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2019 IEEE Global Communications Conference (GLOBECOM)

作者： Di Wu Huiyong Li Xuefeng Liu Jianwei Niu State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC) Beihang University Hangzhou Innovation Research Institute Beihang University

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Gesture recognition systems based on myoelectric signal have raised more and more attention from researchers. Traditional gesture recognition methods are susceptible to multiple types of noise and require a large number of features, which increase overhead and decrease recognition efficiency. Fully utilizing the characteristics of the signal to recognize gestures is a big challenge. This paper proposes an improved empirical mode decomposition method (XB-EMD) based on autocorrelation function to denoise myoelectric signal. In addition, a novel deep neural network (CRNet) which combines the CNN and RNN layers together is trained for classifying the gestures based on denoised myoelectric signal. Experimental results show that the proposed gesture recognition system can improve recognition effectiveness at 97.4\% with 10 typical gestures, and 72.55\% with 16 complicated gestures.

关键词： Correlation Gesture recognition Feature extraction Empirical mode decomposition Recurrent neural networks Sensors

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Feature Extraction of Electric Information Acquisition System Based on Haar Wavelet Transform 2

Feature Extraction of Electric Information Acquisition Syste...

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2017 IEEE 2nd International Conference on big data Analysis（ICBDA 2017）

作者： Ting Zhao Jiangqi Chen Di Zhang Yang Yang Advanced Computing and Big Data Technology Laboratory of SGCC Global Energy Interconnection Research Institute School of Control and Computer Engineering North China Electric Power University

ISBN: (纸本)9781509036202

This paper studies the structure features of the collected power consumers' power consumption data,in which the 96 measured data points indicating a single user's power consumption curve of a *** 96 measured data points are taken as 96 variables for *** dimensionality of original data is reduced by principal component analysis(PCA),and then the K-means algorithm is employed to cluster the original time-series load data of power *** detail,Haar wavelet transform is adopted to provide a five-level multi-resolution decomposition of the original load data,from which 93 Haar coefficients and 3 scale coefficients are *** cluster result is taken as category labels,and the standardized 93 coefficients and 3 scale coefficients as dependent variables,a classification model based on C5.0 algorithm is established to confirm the Haar scale coefficients as characteristic quantity of power consumption ***,the data acquisition is simplified and storage space *** method could also be adopted for feature extraction of tremendous detail data and indicator data in power system,with potential application value and economic benefit.

关键词： electricity information collection data wavelet transform C5.0 algorithm K-means algorithm

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Residual Networks for Light Field Image Super-Resolution

Residual Networks for Light Field Image Super-Resolution

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IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Shuo Zhang Youfang Lin Hao Sheng Beijing Key Lab of Traffic Data Analysis and Mining School of Computer and Information Technology Beijing Jiaotong University Key Laboratory of Intelligent Passenger Service of Civil Aviation CAAC State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

Light field cameras are considered to have many potential applications since angular and spatial information is captured simultaneously. However, the limited spatial resolution has brought lots of difficulties in developing related applications and becomes the main bottleneck of light field cameras. In this paper, a learning-based method using residual convolutional networks is proposed to reconstruct light fields with higher spatial resolution. The view images in one light field are first grouped into different image stacks with consistent sub-pixel offsets and fed into different network branches to implicitly learn inherent corresponding relations. The residual information in different spatial directions is then calculated from each branch and further integrated to supplement high-frequency details for the view image. Finally, a flexible solution is proposed to super-resolve entire light field images with various angular resolutions. Experimental results on synthetic and real-world datasets demonstrate that the proposed method outperforms other state-of-the-art methods by a large margin in both visual and numerical evaluations. Furthermore, the proposed method shows good performances in preserving the inherent epipolar property in light field images.

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Unveiling Dark Matter free-streaming at the smallest scales with high redshift Lyman-alpha forest

arXiv

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arXiv 2023年

作者： Iršič, Vid Viel, Matteo Haehnelt, Martin G. Bolton, James S. Molaro, Margherita Puchwein, Ewald Boera, Elisa Becker, George D. Gaikwad, Prakash Keating, Laura C. Kulkarni, Girish Kavli Institute for Cosmology University of Cambridge Madingley Road CambridgeCB3 0HA United Kingdom Cavendish Laboratory University of Cambridge 19 J. J. Thomson Ave. CambridgeCB3 0HE United Kingdom SISSA- International School for Advanced Studies Via Bonomea 265 Trieste34136 Italy INFN - National Institute for Nuclear Physics Via Valerio 2 TriesteI-34127 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy INAF Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 TriesteI-34131 Italy ICSC - Centro Nazionale di Ricerca in High Performance Computing Big Data e Quantum Computing Via Magnanelli 2 Bologna Italy Institute of Astronomy University of Cambridge Madingley Road CambridgeCB3 0HA United Kingdom School of Physics and Astronomy University of Nottingham University Park NottinghamNG7 2RD United Kingdom Leibniz-Institut für Astrophysik Potsdam An der Sternwarte 16 Potsdam14482 Germany Department of Physics and Astronomy University of California RiversideCA92521 United States Max-Planck-Institut für Astronomie Königstuhl 17 HeidelbergD-69117 Germany Institute for Astronomy University of Edinburgh Blackford Hill EdinburghEH9 3HJ United Kingdom Tata Institute of Fundamental Research Homi Bhabha Road Mumbai400005 India

