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7th International Green and Sustainable Computing Conference, IGSC 2016

作者： Xue, Pei Li, Tao Dong, Han Liu, Chunbo Ma, Wenjing Pei, Songwen College of Computer and Control Engineering Nankai University Tianjin300071 China Information Security Evaluation Center Civil Aviation University of China Tianjin300300 China Laboratory of Parallel Software and Computational Science State Key Laboratory of Computing Science Institute of Software CAS Beijing China Shanghai Key Lab of Modern Optical Systems Department of Computer Science and Engineering University of Shanghai for Science and Technology Shanghai200093 China

ISBN: (纸本)9781509051175

Encryption algorithms are applied to a variety of fields and the security of encryption algorithms depends heavily on the computational infeasibility of exhaustive key-space search. RC4 algorithm has an extensive application for stream encryption, however, the disadvantages of traditional RC4 serial algorithm are large computational quantity and slow computation speed, which means a great challenge for throughput of computing system. Graphics processors recently have been widely used as accelerators for high throughput computing. In this paper, GPU is used to improve the efficiency and performance of attacking RC4 algorithm. First, we revised RC4 algorithm to make it easier to parallelize on a GPU. Then we take advantage of constant memory and shared memory in GPU to search the key space of RC4 algorithm efficiently. Besides, we solved the bank conflict problem in shared memory to further improve the performance. Our approach was evaluated in the whole key space of 40-bit, and the results show it can complete searching of the whole key space within 12.8 hours. © 2016 IEEE.

关键词： Graphics processing unit

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Flow: A modular learning framework for mixed autonomy traffic

arXiv

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arXiv 2017年

作者： Wu, Cathy Kreidieh, Abdul Rahman Parvate, Kanaad Vinitsky, Eugene Bayen, Alexandre M. Laboratory For Information And Decision Systems Massachusetts Institute Of Technology CambridgeMA02139 United States Department Of Civil And Environmental Engineering Massachusetts Institute Of Technology CambridgeMA02139 United States Institute Of Data Systems And Society Massachusetts Institute Of Technology CambridgeMA02139 United States Department Of Civil And Environmental Engineering University Of California Berkeley BerkeleyCA94720 United States Department Of Electrical Engineering And Computer Sciences University Of California Berkeley BerkeleyCA94720 United States Department Of Mechanical Engineering University Of California Berkeley BerkeleyCA94720 United States Institute For Transportation Studies University Of California Berkeley BerkeleyCA94720 United States

The rapid development of autonomous vehicles (AVs) holds vast potential for transportation systems through improved safety, efficiency, and access to mobility. However, the progression of these impacts, as AVs are adopted, is not well understood. Numerous technical challenges arise from the goal of analyzing the partial adoption of autonomy: partial control and observation, multi-vehicle interactions, and the sheer variety of scenarios represented by real-world networks. To shed light into near-term AV impacts, this article studies the suitability of deep reinforcement learning (RL) for overcoming these challenges in a low AV-adoption regime. A modular learning framework is presented, which leverages deep RL to address complex traffic dynamics. Modules are composed to capture common traffic phenomena (stop-and-go traffic jams, lane changing, intersections). Learned control laws are found to improve upon human driving performance, in terms of system-level velocity, by up to 57% with only 4-7% adoption of AVs. Furthermore, in single-lane traffic, a small neural network control law with only local observation is found to eliminate stop-and-go traffic - surpassing all known model-based controllers to achieve near-optimal performance - and generalize to out-of-distribution traffic densities. Copyright © 2017, The Authors. All rights reserved.

关键词： Deep learning

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Distributed kalman filter in a network of linear dynamical systems

arXiv

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arXiv 2017年

作者： Marelli, Damián Zamani, Mohsen Fu, Minyue Department of Control Science and Engineering State Key Laboratory of Industrial Control Technology Zhejiang University 388 Yuhangtang Road Hangzhou Zhejiang Province310058 French-Argentinean International Center for Information and Systems Sciences National Scientific and Technical Research Council Ocampo Esmeralda Rosario2000 Argentina School of Electrical Engineering and Computer Science University of Newcastle University Drive CallaghanNSW2308 Australia

This paper is concerned with the problem of distributed Kalman filtering in a network of interconnected subsystems with distributed control protocols. We consider networks, which can be either homogeneous or heterogeneous, of linear time-invariant subsystems, given in the state-space form. We propose a distributed Kalman filtering scheme for this setup. The proposed method provides, at each node, an estimation of the state parameter, only based on locally available measurements and those from the neighbor nodes. The special feature of this method is that it exploits the particular structure of the considered network to obtain an estimate using only one prediction/update step at each time step. We show that the estimate produced by the proposed method asymptotically approaches that of the centralized Kalman filter, i.e., the optimal one with global knowledge of all network parameters, and we are able to bound the convergence rate. Moreover, if the initial states of all subsystems are mutually uncorrelated, the estimates of these two schemes are identical at each time step. Copyright © 2017, The Authors. All rights reserved.

