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Hyperspectral Open Set Classification towards Deep Networks Based on Boxplot

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IOP Conference Series: Earth and Environmental science 2021年第1期693卷

作者： Yu Liu Jing Hou Yuanxi Peng Yunpeng Xu Tian Jiang College of Advanced Interdisciplinary Studies National University of Defense Technology Changsha 410073 China State Key Laboratory of High-Performance Computing College of Computer National University of Defense Technology Changsha 410073 China Beijing Institute for Advanced Study National University of Defense Technology Beijing 100010 China

Recently, hyperspectral imaging (HSI) supervised classification has achieved an astonishing performance by using deep learning. However, most of them take the ideal assumption of 'closed set', where all testing classes have been known during training. In fact, in the real world, new classes unseen in training may appear during testing. Obviously, traditional supervised classification methods cannot operate correctly in the real world, which requires classifiers not only to classify known classes, but reject the unknown in order to avoid false positives. This challenge is called 'open set classification'(OSC). Considering the increased applications of deep learning in the real world, rejecting unknown classes during classification is of vital importance. To tackle it, we present a simple but effective HSI OSC method toward deep networks. In this method, we tighten the decision boundaries of SoftMax function of the last layer of the deep networks by using boxplots to analysis the statistical characteristics of the probability distribution of known classes and generate a proper rejection threshold for each known class. To test the performance of the proposed HSI OSC method, experiments are conducted on three HSI datasets. The results show that the proposed method outperforms existing state-of-the-art HSI OSC methods.

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The First LHAASO Catalog of Gamma-Ray Sources

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arXiv 2023年

作者： Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, J.T. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, X.T. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.Y. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Huang, Z.C. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Ke, T. Kuleshov, D. Kurinov, K. Li, B.B. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, Jian Li, Jie Li, K. Li, W.L. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Lu, R. Luo, Q. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, Z.W. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Sáiz, A. Semikoz, D. Shao, C.Y. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, Q.N. Sun, X.N. Sun, Z.B. Tam, P.H.T. Tang, Q.W. Tang, Z.B. Key Laboratory of Particle Astrophyics Experimental Physics Division & Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China Tianfu Cosmic Ray Research Center Sichuan Chengdu610000 China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Key Laboratory of Cosmic Rays Tibet University Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China School of Physics and Astronomy Sino-French Institute of Nuclear Engineering and Technology Sun Yat-sen University Guangdong Zhuhai519000 China School of Physics Sun Yat-sen University Guangdong Guangzhou510275 China School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China Département de Physique Nucléaire et Corpusculaire Faculté de Sciences Université de Genève 24 Quai Ernest Ansermet Geneva121

We present the first catalog of very-high energy and ultra-high energy gamma-ray sources detected by the Large high Altitude Air Shower Observatory (LHAASO). The catalog was compiled using 508 days of data collected by the Water Cherenkov Detector Array (WCDA) from March 2021 to September 2022 and 933 days of data recorded by the Kilometer Squared Array (KM2A) from January 2020 to September 2022. This catalog represents the main result from the most sensitive large coverage gamma-ray survey of the sky above 1 TeV, covering declination from −20◦ to 80◦. In total, the catalog contains 90 sources with an extended size smaller than 2◦ and a significance of detection at > 5σ. Based on our source association criteria, 32 new TeV sources are proposed in this study. Among the 90 sources, 43 sources are detected with ultra-high energy (E > 100 TeV) emission at > 4σ significance level. We provide the position, extension, and spectral characteristics of all the sources in this catalog. Copyright © 2023, The Authors. All rights reserved.