This study introduces novel constraints on the free-streaming of thermal relic warm dark matter (WDM) from Lyman-α forest flux power spectra. Our analysis utilises a high-resolution, high-redshift sample of quasar spectra observed using the HIRES and UVES spectrographs (z = 4.2 − 5.0). We employ a Bayesian inference framework and a simulation-based likelihood that encompasses various parameters including the free-streaming of dark matter, cosmological parameters, the thermal history of the intergalactic medium, and inhomogeneous reionization, to establish lower limits on the mass of a thermal relic WDM particle of 5.7 keV (at 95% C.L.). This result surpasses previous limits from the Lyman-α forest through reduction of the measured uncertainties due to a larger statistical sample and by measuring clustering to smaller scales (kmax = 0.2 km−1 s). The approximately two-fold improvement due to the expanded statistical sample suggests that the effectiveness of Lyman-α forest constraints on WDM models at high redshifts are limited by the availability of high-quality quasar spectra. Restricting the analysis to comparable scales and thermal history priors as in prior studies (kmax −1 s) lowers the bound on the WDM mass to 4.1 keV. As the precision of the measurements increases, it becomes crucial to examine the instrumental and modelling systematics. On the modelling front, we argue that the impact of the thermal history uncertainty on the WDM particle mass constraint has diminished due to improved independent observations. At the smallest scales, the primary source of modeling systematic arises from the structure in the peculiar velocity of the intergalactic medium and inhomogeneous reionization. © 2023, CC BY.

关键词： Galaxies

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Distributed cooperative guidance for maneuvering targets with directed conmunication topologies

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Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica 2020年 41卷

作者： Dong, Xiaofei Ren, Zhang Chi, Qingxi Li, Qingdong School of Automation Science and Electrical Engineering Beihang University Beijing100083 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Science and Technology on Aircraft Control Laboratory Beihang University Beijing100083 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China

This paper studies the distributed cooperative guidance for maneuvering targets with directed communication topologies. First, a guidance system model is established based on the geometric relationship between the aircraft and the target, in which the nonlinear problem is solved by feedback linearization. In this design, the unknown maneuver of the target is observed by the extended state observer, and the estimation of the unknown maneuver of the target is applied to the design of the guidance law. In this process, the influence of the target maneuvering on the time-to-go is eliminated by means of direct compensation. Then, the designed guidance law is brought into the guidance model, transforming the problem of cooperative guidance into the problem of consensus. Next, the necessary and sufficient conditions for the convergence of the designed cooperative guidance law are obtained by conducting the pole analysis. Finally, the designed cooperative guidance law and the method of the parameter selection are analyzed by adopting the simulation analysis. © 2020, Beihang University Aerospace Knowledge Press. All right reserved.

关键词： State estimation

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Coherent H ∞ control for Markovian jump linear quantum systems

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IFAC-PapersOnLine 2020年第2期53卷 269-274页

作者： Yanan Liu Daoyi Dong Ian R. Petersen Qing Gao Steven X. Ding Hidehiro Yonezawa School of Engineering and Information Technology University of New South Wales Canberra ACT 2600 Australia Center for Quantum Computation and Communication Technology Australian Research Council Canberra ACT 2600 Australia Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen. 47057 Duisburg Germany Research School of Electrical Energy and Materials Engineering The Australian National University Canberra ACT 2601 Australia School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing and also with Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China

The purpose of this paper is to design a coherent feedback controller for a Markovian jump linear quantum system suffering from a fault signal. The control objective is to bound the effect of the disturbance input on the output for the time-varying quantum system. We prove the relation between the H ∞ control problem, the dissipation properties, and the solutions of Riccati differential equations, by which the H ∞ controller of the Markovian jump linear quantum system is given by the solutions of Linear Matrix Inequalities (LMIs).

关键词： Coherent quantum feedback H∞ control fault-tolerant control Markovian jump linear quantum systems

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Deep learning for image and point cloud fusion in autonomous driving: A review

arXiv

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arXiv 2020年

作者： Cui, Yaodong Chen, Ren Chu, Wenbo Chen, Long Tian, Daxin Li, Ying Cao, Dongpu The Waterloo CogDrive Lab Department of Mechanical and Mechatronics Engineering University of Waterloo 200 University Ave West WaterlooONN2L3G1 Canada Research Institute Co. Ltd. Beijing100176 China School of Data and Computer Science Sun Yat-sen University Zhuhai519082 China Waytous Inc. Qingdao266109 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

Autonomous vehicles were experiencing rapid development in the past few years. However, achieving full autonomy is not a trivial task, due to the nature of the complex and dynamic driving environment. Therefore, autonomous vehicles are equipped with a suite of different sensors to ensure robust, accurate environmental perception. In particular, the camera-LiDAR fusion is becoming an emerging research theme. However, so far there has been no critical review that focuses on deep-learning-based camera-LiDAR fusion methods. To bridge this gap and motivate future research, this paper devotes to review recent deep-learning-based data fusion approaches that leverage both image and point cloud. This review gives a brief overview of deep learning on image and point cloud data processing. Followed by in-depth reviews of camera-LiDAR fusion methods in depth completion, object detection, semantic segmentation, tracking and online cross-sensor calibration, which are organized based on their respective fusion levels. Furthermore, we compare these methods on publicly available datasets. Finally, we identified gaps and over-looked challenges between current academic researches and real-world applications. Based on these observations, we provide our insights and point out promising research directions. Copyright © 2020, The Authors. All rights reserved.

