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2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017

作者： Wang, Di Guo, Qinglai Song, Yan Gao, Kunlun Zhou, Aihua State Key Laboratory of Power Systems Department of Electrical Engineering Tsinghua University Beijing100084 China Electric Power Research Institute State Grid Shanghai Municipal Electric Power Company Shanghai200437 China Advanced Computing and Big Data Laboratory of SGCC Global Energy Interconnection Research Institute Beijing102209 China

ISBN: (纸本)9781538614273

With the development of information technology, the operation of power grid increasingly depends upon the support of strong communication network. The power system consisting of grids infrastructure and communication equipment is a typical cyber-physical system(CPS). In recent years, power accidents that information-side failure impacts on physical operation happen at times. In order to simulate the impacts of information failure on grid operation, we develop a cyber-physical simulation tool for the secondary-voltage control of power system to implement the reasonable analysis and evaluation of the influence of different types of information failure on voltage control effect. In this paper, the graph database is introduced to construct the basic cyber-physical data model as an important part of the simulation tool, whose graphical modeling and management is friendly for users. In addition, the importance of different types of information is analyzed with the tool. It can be seen that the voltage information is more fragile and critical than the non-independent generator reactive information. © 2017 IEEE.

关键词： Cyber Physical System

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Low-resolution face recognition in the wild via selective knowledge distillation

arXiv

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arXiv 2018年

作者： Ge, Shiming Zhao, Shengwei Li, Chenyu Li, Jia Institute of Information Engineering Chinese Academy of Sciences Beijing100095 China Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security at University of Chinese Academy of Sciences China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

Typically, the deployment of face recognition models in the wild needs to identify low-resolution faces with extremely low computational cost. To address this problem, a feasible solution is compressing a complex face model to achieve higher speed and lower memory at the cost of minimal performance drop. Inspired by that, this paper proposes a learning approach to recognize low-resolution faces via selective knowledge distillation. In this approach, a two-stream convolutional neural network (CNN) is first initialized to recognize high-resolution faces and resolution-degraded faces with a teacher stream and a student stream, respectively. The teacher stream is represented by a complex CNN for high-accuracy recognition, and the student stream is represented by a much simpler CNN for low-complexity recognition. To avoid significant performance drop at the student stream, we then selectively distil the most informative facial features from the teacher stream by solving a sparse graph optimization problem, which are then used to regularize the fine-tuning process of the student stream. In this way, the student stream is actually trained by simultaneously handling two tasks with limited computational resources: approximating the most informative facial cues via feature regression, and recovering the missing facial cues via low-resolution face classification. Experimental results show that the student stream performs impressively in recognizing low-resolution faces and costs only 0.15MB memory and runs at 418 faces per second on CPU and 9, 433 faces per second on GPU. Copyright © 2018, The Authors. All rights reserved.

关键词： Students

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High-level representation sketch for video event retrieval

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Science China(Information Sciences) 2016年第7期59卷 158-172页

作者： Yu ZHANG Xiaowu CHEN Liang LIN Changqun XIA Dongqing ZOU State Key Laboratory of Virtual Reality Technology and Systems School of Compute Science and EngineeringBeihang University School of Advanced Computing Sun Yat-Sen University

Representing video events is an essential step for a wide range of visual applications. In this paper,we propose the event sketch, a high-level event representation, to depict the dynamic properties of video events composed of actions of semantic objects. We show that this representation can facilitate a novel sketch based video retrieval(SBVR) system, which has not been considered before to the best of our knowledge. In this system, users are allowed to draw the evolutions(e.g. spatiotemporal layouts and behaviors of semantic objects)on a board, and retrieve the events whose semantic objects have the similar evolutions from a database. To do this, event sketches are constructed on both the user queries and database videos, and compared under a novel graph-matching scheme based on data-driven Monta Carlo Markov chain(DDMCMC). To test our approach, we collect a novel dataset of goal events in real soccer videos, which consists actions of multiple players and shows large variability in the evolution process of the events. Experiments on this dataset and the publicly available dataset CAVIAR demonstrated the effectiveness of the proposed approach.

