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4th ACM International Workshop on Security in Cloud Computing, SCC 2016

作者： Mao, Yunlong Zhang, Yuan State Key Laboratory for Novel Software Technology Nanjing University Computer Science and Technology Department Nanjing210046 China

ISBN: (纸本)9781450342858

In this paper, we propose a privacy-preserving algorithm for two-party distributed permutation test for the difference of means. Our algorithm allows two parties to jointly perform a permutation test on the union of their data without revealing their data to each other. Our algorithm is useful especially in areas where the testing data often contains private information e.g. clinic trial and biomedical research. We have proved the security of our algorithm and used experiment to show its efficiency. To the best of our knowledge, we are the first to address the privacy issues in permutation tests. © 2016 ACM.

关键词： Bioinformatics

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Random asynchronous iterations in distributed coordination algorithms

arXiv

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arXiv 2018年

作者： Chen, Yao Xia, Weiguo Cao, Ming Lü, Jinhu Department of Computer Science Southwestern University of Finance and Economics Chengdu611130 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China Faculty of Science and Engineering ENTEG University of Groningen Groningen9747 AG Netherlands School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

Distributed coordination algorithms (DCA) carry out information processing processes among a group of networked agents without centralized information fusion. Though it is well known that DCA characterized by an SIA (stochastic, indecomposable, aperiodic) matrix generate consensus asymptotically via synchronous iterations, the dynamics of DCA with asynchronous iterations have not been studied extensively, especially when viewed as stochastic processes. This paper aims to show that for any given irreducible stochastic matrix, even non-SIA, the corresponding DCA lead to consensus successfully via random asynchronous iterations under a wide range of conditions on the transition probability. Particularly, the transition probability is neither required to be independent and identically distributed, nor characterized by a Markov chain. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

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A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

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Computing and software for Big science 2020年第1期4卷 1-20页

作者： Sirunyan, A.M. Tumasyan, A. Adam, W. Ambrogi, F. Bergauer, T. Dragicevic, M. Erö, J. Valle, A. Escalante Del Flechl, M. Frühwirth, R. Jeitler, M. Krammer, N. Krätschmer, I. Liko, D. Madlener, T. Mikulec, I. Rad, N. Schieck, J. Schöfbeck, R. Spanring, M. Spitzbart, D. Waltenberger, W. Wulz, C.-E. Zarucki, M. Drugakov, V. Mossolov, V. Gonzalez, J. Suarez Darwish, M.R. De Wolf, E.A. Croce, D. Di Janssen, X. Lelek, A. Pieters, M. Sfar, H. Rejeb Haevermaet, H. Van Mechelen, P. Van Putte, S. Van Remortel, N. Van Blekman, F. Bols, E.S. Chhibra, S.S. D’Hondt, J. De Clercq, J. Lontkovskyi, D. Lowette, S. Marchesini, I. Moortgat, S. Python, Q. Skovpen, K. Tavernier, S. Doninck, W. Van Mulders, P. Van Beghin, D. Bilin, B. Clerbaux, B. De Lentdecker, G. Delannoy, H. Dorney, B. Favart, L. Grebenyuk, A. Kalsi, A.K. Popov, A. Postiau, N. Starling, E. Thomas, L. Velde, C. Vander Vanlaer, P. Vannerom, D. Cornelis, T. Dobur, D. Khvastunov, I. Niedziela, M. Roskas, C. Tytgat, M. Verbeke, W. Vermassen, B. Vit, M. Bondu, O. Bruno, G. Caputo, C. David, P. Delaere, C. Delcourt, M. Giammanco, A. Lemaitre, V. Prisciandaro, J. Saggio, A. Marono, M. Vidal Vischia, P. Zobec, J. Alves, F.L. Alves, G.A. Silva, G. Correia Hensel, C. Moraes, A. Teles, P. Rebello Chagas, E. Belchior Batista Das Carvalho, W. Chinellato, J. Coelho, E. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. De Oliveira Martins, C. De Souza, S. Fonseca Guativa, L. M. Huertas Malbouisson, H. Martins, J. Figueiredo, D. Matos Jaime, M. Medina De Almeida, M. Melo Herrera, C. Mora Mundim, L. Nogima, H. Da Silva, W. L. Prado Rosas, L. J. Sanchez Santoro, A. Sznajder, A. Thiel, M. Manganote, E. J. Tonelli Da Silva De Araujo, F. Torres Pereira, A. Vilela Bernardes, C.A. Calligaris, L. Tomei, T. R. Fernandez Perez Gregores, E.M. Lemos, D.S. Mercadante, P.G. Novaes, S.F. Padula, SandraS. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Rodozov, M. Shopova, M. Sultanov, G. Bonchev, M. Dimitrov, A. Ivanov, T. Litov, L. Pavlov, B. Petkov, P. Fang, W. Gao, X. Yuan, Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Wien Austria Institute for Nuclear Problems Minsk Belarus Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Zhejiang University Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics University of Helsinki Helsinki Finland Helsinki Institute of Physics Helsinki Finland Lappeenranta University of Technology Lappeenranta Finland IRFU CEA Université Paris-Saclay Gif-sur-Yvette France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France Université de Strasbourg CNRS IPH

