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arXiv 2018年

作者： Watts, Anna L. Yu, Wenfei Poutanen, Juri Zhang, Shu Bhattacharyya, Sudip Bogdanov, Slavko Ji, Long Patruno, Alessandro Riley, Thomas E. Bakala, Pavel Baykal, Altan Bernardini, Federico Bombaci, Ignazio Brown, Edward Cavecchi, Yuri Chakrabarty, Deepto Chenevez, Jérôme Degenaar, Nathalie Santo, Melania Del Salvo, Tiziana Di Doroshenko, Victor Falanga, Maurizio Ferdman, Robert D. Feroci, Marco Gambino, Angelo F. Ge, MingYu Greif, Svenja K. Guillot, Sebastien Gungor, Can Hartmann, Dieter H. Hebeler, Kai Heger, Alexander Homan, Jeroen Iaria, Rosario in’t Zand, Jean Kargaltsev, Oleg Kurkela, Aleksi Lai, Xiaoyu Li, Ang Li, XiangDong Li, Zhaosheng Linares, Manuel Lu, FangJun Mahmoodifar, Simin Méndez, Mariano Miller, M. Coleman Morsink, Sharon Nättilä, Joonas Possenti, Andrea Prescod-Weinstein, Chanda Qu, JinLu Riggio, Alessandro Salmi, Tuomo Sanna, Andrea Santangelo, Andrea Schatz, Hendrik Schwenk, Achim Song, LiMing Šrámková, Eva Stappers, Benjamin Stiele, Holger Strohmayer, Tod Tews, Ingo Tolos, Laura Török, Gabriel Tsang, David Urbanec, Martin Vacchi, Andrea Xu, RenXin Xu, Ypeng Zane, Silvia Zhang, Guobao Zhang, ShuangNan Zhang, Wenda Zheng, ShiJie Zhou, Xia Anton Pannekoek Institute for Astronomy University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Shanghai Astronomical Observatory Shanghai200030 China Tuorla Observatory Department of Physics and Astronomy University of Turku Väisäläntie 20 PiikkiöFIN-21500 Finland Nordita KTH Royal Institute of Technology Stockholm University Roslagstullsbacken 23 StockholmSE-10691 Sweden Institute of High Energy Physics CAS Beijing100049 China Tata Institute of Fundamental Research Mumbai400005 India Columbia Astrophysics Laboratory Columbia University 550 West 120th Street New YorkNY10027 United States Institut für Astronomie und Astrophysik Tübingen Universität Tübingen Sand 1 TübingenD-72076 Germany Leiden Observatory Leiden University PO Box 9513 Leiden2300 RA Netherlands Research Center for Computational Physics and Data Processing Silesian University in Opava Bezrucovo nam. 13 OpavaCZ-74601 Czech Republic Physics Department Middle East Technical University Ankara06531 Turkey INAF Osservatorio Astronomico di Roma Via Frascati 33 Monteporzio CatoneI-00078 Italy New York University Abu Dhabi PO Box 129188 Abu Dhabi United Arab Emirates Dipartimento di Fisica Enrico Fermi University of Pisa PisaI-56127 Italy INFN Italian National Institute for Nuclear Physics Pisa Section Pisa56127 Italy Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Department of Astrophysical Sciences Princeton University Peyton Hall PrincetonNJ08544 United States Mathematical Sciences and STAG Research Centre University of Southampton SouthamptonSO17 1BJ United Kingdom MIT Kavli Institute for Astrophysics and Space Research CambridgeMA02139 United States DTU Space Technical University of Denmark Elektrovej 327-328 Kgs Lyngby2800 Denmark INAF/IASF Palermo via Ugo La Malfa 153 PalermoI-90146 Italy Universita degli Studi di Palermo Dipartimento di Fisica e Chimica via Archira 36 Palermo90123 Italy

In this White Paper we present the potential of the Enhanced X-ray Timing and Polarimetry (eXTP) mission for determining the nature of dense matter;neutron star cores host an extreme density regime which cannot be replicated in a terrestrial laboratory. The tightest statistical constraints on the dense matter equation of state will come from pulse profile modelling of accretion-powered pulsars, burst oscillation sources, and rotation-powered pulsars. Additional constraints will derive from spin measurements, burst spectra, and properties of the accretion flows in the vicinity of the neutron star. Under development by an international Consortium led by the institute of High Energy Physics of the Chinese Academy of science, the eXTP mission is expected to be launched in the mid 2020s. Copyright © 2018, The Authors. All rights reserved.