关键词： Object detection

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Impact of temperature and relative humidity on the transmission of COVID-19: A modeling study in China and the United States

arXiv

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arXiv 2020年

作者： Wang, Jingyuan Tang, Ke Feng, Kai Lin, Xin Lv, Weifeng Chen, Kun Wang, Fei School of Computer Science and Engineering Beihang University China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University China School of Social Sciences Tsinghua University China State Key Laboratory of Software Development Environment Beihang University China Department of Statistics University of Connecticut United States Center for Population Health University of Connecticut Health Center United States Department of Population Health Sciences Weill Cornell Medical College Cornell University United States

Objectives We aim to assess the impact of temperature and relative humidity on the transmission of COVID-19 across communities after accounting for community-level factors such as demographics, socioeconomic status, and human mobility status. Design A retrospective cross-sectional regression analysis via the Fama-MacBeth procedure is adopted. Setting We use the data for COVID-19 daily symptom-onset cases for 100 Chinese cities and COVID-19 daily confirmed cases for 1,005 U.S. counties. Participants A total of 69,498 cases in China and 740,843 cases in the U.S. are used for calculating the effective reproductive numbers. Primary outcome measures Regression analysis of the impact of temperature and relative humidity on the effective reproductive number (R value). Results Statistically significant negative correlations are found between temperature/relative humidity and the effective reproductive number (R value) in both China and the U.S. Conclusions Higher temperature and higher relative humidity potentially suppress the transmission of COVID-19. Specifically, an increase in temperature by 1 degree Celsius is associated with a reduction in the R value of COVID-19 by 0.026 (95% CI [-0.0395,-0.0125]) in China and by 0.020 (95% CI [-0.0311, -0.0096]) in the U.S.;an increase in relative humidity by 1% is associated with a reduction in the R value by 0.0076 (95% CI [-0.0108,-0.0045]) in China and by 0.0080 (95% CI [-0.0150,-0.0010]) in the U.S. Therefore, the potential impact of temperature/relative humidity on the effective reproductive number alone is not strong enough to stop the pandemic. Copyright © 2020, The Authors. All rights reserved.

关键词： Regression analysis

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An advanced Quantum-Resistant Signature Scheme for Cloud Based on Eisenstein Ring

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Computers, Materials & Continua 2018年第7期56卷 19-34页

作者： Faguo Wu Xiao Zhang Wang Yao Zhiming Zheng Lipeng Xiang Wanpeng Li Key Laboratory of Mathematics Informatics and Behavioral SemanticsMinistry of EducationSchool of Mathematics and Systems ScienceBeihang UniversityBeijing100191China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing100191China The Fifth Electronics Research Institute of Ministry of Industry and Information Technology Guangzhou510610China Department of Electrical and Electronic Engineering City University of LondonUK

Signature,widely used in cloud environment,describes the work as readily identifying its *** existing signature schemes in the literature mostly rely on the Hardness assumption which can be easily solved by quantum *** this paper,we proposed an advanced quantum-resistant signature scheme for Cloud based on Eisenstein Ring(ETRUS)which ensures our signature scheme proceed in a lattice with higher *** proved that ETRUS highly improve the performance of traditional lattice signature ***,the Norm of polynomials decreases significantly in ETRUS which can effectively reduce the amount of polynomials convolution ***,storage complexity of ETRUS is smaller than classical ***,according to all convolution of ETRUS enjoy lower degree polynomials,our scheme appropriately accelerate 56.37%speed without reducing its security level.

关键词： Signature quantum-resistant Eisenstein Ring ETRUS

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Erratum: “Surface anisotropy induced spin wave nonreciprocity in epitaxial La0.33Sr0.67MnO3 film on SrTiO3 substrate” [Appl. Phys. Lett. 117, 232402 (2020)]

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Applied Physics Letters 2021年第18期119卷

作者： Jianyu Zhang Arjan Auke Burema Jilei Chen Junfeng Hu Chenyang Guo Hanchen Wang Ningsheng Li Bohang Wei Xiufeng Han Tamalika Banerjee Haiming Yu 1Fert Beijing Institute School of Microelectronics Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China 2University of Groningen Zernike Institute for Advanced Materials 9747 AG Groningen The Netherlands 3Beijing National Laboratory for Condensed Matter Physics Institute of Physics University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing 100190 China

In the original published article,1 the concentrations of La and Sr are reversed. The correct concentration should be La0.67Sr0.33MnO3 (which is in the ferromag

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