关键词： Kalman filters

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Codelet Scheduling by Genetic Algorithm

Codelet Scheduling by Genetic Algorithm

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Songwen Pei Jinkai Wang Wenyang Cui Linhua Jiang Tongsheng Geng Jean-Luc Gaudiot Stéphane Zuckerman Shanghai Key Lab of Modern Optical Systems University of Shanghai for Science and Technology Shanghai China Parallel Systems and Computer Architecture Lab University of California Irvine CA USA Computer Architecture & Parallel Systems Laboratory University of Delaware Newark DE

ISBN: (纸本)9781509032068

Codelet model is a fine-grained, event-driven hybrid parallel model inspired by dataflow, whose performance depends on the scheduling policy. How to design optimal codelet scheduling policy based on the features of tasks is important to the codelet-based system performance. In this paper, we propose an adaptive codelet scheduling policy by combing "pure" genetic algorithm for tasks with complex dependencies. It is verified that the policy is effective based on bunches of experimental results.

关键词： Computational modeling Schedules Genetic algorithms Scheduling Runtime Optimal scheduling Sociology

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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge CB2 1EW UK Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge UK Ludwig Center at Harvard Medical School Boston MA USA School of Mathematical Sciences and Center for Statistical Science Peking University Beijing 100871 China Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Bioi

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DD-Rtree: A dynamic distributed data structure for efficient data distribution among cluster nodes for spatial data mining algorithms

DD-Rtree: A dynamic distributed data structure for efficient...

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IEEE International Conference on Big Data

作者： Jagat Sesh Challa Poonam Goyal S. Nikhil Aditya Mangla Sundar S. Balasubramaniam Navneet Goyal Department of Computer Science & Information Systems Birla Institute of Technology & Science Pilani Pilani Campus India Advanced Data Analytics & Parallel Technologies Laboratory Department of Computer Science & Information Systems Birla Institute of Technology & Science Pilani Pilani Campus India

ISBN: (纸本)9781467390064

Parallelizing data mining algorithms has become a necessity as we try to mine ever increasing volumes of data. Spatial data mining algorithms like Dbscan, Optics, Slink, etc. have been parallelized to exploit a cluster infrastructure. The efficiency achieved by existing algorithms can be attributed to spatial locality preservation using spatial indexing structures like k-d-tree, quad-tree, grid files, etc. for distributing data among cluster nodes. However, these indexing structures are static in nature, i.e., they need to scan the entire dataset to determine the partitioning coordinates. This results in high data distribution cost when the data size is large. In this paper, we propose a dynamic distributed data structure, DD-Rtree, which preserves spatial locality while distributing data across compute nodes in a shared nothing environment. Moreover, DD-Rtree is dynamic, i.e., it can be constructed incrementally making it useful for handling big data. We compare the quality of data distribution achieved by DD-Rtree with one of the recent distributed indexing structure, SD-Rtree. We also compare the efficiency of queries supported by these indexing structures along with the overall efficiency of DBSCAN algorithm. Our experimental results show that DD-Rtree achieves better data distribution and thereby resulting in improved overall efficiency.

关键词： Data structures Clustering algorithms Data mining Indexing Distributed databases Algorithm design and analysis

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Decode-and-Forward Relaying via Standard AWGN Coding and Decoding

Decode-and-Forward Relaying via Standard AWGN Coding and Dec...

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作者： Khina, Anatoly Kochman, Yuval Erez, Uri Wornell, Gregory W. Department of Electrical Engineering-Systems Tel Aviv University Tel Aviv69978 Israel Department of Electrical Engineering California Institute of Technology PasadenaCA91125 United States School of Computer Science and Engineering Hebrew University of Jerusalem Jerusalem91904 Israel Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States

A framework is developed for decode-and-forward-based relaying using standard coding and decoding that are good for the single-input single-output (SISO) additive white Gaussian noise channel. The framework is applicable to various scenarios and is demonstrated for several important cases. Each of these scenarios is transformed into an equivalent Gaussian multiple-input multiple-output (MIMO) common-message broadcast problem, which proves useful even when all links are SISO ones. Over the effective MIMO broadcast channel, a recently developed Gaussian MIMO common-message broadcast scheme is applied. This scheme transforms the MIMO links into a set of parallel SISO channels with no loss of mutual information, using linear pre-and post-processing combined with successive decoding. Over these resulting SISO channels, off-the-shelf scalar codes may be used. © 2016 IEEE.