关键词： video retrieval event representation event sketch drawing board distance function relevance feedback DDMCMC

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Ensuring kernel integrity using KIPBMFH 1

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作者： Chen, Zhifeng Li, Qingbao Guo, Songhui Wang, Ye State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9783319298146

ISBN: (纸本)9783319298139

Kernel-level malwares are a serious threat to the integrity and security of the operating system. Current kernel integrity measurement methods have one-sidedness in selecting the measurement objects, and the characters of periodic measurement make TOC-TOU attacks unavoidable. The kernel integrity measurement methods based on hardware usually suffer high cost due to the additional hardware, while the kernel integrity measurement methods based on host are always likely to be passed. To address these problems, a kernel integrity protection approach based on memory forensics technique implemented in Hypervisor (KIPBMFH) is proposed in this paper. We first use memory forensics technology to extract the static and dynamic measurement objects, and then adopt time randomization algorithm to weaken TOC-TOU attacks. The experimental results show that KIPBMFH can measure the integrity of the operating system effectively, and has reasonable performance overhead. © Springer International Publishing Switzerland 2016.

关键词： Malware

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Nonabelian magnonics in antiferromagnets

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Physical Review B 2018年第13期98卷 134450-134450页

作者： Matthew W. Daniels Ran Cheng Weichao Yu (余伟超) Jiang Xiao (萧江) Di Xiao Department of Physics Carnegie Mellon University Pittsburgh Pennsylvania 15213 USA Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 USA Department of Physics and State Key Laboratory of Surface Physics Fudan University Shanghai 200433 China Collaborative Innovation Center of Advanced Microstructures Nanjing 210093 China Institute for Nanoelectronics Devices and Quantum Computing Fudan University Shanghai 200433 China

We present a semiclassical formalism for antiferromagnetic (AFM) magnonics which promotes the central ingredient of spin wave chirality, encoded in a quantity called magnonic isospin, to a first-class citizen of the theory. We use this formalism to unify results of interest from the field under a single chirality-centric formulation. Our main result is that the isospin is governed by unitary time evolution, through a Hamiltonian projected down from the full spin wave dynamics. Because isospin is SU(2) valued, its dynamics on the Bloch sphere are precisely rotations, which, in general, do not commute. Consequently, the induced group of operations on AFM spin waves is nonabelian. This is a paradigmatic departure from ferromagnetic magnonics, which operates purely within the abelian group generated by spin wave phase and amplitude. Our investigation of this nonabelian magnonics in AFM insulators focuses on studying several simple gate operations, and offering in broad strokes a program of study for interesting new logic families in antiferromagnetic spin wave systems.

关键词： Antiferromagnetism Geometric & topological phases Hall effect Magnetic texture Magnons Spin current Spin waves Spintronics 1-dimensional spin chains 2-dimensional systems Antiferromagnets Magnetic insulators Nanoribbon Bloch wave theory Classical spin chains Discrete symmetries in condensed matter Domain walls Heisenberg model Landau-Lifschitz-Gilbert equation Landau-Lifshitz model Methods in transport Non-Abelian models

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Erratum to: Search for exclusive Higgs and Z boson decays to ϕγ and ργ with the ATLAS detector

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Journal of High Energy Physics 2023年第12期2023卷 1-21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. Bakker, P. J. 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. Barno 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 United States of America 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 United States of America 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 United States of America Department of Physics Stockholm University Stockholm Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste 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 United States of America 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 United States of America Joi

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Finite Temperature Phase Transition in a Cross-Dimensional Triangular Lattice

arXiv

引用

arXiv 2018年

作者： Jin, Shengjie Guo, Xinxin Peng, Peng Chen, Xuzong Li, Xiaopeng Zhou, Xiaoji School of Electronics Engineering and Computer Science Peking University Beijing100871 China State Key Laboratory of Surface Physics Institute of Nanoelectronics and Quantum Computing Department of Physics Fudan University Shanghai200433 China Collaborative Innovation Center of Advanced Microstructures Nanjing210093 China Collaborative Innovation Center of Extreme Optics Shanxi University Taiyuan Shanxi030006 China

Atomic many-body phase transitions and quantum criticality have recently attracted much attention in non-standard optical lattices. Here we perform an experimental study of finite-temperature superfluid transition of bosonic atoms confined in a three dimensional triangular lattice, whose structure can be continuously deformed to dimensional crossover regions including quasi-one and two dimensions. This non-standard lattice system provides a versatile platform to investigate many-body correlated phases. For the three dimensional case, we find that the finite temperature superfluid transition agrees quantitatively with the Gutzwiller mean field theory prediction, whereas tuning towards reduced dimensional cases, both quantum and thermal fluctuation effects are more dramatic, and the experimental measurement for the critical point becomes strongly deviated from the mean field theory. We characterize the fluctuation effects in the whole dimension crossover process. Our experimental results imply strong many-body correlations in the system beyond mean field description, paving a way to study quantum criticality near Mott-superfluid transition in finite temperature dimension-crossover lattices. Copyright © 2018, The Authors. All rights reserved.