关键词： Pulsars

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Noncontiguous Channel Allocation for Multimedia Communication in Cognitive Radio Networks

Noncontiguous Channel Allocation for Multimedia Communicatio...

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作者： Bhattacharya, Ansuman Ghosh, Rabindranath Sinha, Koushik Datta, Debasish Sinha, Bhabani P. Department of Computer Science and Engineering National Institute of Technology Shillong793003 India Department of Electronics and Communication Engineering St. Thomas' College of Engineering and Technolgy Kolkata700023 India Department of Computer Science Southern Illinois University Carbondale CarbondaleIL62901 United States Department of Electronics and Electrical Communication Engineering Indian Institute of Technology Kharagpur Kharagpur721302 India Advanced Computing and Microelectronics Unit Indian Statistical Institute Kolkata700108 India

In conventional wireless systems, unless a contiguous frequency band with width at least equal to the required bandwidth is obtained, multimedia communication cannot be effected with the desired quality of service. We propose here a novel channel allocation technique to overcome this limitation in a cognitive radio network, which is based on utilizing several noncontiguous channels, each of width smaller than the required bandwidth, but whose sum equals at least the required bandwidth. We present algorithms for channel sensing, channel reservation, and channel deallocation along with transmission and reception protocols with two different implementations based on FDM-FDMA and OFDM-FDMA techniques. Simulation results for both these implementations show that the proposed technique outperforms the existing first-fit and best-fit allocation techniques in terms of the average number of attempts needed for acquiring the necessary number of channels for all traffic situations ranging from light to extremely heavy traffic. Furthermore, the proposed technique can allocate the required numbers of channels in less than 1 s with FDM-FDMA even (4.5 s with OFDM-FDMA) for 96% traffic load, while the first-fit and best-fit techniques fail to allocate any channel in such situations. © 2015 IEEE.

关键词： Orthogonal frequency division multiplexing

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An Improved Method for Automatic Retinal Blood Vessel Vascular Segmentation Using Gabor Filter

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Open Journal of Medical Imaging 2015年第4期5卷 204-213页

作者： Nalan Karunanayake Nihal D. Kodikara Department of Electrical and Computer Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Science University of Colombo School of Computing Colombo Sri Lanka

Early detection of Non-Proliferative Diabetic Retinopathy (NDPR) is currently a highly interested research area in biomedical imaging. Ophthalmologists discover NDPR by observing the configuration of the vessel vascular network deliberately. Therefore, a computerized automatic system for the segmentation of vessel system will be an assist for ophthalmologists in order to detect an early stage of retinopathy. In this research, region based retinal vascular segmentation approach is suggested. In the steps of processing, the illumination variation of the fundus image is adjusted by using the point operators. Then, the edge features of the vessels are enhanced by applying the Gabor Filter. Finally, the region growing method with automatic seed point selection is used to extract the vessel network from the image background. The experiments of the proposed algorithm are conducted on DRIVE dataset, which is an open access dataset. Results obtain an accuracy of 94.9% over the dataset that has been used.

关键词： Diabetic Retinopathy Blood Vessel Segmentaion Retinul Fundus Image Gabor Filter Region Growing Point Operators Illumination Variation

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Variability-aware parametric yield enhancement via post-silicon tuning of hybrid redundant MAC units

Variability-aware parametric yield enhancement via post-sili...

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International Symposium on VLSI Design, Automation and Test

作者： Sunil Dutt Anshu Chauhan Sukumar Nandi Gaurav Trivedi Department of Electronics & Electrical Engineering Department of Computer Science & Engineering Indian Institute of Technology Guwahati India Center for Advanced Computing

Variations in process parameter jeopardize the parametric yield which imposes severe cost implication on the semiconductor industry. Post-silicon tunning, such as Adaptive Body Bias (ABB) and Dynamic Voltage Scaling (DVS) is a powerful technique that mitigates the impacts of process parameter variations. However, since process parameter variations are getting aggravated with continued CMOS technology scaling, the achievable performance by ABB or DVS alone is becoming limited. In this paper, to enhance the parametric yield, we integrate ABB and DVS for the Hybrid Redundant Multiply-and-Accumulate (HR-MAC) units. Simulation results based on the PTM 32nm CMOS technology show that the proposed approach enhances the parametric yield at Fast-Fast (FF), Fast-Slow (FS), Slow-Fast (SF) and Slow-Slow (SS) process corners by 81.5%, 45.3%, 59.92% and 89.08%, respectively.