关键词： Mathematical transformations

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Constructing IGA-suitable planar parameterization from complex CAD boundary by domain partition and global/local optimization

arXiv

引用

arXiv 2017年

作者： Xu, Gang Li, Ming Mourrain, Bernard Rabczuk, Timon Xu, Jinlan Bordas, Stéphane P.A. School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou310018 China State Key Laboratory of CAD &CG Zhejiang University Hangzhou310058 China INRIA Sophia-Antipolis 2004 Route des Lucioles Cedex06902 France Institute of Structural Mechanics Bauhaus-University Weimar Marienstr. 15 WeimarD-99423 Germany Research Unit in Engineering University of Luxembourg Luxembourg

In this paper, we propose a general framework for constructing IGA-suitable planar B-spline parameterizations from given complex CAD boundaries consisting of a set of B-spline curves. Instead of forming the computational domain by a simple boundary, planar domains with high genus and more complex boundary curves are considered. Firstly, some pre-processing operations including Bézier extraction and subdivision are performed on each boundary curve in order to generate a high-quality planar parameterization;then a robust planar domain partition framework is proposed to construct high-quality patch-meshing results with few singularities from the discrete boundary formed by connecting the end points of the resulting boundary segments. After the topology information generation of quadrilateral decomposition, the optimal placement of interior Bézier curves corresponding to the interior edges of the quadrangulation is constructed by a global optimization method to achieve a patch-partition with high quality. Finally, after the imposition of C1/G1-continuity constraints on the interface of neighboring Bézier patches with respect to each quad in the quadrangulation, the high-quality Bézier patch parameterization is obtained by a C1constrained local optimization method to achieve uniform and orthogonal iso-parametric structures while keeping the continuity conditions between patches. The efficiency and robustness of the proposed method are demonstrated by several examples which are compared to results obtained by the skeleton-based parameterization approach. Copyright © 2017, The Authors. All rights reserved.

关键词： Parameterization

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Author Correction: Loss of Phd2 cooperates with BRAFV600E to drive melanomagenesis

引用

Nature communications 2019年第1期10卷 1211页

作者： Shujing Liu Gao Zhang Jianping Guo Xiang Chen Jingce Lei Kan Ze Liyun Dong Xiangpeng Dai Yang Gao Daisheng Song Brett L Ecker Ruifeng Yang Caitlin Feltcher Kai Peng Cheng Feng Hui Chen Rebecca X Lee Heddy Kerestes Jingwen Niu Suresh Kumar Weiting Xu Jie Zhang Zhi Wei James S Martin Xiaoming Liu Gordon Mills Yiling Lu Wei Guo Lunquan Sun Lin Zhang Ashani Weeraratna Meenhard Herlyn Wenyi Wei Frank S Lee Xiaowei Xu Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA 19104 USA. The Wistar Institute Philadelphia PA 19104 USA. Department of Pathology Beth Israel Deaconess Medical Center Harvard Medical School Boston MA 02115 USA. Xiangya Hospital Central South University Changsha 410008 China. Department of Computer Science New Jersey Institute of Technology Newark NJ 07102 USA. Department of Systems Biology The University of Texas MD Anderson Cancer Center Houston TX 77030 USA. Department of Biology School of Arts and Sciences University of Pennsylvania Philadelphia PA 19104 USA. Center for Research on Reproduction & Women's Health University of Pennsylvania Philadelphia PA 19104 USA. Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA 19104 USA. franklee@pennmedicine.upenn.edu. Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA 19104 USA. xug@pennmedicine.upenn.edu.

The original version of this Article contained an error in the spelling of the author Brett L. Ecker, which was incorrectly given as Brett Ecker. This has now been corrected in both the PDF and HTML versions of the Ar...

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Investigation of microinverter based on the two-switch DC-DC flyback converter topology

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IOP Conference Series: Earth and Environmental Science 2018年第1期161卷

作者： L El Iysaouy E Bielskis M Lahbabi A Baskys A Oumnad The Signals Systems and Components Laboratory Sidi Mohamed Ben Abdellah University FST Fez Morocco Department of Electrical Engineering Mohamed V University EMI Rabat Morocco Center for Physical Sciences and Technology Sauletekio al.3 LT-10257 Vilnius Lithuania Department of Computer Engineering Vilnius Gediminas Technical University Naugarduko St. 41 LT-03227 Vilnius Lithuania

This paper presents an investigation of a novel scheme of the single stage flyback microinverter based on two-switch [1]. The purpose of this topology of microinverter is to transform the DC power generated by the DC voltage input to a standard electric grid AC voltage. The single stage two-switch DC-DC flyback microinverter for the case CL output filter ensures the isolation between the DC power sources and the AC sources by a flyback transformer; has high efficiency (more than 96%) if the parameters of dual two-transistor stage: M1 to M4 are chosen correctly and Total Harmonic Distortion THD less than 5 %. However, the design of this microinverter is characterized by a low number of components.

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