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton–proton collisions at an energy of s=13TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb-1. A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯. © 2020, The Author(s).

关键词： b jets CMS Deep learning Higgs boson Jet energy Jet resolution

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Glucose Screening Measurements and Noninvasive Glucose Monitor Methods

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Procedia computer science 2018年 139卷 613-621页

作者： Hui Zheng Jing He Peng Li Mengjiao Guo Hui Jin Jie Shen Zhijun Xie Chihung Chi School of Software and Electrical Engineering Swinburne University of Technology Melbourne Australia School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China North China Institute of Aerospace Engineering Hebei China College of Information Engineering Nanjing University of Finance and Economics China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Jiangsu Province Nanjing China Endocrinology Department Zhongda Hospital Southeast University Nanjing Jiangsu China Endocrinology Department The Third Affiliated Hospital of Southern Medical University Guangzhou Guangdong China Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo Zhejiang Province China Commonwealth Scientific and Industrial Research Organisation (CSIRO) Tasmania Australia

Diabetes alone does not affect the health, but its complications always bring danger to people’s health. To avoid the development of diabetes and posterior to discover diabetes, checking blood glucose level is an effective way. The development of glucose screening measurements is introduced. Non-invasive glucose monitor methods, as accurate, safe, convenient and comfortable methods, are also illustrated and compared in this paper. Also, an Intelligent dynamic health inspection is designed with a proposed non-invasion glucose monitor measurement.

关键词： diabetes blood glucose screening noninvasive methods

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FlowTrace： measuring round-trip time and tracing path in software-defined networking with low communication overhead

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Frontiers of Information technology & Electronic Engineering 2017年第2期18卷 206-219页

作者： Shuo WANG Jiao ZHANG Tao HUANG Jiang LIU Yun-jie LIU F. Richard YU State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing 100876 China Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory Shijiazhuang 050081 China Beijing Advanced Innovation Center for Future Internet Technology Beijing University of Technology Beijing 100124 China Department of Systems and Computer Engineering Carleton University Ottawa ON KIS 5B6 Canada

：In today＇s networks, load balancing and priority queues in switches are used to support various quality-of-service （QoS） features and provide preferential treatment to certain types of traffic. Traditionally, network operators use ‘traceroute＇ and ‘ping＇ to troubleshoot load balancing and QoS problems. However, these tools are not supported by the common OpenFlow-based switches in software-defined networking （SDN）. In addition, traceroute and ping have potential problems. Because load balancing mechanisms balance flows to different paths, it is impossible for these tools to send a single type of probe packet to find the forwarding paths of flows and measure latencies. Therefore, tracing flows＇ real forwarding paths is needed before measuring their latencies, and path tracing and latency measurement should be jointly considered. To this end, FlowTrace is proposed to find arbitrary flow paths and measure flow latencies in OpenFlow networks. FlowTrace collects all flow entries and calculates flow paths according to the collected flow entries. However, polling flow entries from switches will induce high overhead in the control plane of SDN. Therefore, a passive flow table collecting method with zero control plane overhead is proposed to address this problem. After finding flows＇ real forwarding paths, FlowTrace uses a new measurement method to measure the latencies of different flows. Results of experiments conducted in Mininet indicate that FlowTrace can correctly find flow paths and accurately measure the latencies of flows in different priority classes.

关键词： software-defined networking Network monitoring Traceroute

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Testing as an investment

arXiv

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arXiv 2017年

作者： Xu, Xiaoran Fang, Chunrong Chen, Zhenyu State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Software Institute Nanjing University Nanjing China Computer Science Department Rice University HoustonTX United States

software testing is an expensive and important task. Plenty of researches and industrial efforts have been invested on improving software testing techniques, including criteria, tools, etc. These studies can provide guidelines to select suitable test techniques for software engineers. However, in some engineering projects, business issues may be more important than technical ones, hence we need to lobby non-technical members to support our decisions. In this paper, a well-known investment model, Nelson-Siegel model, is introduced to evaluate and forecast the processes of testing with different testing criteria. Through this model, we provide a new perspective to understand short-term, medium-term, and long-term returns of investments throughout the process of testing. A preliminary experiment is conducted to investigate three testing criteria from the viewpoint of investments. The results show that statement-coverage criterion performs best in gaining long-term yields;the short-term and medium-term yields of testing depend on the scale of programs and the number of faults they contain. Copyright © 2017, The Authors. All rights reserved.