关键词： Mean field theory

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Joint adaptive neighbours and metric learning for multi-view subspace clustering

arXiv

引用

arXiv 2017年

作者： Xu, Nan Guo, Yanqing Wang, Jiujun Luo, Xiangyang He, Ran School of Information and Communication Engineering Dalian University of Technology State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Science and Technology Institute National Laboratory of Pattern Recognition CASIA

Due to the existence of various views or representations in many real-world data, multi-view learning has drawn much attention recently. Multi-view spectral clustering methods based on similarity matrixes or graphs are pretty popular. Generally, these algorithms learn informative graphs by directly utilizing original data. However, in the real-world applications, original data often contain noises and outliers that lead to unreliable graphs. In addition, different views may have different contributions to data clustering. In this paper, a novel Multi-view Subspace Clustering method unifying Adaptive neighbours and Metric learning (MSCAM), is proposed to address the above problems. In this method, we use the subspace representations of different views to adaptively learn a consensus similarity matrix, uncovering the subspace structure and avoiding noisy nature of original data. For all views, we also learn different Mahalanobis matrixes that parameterize the squared distances and consider the contributions of different views. Further, we constrain the graph constructed by the similarity matrix to have exact c (c is the number of clusters) connected components. An iterative algorithm is developed to solve this optimization problem. Moreover, experiments on a synthetic dataset and different real-world datasets demonstrate the effectiveness of MSCAM. Copyright © 2017, The Authors. All rights reserved.

关键词： Cluster analysis

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MCSMGS:Malware Classification Model Based on Deep Learning

MCSMGS:Malware Classification Model Based on Deep Learning

引用

第九届网络分布式计算与知识发现国际会议( 2017 International Conference on Cyber-enabled distributed computing and knowledge discovery)

作者： Zhen Shan Jing Wang Fudong Liu Bingling Zhao Xi Meng Jin Han Hongyan Wang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Division of Information Theory Aviation University of Air Force Changchun China

As a major threat to cyber security,malware has been increasingly damaging national *** paper proposes a malware classification model,*** model(Malware Classification Based on Static Malware Gene Sequences),that combines the static malware genes with deep learning *** model extracts the malware gene sequences that have both material attribute and informational *** it makes distributed representation for each malware gene to represent the intrinsic correlation and ***,the SMGS_CNN(Static Malware Gene Sequences--Convolution Neural Network)module is used to construct the neural network to analyze the malware gene sequences and realize malware *** experimental results show that the classification accuracy is greatly improved and up to 98%with the MCSMGS *** model is more effective than the traditional SVM model.

关键词： malware gene sequence intrinsic correlation similarity neural network classification

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MBSA: a lightweight and flexible storage architecture for virtual machines

MBSA: a lightweight and flexible storage architecture for vi...

引用

作者： Chen, Xian Chen, Wenzhi Lu, Zhongyong Zhang, Yu Chang, Rui Hassan, Mohammad Mehedi Alelaiwi, Abdulhameed Xiang, Yang College of Computer Science and Technology Zhejiang University Hangzhou China State Key Laboratory of Mathematic Engineering and Advanced Computing Zhengzhou China College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia Centre for Cyber Security Research Deakin University BurwoodVIC Australia

With the advantages of extremely high access speed, low energy consumption, nonvolatility, and byte addressability, nonvolatile memory (NVM) device has already been setting off a revolution in storage field. Conventional storage architecture needs to be optimized or even redesigned from scratch to fully explore the performance potential of NVM device. However, most previous NVM-related works only explore its low access latency and low energy consumption. Few works have been done to explore the appropriate way to use NVM device for improving virtual machine's storage performance. In this paper, we comprehensively evaluate and analyze conventional virtual machine's storage architecture. We find that, even with cutting-edge optimization technologies, virtual machine can only achieve 30% of NVM device's original performance. Based on this observation, we propose a memory bus–based storage architecture, which we named MBSA. Memory bus–based storage architecture can greatly shorten the length of virtual machine's storage input/output stack and improve NVM device's use flexibility. In addition, an efficient wear-leveling algorithm is proposed to prolong NVM device's lifespan. To evaluate the new architecture, we implement it as well as the wear-leveling algorithm on real hardware and software platform. Experimental results show that MBSA can provide a big performance improvement, about 2.55X, and the wear-leveling algorithm can efficiently balance write operations on NVM device with a negligible performance overhead (no more than 3%). Copyright © 2017 John Wiley & Sons, Ltd.

关键词： Virtual machine

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