关键词： Gamma rays

Applications of Game Theory in Vehicular Networks: A Survey

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arXiv 2021年

作者： Sun, Zemin Liu, Yanheng Wang, Jian Li, Guofa Anil, Carie Li, Keqiang Guo, Xinyu Sun, Geng Tian, Daxin Cao, Dongpu College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China Institute of Human Factors and Ergonomics College of Mechatronics and Control Engineering Shenzhen University Guangdong Shenzhen518060 China School of Computer Science and Engineering VIT-AP Andhra Pradesh Amaravati522237 India College of Engineering Nanjing Agricultural University Nanjing210031 China State Key Laboratory of Automotive Safety and Energy Department of Automotive Engineering Tsinghua University Beijing100084 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing100191 China Waterloo Cognitive Autonomous Driving Lab University of Waterloo N2L 3G1 Canada

In the Internet of things (IoT) era, vehicles and other intelligent components in an intelligent transportation system (ITS) are connected, forming vehicular networks (VNs) that provide efficient and safe traffic and ubiquitous access to various applications. However, as the number of nodes in an ITS increases, it is challenging to satisfy a varied and large number of service requests with different quality of service (QoS) and security requirements in highly dynamic VNs. Intelligent nodes in VNs can compete or cooperate for limited network resources to achieve the objective for either an individual or a group. Game theory (GT), a theoretical framework designed for strategic interactions among rational decision makers sharing scarce resources, can be used to model and analyze individual or group behaviors of communicating entities in VNs. This paper primarily surveys the recent developments of GT in solving various challenges of VNs. This survey starts with an introduction to the background of VNs. A review of GT models studied in the VNs is then introduced, including the basic concepts, classifications, and applicable vehicular issues. After discussing the requirements of VNs and the motivation of using GT, a comprehensive literature review on GT applications in dealing with the challenges of current VNs is provided. Furthermore, recent contributions of GT to VNs that are integrated with diverse emerging 5G technologies are surveyed. Finally, the lessons learned are given, and several key research challenges and possible solutions of applying GT in VNs are outlined. Copyright © 2021, The Authors. All rights reserved.

关键词： Quality of service

Practical security of continuous-variable quantum key distribution with reduced optical attenuation

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Physical Review A 2019年第1期100卷 012313-012313页

作者： Yi Zheng Peng Huang Anqi Huang Jinye Peng Guihua Zeng College of Information Science and Technology Northwest University Xi'an 710127 Shaanxi China State Key Laboratory of Advanced Optical Communication Systems and Networks and Center of Quantum Information Sensing and Processing Shanghai Jiao Tong University Shanghai 200240 China Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha 410073 China Greatwall Quantum Laboratory China Greatwall Technology Changsha 410205 China

In a practical continuous-variable quantum key distribution (CVQKD) system, the optical attenuator can adjust the Gaussian-modulated coherent states and the local oscillator signal to an optimal value for guaranteeing the security of the system and optimizing the performance of the system. However, the performance of the optical attenuator may deteriorate due to the intentional and unintentional damage of the device. In this paper, we investigate the practical security of a CVQKD system with reduced optical attenuation. We find that the secret key rate of the system may be overestimated based on the investigation of parameter estimation under the effects of reduced optical attenuation. This opens a security loophole for Eve to successfully perform an intercept-resend attack in a practical CVQKD system. To close this loophole, we add an optical fuse at Alice's output port and design a scheme to monitor the level of optical attenuation in real time, which can make the secret key rate of the system evaluated precisely. The analysis shows that these countermeasures can effectively resist this potential attack.

关键词： Quantum communication Quantum cryptography Quantum information processing with continuous variables

LVMapper: A large-variance clone detector using sequencing alignment approach

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arXiv 2019年

作者： Wu, Ming Wang, Pengcheng Yin, Kangqi Cheng, Haoyu Xu, Yun Roy, Chanchal K. School of Computer Science University of Science and Technology of China Hefei China Key Laboratory on High Performance Computing Anhui Province Hefei China Department of Computer Science University of Saskatchewan Saskatoon Canada

To detect large-variance code clones (i.e. clones with relatively more differences) in large-scale code repositories is difficult because most current tools can only detect almost identical or very similar clones. It will make promotion and changes to some software applications such as bug detection, code completion, software analysis, etc. Recently, CCAligner made an attempt to detect clones with relatively concentrated modifications called large-gap clones. Our contribution is to develop a novel and effective detection approach of large-variance clones to more general cases for not only the concentrated code modifications but also the scattered code modifications. A detector named LVMapper is proposed, borrowing and changing the approach of sequencing alignment in bioinformatics which can find two similar sequences with more differences. The ability of LVMapper was tested on both self-synthetic datasets and real cases, and the results show substantial improvement in detecting large-variance clones compared with other state-of-the-art tools including CCAligner. Furthermore, our new tool also presents good recall and precision for general Type-1, Type-2 and Type-3 clones on the widely used benchmarking dataset, BigCloneBench. Copyright © 2019, The Authors. All rights reserved.

