physics University of Toronto Toronto Canada Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz U.S.A. Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel Center for High Energy Physics University of Oregon Eugene U.S.A. Department of Physics Stockholm University Stockholm Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Udine Italy ICTP Trieste Italy Department of Physics King’s College London London United Kingdom International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb U.S.A. Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Institute of Physics University of Belgrade Belgrade Serbia Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física Experimental de Partículas – LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos Universidad de Granada Granada Portugal Department of Physics Boston University Boston U.S.A. Joint Institute for Nuclear Research JINR Dubna Dubna Russia INFN Sezione di Roma Tor Vergata Roma Italy Dip

One correction is made to the figure 4e of the paper.

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