关键词： Delays Voltage control MOS devices CMOS integrated circuits CMOS technology Tuning Systematics

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Exploiting game theoretic analysis for link recommendation in social networks 15

Exploiting game theoretic analysis for link recommendation i...

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24th ACM International Conference on Information and Knowledge Management, CIKM 2015

作者： Zhao, Tong Zhao, H. Vicky King, Irwin Shenzhen Key Laboratory of Rich Media Big Data Analytics and Applications Shenzhen Research Institute Chinese University of Hong Kong Shenzhen China Department of Computer Science and Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong Electrical and Computer Engineering Department University of Alberta EdmontonAB Canada

ISBN: (纸本)9781450337946

The popularity of Online Social Networks (OSNs) has attracted great research interests in different fields. In Economics, researchers use game theory to analyze the mechanism of network formation, which is called Network Formation Game. While in computer science, much effort has been done in building machine learning models to predict future or missing links. However, there are few works considering how to combine game theoretic analysis and machine learning models. Therefore, in this paper, we study the problem of Exploiting Game Theoretic Analysis for Link Recommendation in Social Networks. Our goal is to improve link recommendation accuracy via leveraging the power of Network Formation Games into machine learning models. We present two different approaches to solve this problem. First, we propose a three-phase method that straightforwardly combines game theoretic analysis with machine learning models. Second, we develop a unified model, BPRLGT, that incorporates Network Formation Game into a Bayesian ranking framework for link recommendation. Specifically, BPRLGT takes advantage of network topology and we design a game theoretic sampling approach to improve its training process. The experiments are conducted on four real world datasets and the results on all datasets demonstrate that both our proposed three-phase method and the unified ranking model outperform the baseline methods. © 2015 ACM.

关键词： Game theory

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Double Nyström method: An efficient and accurate Nyström scheme for large-scale data sets 32

Double Nyström method: An efficient and accurate Nyström s...

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32nd International Conference on Machine Learning, ICML 2015

作者： Lim, Woosang Kim, Minhwan Park, Haesun Jung, Kyomin School of Computing KAIST Daejeon Korea Republic of LG Electronics Seoul Korea Republic of School of Computational Science and Engineering Georgia Institute of Technology AtlantaGA30332 United States Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of

ISBN: (纸本)9781510810587

The Nyström method has been one of the most effective techniques for kernel-based approach that scales well to large data sets. Since its introduction, there has been a large body of work that improves the approximation accuracy while maintaining computational efficiency. In this paper, we present a novel Nyström method that improves both accuracy and efficiency based on a new theoretical analysis. We first provide a generalized sampling scheme, CAPS, that minimizes a novel error bound based on the subspace distance. We then present our double Nyström method that reduces the size of the decomposition in two stages. We show that our method is highly efficient and accurate compared to other state-of-the-art Nyström methods by evaluating them on a number of real data sets. Copyright © 2015 by the author(s).

关键词： Computational efficiency

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A New Logistic Map Based Chaotic Biogeography-based Optimization Approach for Cluster Analysis

A New Logistic Map Based Chaotic Biogeography-based Optimiza...

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2016 IEEE International Conference on Progress in Informatics and computing

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang School of Computer Science and Technology Nanjing Normal University Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Department of Electrical Engineering The city college of New YorkCUNY Department of Mechanical and Control Engineering Kyushu Institute of Technology School of Information Engineering Yangzhou University School of Physics and Electronic Engineering Taizhou University School of Electronic Information Shanghai Dianji University School of Energy and Mechanical Engineering Nanjing Normal University Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization(CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： chaotic biogeography-based optimization cluster analysis centroid-based clustering simulation particle swarm optimization

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From categorical to numerical: Multiple transitive distance learning and embedding

From categorical to numerical: Multiple transitive distance ...