关键词： Investments

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Towards a semantic keyword search over industrial knowledge graphs (extended abstract)

Towards a semantic keyword search over industrial knowledge ...

引用

IEEE International Conference on Big Data

作者： Gong Cheng Evgeny Kharlamov National Key Laboratory for Novel Software Technology Nanjing University Nanjing China Department of Computer Science University of Oxford Oxford United Kingdom

Knowlege graphs have become powerful assets for enhancing search and data integration and are now widely used in both academia and industry. Existing semantics of keyword search over knowledge graphs, especially in industrial context, has limitations. In this extended abstract we discuss these limitations and ingredients for alternative semantics.

关键词： Semantics keyword search Syntactics Ontologies Oils Resource description framework

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Feature learning based deep supervised hashing with pairwise labels 25

Feature learning based deep supervised hashing with pairwise...

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25th International Joint Conference on Artificial Intelligence, IJCAI 2016

作者： Li, Wu-Jun Wang, Sheng Kang, Wang-Cheng National Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University China

Recent years have witnessed wide application of hashing for large-scale image retrieval. However, most existing hashing methods are based on handcrafted features which might not be optimally compatible with the hashing procedure. Recently, deep hashing methods have been proposed to perform simultaneous feature learning and hash-code learning with deep neural networks, which have shown better performance than traditional hashing methods with hand-crafted features. Most of these deep hashing methods are supervised whose supervised information is given with triplet labels. For another common application scenario with pairwise labels, there have not existed methods for simultaneous feature learning and hash-code learning. In this paper, we propose a novel deep hashing method, called deep pairwise-supervised hashing (DPSH), to perform simultaneous feature learning and hashcode learning for applications with pairwise labels. Experiments on real datasets show that our DPSH method can outperform other methods to achieve the state-of-the-art performance in image retrieval applications.

关键词： Image retrieval

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Integrating reviews into personalized ranking for cold start recommendation

arXiv

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arXiv 2017年

作者： Hu, Guang-Neng Dai, Xin-Yu Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong National Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China

Item recommendation task predicts a personalized ranking over a set of items for each individual user. One paradigm is the rating-based methods that concentrate on explicit feedbacks and hence face the difficulties in collecting them. Meanwhile, the ranking-based methods are presented with rated items and then rank the rated above the unrated. This paradigm takes advantage of widely available implicit feedback. It, however, usually ignores a kind of important information: item reviews. Item reviews not only justify the preferences of users, but also help alleviate the cold-start problem that fails the collaborative filtering. In this paper, we propose two novel and simple models to integrate item reviews into Bayesian personalized ranking. In each model, we make use of text features extracted from item reviews using word embeddings. On top of text features we uncover the review dimensions that explain the variation in users' feedback and these review factors represent a prior preference of users. Experiments on six real-world data sets show the benefits of leveraging item reviews on ranking prediction. We also conduct analyses to understand the proposed models. Copyright © 2017, The Authors. All rights reserved.

关键词： Collaborative filtering

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Short-Term Wind Power Forecast for Wind Farm Base on Artificial Neural Network

Short-Term Wind Power Forecast for Wind Farm Base on Artific...

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International Conference on computer technology, Electronics and Communication (ICCTEC)

作者： Feiyan Wu Xianwen Liao Guangxi Colleges and Universities Key Laboratory of Professional Software Technology Wuzhou University Wuzhou Technology Department of Computer Science The Beihai Campus of the Guilin University of Electronic Beihai China

ISBN: (纸本)9781538657850

Wind power forecasting is a critical method in minimizing the impact caused by integrated power grids. Firstly, the general steps of the establishment of neural network based load forecasting model for wind farm are presented and the principles are introduced. Next, in an example of a wind farm, the paper focuses on the relationship of weather data and output power by analyzing this relationship. A number of factors having significant impact on the output power are selected and used as network input. This network is an excellent predictive model which has been proved high prediction accuracy in experiments.

关键词： Generators Wind power generation Wind farms Wind speed Wind forecasting

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