关键词： Cloning

Multi-Agent Online Coordination via Bayesian Inverse Planning

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Journal of Physics: Conference Series 2020年第1期1684卷

作者： Meiming Wang Long Lan Wenjing Yang Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha China

Multi-agent coordination is a classical applied engineering problem and has been widely used in daily life. To efficiently coordinate all agents in the environment, most traditional models rely on a robust communication system between agents. However, in the scenario of autonomous vehicles, building a reliable communication system is extremely expensive and is very difficult to achieve in the foreseeable future. In this paper, we propose an online multi-agent coordination mechanism for each agent in the absence of communication and explore the benefits of Bayesian inverse planning in achieving the Nash equilibrium which provides an optimal coordination solution for each participant in multi-agent environment. By deliberate design, the proposed Bayesian inverse planning enables each independent agent to infer goals and predict future actions of other agents only by simply observing the past actions of them. To make a timely response to the dynamic environment, the inferences and predictions can be flexibly adjusted accordingly with the continuously updated action information of agents. Based on future action predictions, agents take coordinated actions to achieve Nash equilibrium coordination. We designed several mixed driving scenarios in the real world to test our model, and simulation results show that our model is efficient and flexible, compared with an optimal model and a heuristic model.

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Boosting Electrocatalytic Carbon Dioxide Reduction via Self-Relaxation of Asymmetric Coordination in Fe-Based Single Atom Catalyst

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Angewandte Chemie 2023年第6期136卷

作者： Zhaoyong Jin Dongxu Jiao Yilong Dong Lin Liu Jinchang Fan Ming Gong Xingcheng Ma Ying Wang Wei Zhang Prof. Lei Zhang Prof. Dr. Zhi Gen Yu Prof. Dr. Damien Voiry Weitao Zheng Prof. Dr. Xiaoqiang Cui School of Materials Science and Engineering Key Laboratory of Automobile Materials of MOE Electron Microscopy Center Jilin University 130012 Changchun China College of Chemistry Jilin University 130012 Changchun China Institute of High Performance Computing (IHPC) Agency for Science Technology and Research (A*STAR) 1 Fusionopolis Way #16-16 Connexis 138632 Singapore Singapore Institut Européen des Membranes IEM UMR 5635 Université Montpellier ENSCM CNRS 34000 Montpellier France

Addressing the limitations arising from the consistent catalytic behavior observed for various intermediates during the electrochemical carbon dioxide reduction reaction (CO 2 RR) poses a significant challenge in the optimization of catalytic activity. In this study, we aimed to address this challenge by constructing an asymmetric coordination Fe single atom catalyst (SCA) with a dynamically evolved structure. Our catalyst, consisting of a Fe atom coordinated with one S atom and three N atoms (Fe−S 1 N 3 ), exhibited exceptional selectivity (CO Faradaic efficiency of 99.02 %) and demonstrated a high intrinsic activity (TOF of 7804.34 h −1 ), and remarkable stability. Using operando XAFS spectra and Density Functional Theory (DFT) calculations, we elucidated the self-relaxation of geometric distortion and dynamic evolution of bond lengths within the catalyst. These structure changes enabled independent regulation of the *COOH and *CO intermediate adsorption energies, effectively breaking the linear scale relationship and enhancing the intrinsic activity of CO 2 RR. This study provides valuable insights into the dynamic evolution of SACs and paves the way for targeted catalyst designs aimed to disrupt the linear scaling relationships.

关键词： Asymmetric Coordination CO2 Reduction Reaction Dynamic Evolution Self-Relaxation Single Atom Catalysts

Does or did the supernova remnant Cassiopeia A operate as a PeVatron?