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SIAM International Conference on data Mining 2015, SDM 2015

作者： Zhang, Kai Wang, Qiaojun Chen, Zhengzhang Marsic, Ivan Kumar, Vipin Jiang, Guofei Zhang, Jie School of Computer Science Southwest Petroleum University Chengdu Sichuan Province610500 China Institute of Data Science and Technology Alibaba Group SeattleWA98101 United States Department of Electrical and Computer Engineering Rutger-s the State University of New Jersey NJ08854 United States NEC Laboratories America Inc. PrincetonNJ08540 United States Department of Electrical Engineering and Computer Science Northwestern University EvanstonIL60208 United States Department of Computer Science and Engineering University of Minnesota MinneapolisMN55455 United States Center for Computational Systems Biology Fudan University Shanghai200433 China

ISBN: (纸本)9781510811522

Categorical data are ubiquitous in real-world databases. However, due to the lack of an intrinsic proximity measure, many powerful algorithms for numerical data analysis may not work well on their categorical counterparts, making it a bottleneck in practical applications. In this paper, we propose a novel method to transform categorical data to numerical representations, so that abundant numerical learning methods can be exploited in categorical data mining. Our key idea is to learn a pairwise dissimilarity among categorical symbol-s, henceforth a continuous embedding, which can then be used for subsequent numerical treatment. There are two important criteria for learning the dissimilarities. First, it should capture the important "transitivity" which has shown to be particularly useful in measuring the proximity relation in categorical data. Second, the pairwise sample geometry arising from the learned symbol distances should be maximally consistent with prior knowledge (e.g., class labels) to obtain a good generalization performance. We achieve them through multiple transitive distance learning and embedding. Encouraging results are observed on a number of benchmark classification tasks against state-of-the-art. Copyright © SIAM.

关键词： Distance education

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Response Policies to Process Module Failure in Single-Arm Cluster Tools Subject to Wafer Residency Time Constraints

Response Policies to Process Module Failure in Single-Arm Cl...

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作者： Qiao, Yan Pan, Chun-Rong Wu, Nai-Qi Zhou, Mengchu Department of Industrial Engineering School of Electro-Mechanical Engineering Guangdong University of Technology Guangzhou510006 China School of Mechatronics and Electrical Engineering Jiangxi University of Science and Technology Ganzhou341000 China Institute of Systems Engineering Macau University of Science and Technology Taipa China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102-1982 United States

In semiconductor manufacturing, wafer residency time constraints make the scheduling problem of cluster tools complicated. A process module (PM) in cluster tools is prone to failure. It is crucial to deal with any such failure in a proper and timely manner. If there are feasible periodic schedules in operating a cluster tool before and after a PM failure, it is desired to make it operate continuously when such a failure occurs. However, due to wafer residency time constraints, it is highly challenging to control a tool such that it can be correctly transferred from a feasible schedule before failure to another after it. To solve this problem, a Petri net model is developed to describe the dynamic behavior of a single-arm cluster tool and failure response policies are proposed. The proposed policies are formulated via simple control laws for their easy implementation. Examples are given to show them. © 2015 IEEE.

关键词： Scheduling

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Automated Vulnerability Analysis of AC State Estimation under Constrained False data Injection in Electric Power Systems

Automated Vulnerability Analysis of AC State Estimation unde...

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IEEE Annual Conference on Decision and Control

作者： Sicun Gao Le Xie Armando Solar-Lezama Dimitrios Serpanos Howard Shrobe MIT Computer Science and Artificial Intelligence Lab Department of Electrical and Computer Engineering Texas A&M University Qatar Computing Research Institute

ISBN: (纸本)9781479978878

We introduce new methods for the automatic vulnerability analysis of power grids under false data injection attacks against nonlinear (AC) state estimation. We encode the analysis problems as logical decision problems that can be solved automatically by SMT solvers. To do so, we propose an analysis technique named "symbolic propagation," which is inspired by symbolic execution methods for finding bugs and exploits in software programs. We show that the proposed methods can successfully analyze vulnerability of AC state estimation in realistic power grid models. Our approach is generalizable towards many other applications such as power flow analysis and state estimation.

关键词： power systems State estimation Power grids Power flow analysis False Vulnerability AUTOMATIC

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