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arXiv 2023年

作者： Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, J.T. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, X.T. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.Y. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Huang, Z.C. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Ke, T. Kuleshov, D. Kurinov, K. Li, B.B. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, Jian Li, Jie Li, K. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Lu, R. Luo, Q. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, Z.W. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Sáiz, A. Semikoz, D. Shao, C.Y. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, Q.N. Sun, X.N. Sun, Z.B. Tam, P.H.T. Tang, Q.W. Tang, Z.B. Tian, W.W. Key Laboratory of Particle Astrophysics & Experimental Physics Division & Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China Tianfu Cosmic Ray Research Center Sichuan Chengdu610000 China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Key Laboratory of Cosmic Rays Tibet University Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Sun Yat-sen University Guangdong Zhuhai519000 China Sun Yat-sen University Guangdong Guangzhou510275 China Sun Yat-sen University Guangdong Zhuhai519000 China School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China Département de Physique Nucléaire et Corpusculaire Faculté de Sciences Université de Genève 24 Quai Ernest Ansermet Geneva1211 Switzerland Institute of Frontier and Interdis

For decades, supernova remnants (SNRs) have been considered the prime sources of Galactic Cosmic rays (CRs). But whether SNRs can accelerate CR protons to PeV energies and thus dominate CR flux up to the knee is currently under intensive theoretical and phenomenological debate. The direct test of the ability of SNRs to operate as CR PeVatrons can be provided by ultrahigh-energy (UHE;Eγ ≥ 100 TeV) γ-rays. In this context, the historical SNR Cassiopeia A (Cas A) is considered one of the most promising target for UHE observations. This paper presents the observation of Cas A and its vicinity by the LHAASO KM2A detector. The exceptional sensitivity of LHAASO KM2A in the UHE band, combined with the young age of Cas A, enabled us to derive stringent model-independent limits on the energy budget of UHE protons and nuclei accelerated by Cas A at any epoch after the explosion. The results challenge the prevailing paradigm that Cas A-type SNRs are major suppliers of PeV CRs in the Milky Way. © 2023, CC BY.

关键词： Gamma rays

Observing Geometry of Quantum states in a Three-Level System

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Physical Review Letters 2020年第15期125卷 150401-150401页

作者： Jie Xie Aonan Zhang Ningping Cao Huichao Xu Kaimin Zheng Yiu-Tung Poon Nung-Sing Sze Ping Xu Bei Zeng Lijian Zhang National Laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and Manipulation (Ministry of Education) College of Engineering and Applied Sciences and School of Physics Nanjing University Nanjing 210093 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing 210093 China Department of Mathematics & Statistics University of Guelph Guelph N1G 2W1 Ontario Canada Institute for Quantum Computing University of Waterloo Waterloo N2L 3G1 Ontario Canada Department of Mathematics Iowa State University Ames Iowa 50011 USA Department of Applied Mathematics The Hong Kong Polytechnic University 999077 Hong Kong China Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha 410073 China Department of Physics The Hong Kong University of Science and Technology Clear Water Bay Kowloon 999077 Hong Kong China

In quantum mechanics, geometry has been demonstrated as a useful tool for inferring nonclassical behaviors and exotic properties of quantum systems. One standard approach to illustrate the geometry of quantum systems is to project the quantum state space onto the Euclidean space via measurements of observables on the system. Despite the great success of this method in studying two-level quantum systems (qubits) with the celebrated Bloch sphere representation, it is still difficult to reveal the geometry of multidimensional quantum systems. Here we report the first experiment measuring the geometry of such projections beyond the qubit. Specifically, we observe the joint numerical ranges of a triple of observables in a three-level photonic system, providing a complete classification of these ranges. We further show that the geometry of different classes reveals ground-state degeneracies of a Hamiltonian as a linear combination of the observables, which is related to quantum phases in the thermodynamic limit. Our results offer a versatile geometric approach for exploring the properties of higher-dimensional quantum systems.

关键词： Geometric & topological phases Quantum foundations Quantum measurements Quantum phase transitions