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International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Yuan Liang Sibo Hu Xiwang Dong Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Beihang University Beijing P. R. China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing P. R. China

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

In this paper, the problem of distributed state estimation for nonlinear networked system with correlated noises is investigated. First, a distributed weighted consensus-based cubature information filtering algorithm is designed, of which the goal is to achieve accurate estimated states with the presence of correlated noises in a fully distributed fashion. Then based on the statistical linear approximation method, it is further proved that, the estimated states of the proposed filtering algorithm are consistent. Finally, the improved performance of the proposed filtering algorithm are confirmed by the numerical simulation.

关键词： Sensors Sensor fusion Noise measurement Sensor systems Wireless sensor networks State estimation Kalman filters

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Performance study of trial M-THGEM

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Radiation Detection Technology and Methods 2020年第1期4卷 78-82页

作者： Shao-Qing Deng Wen-Qi Yan Dao-Jin Hong Bo-Xiang Yu Gao-Long Zhang Yu-Guang Xie School of Physics and Nuclear Energy Engineering Beihang UniversityBeijing 100191China Institute of High Energy Physics Chinese Academy of SciencesBeijing 100049China University of Science and Technology of China Hefei 230026China State Key Laboratory of Particle Detection and Electronics Beijing 100049China University of Chinese Academy of Sciences Beijing 100049China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang UniversityBeijing 100083China

Background M-THGEM is a new type of electron multiplier,which is developed with a high gain,good stability and uniformity based on *** the successful application of small area M-THGEM,the large-area M-THGEM is proposed based on large-volume gas *** The production of large-area M-THGEM is difficult compared with the small one with more holes and more stable *** meet the requirements of large-area gas detectors,the performances of the large-area M-THGEM need to be measured and researched,which will provide a guidance on the process and design of the *** The M-THGEM membrane was loaded into a chamber to complete the test under the conditions of 55Fe/X-ray source(5.9 keV)and working gas Ar∶iC4H10=97∶*** performance of gain,energy resolution,uniformity and long-term stability can be *** Based on the small area M-THGEM,the research and design of large-area M-THGEM with 200×200 mm^(2)were *** basic performances were *** results show that the gain with the working gas of Ar∶iC_(4)H_(10)=97∶3 can reach to 6×10^(3),and the energy resolution of the^(55)Fe/X-ray source(5.9 keV)reaches 29.4%with a good gain uniformity and *** At present,the production and measurement of the large-area M-THGEM has been *** M-THGEM of 200×200 mm^(2)shows a good performance,which will provide many references for the future design.

关键词： M-THGEM Gain Energy resolution Stability

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Vehicle re-identification with location and time stamps 32

Vehicle re-identification with location and time stamps

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32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019

作者： Lv, Kai Du, Heming Hou, Yunzhong Deng, Weijian Sheng, Hao Jiao, Jianbin Zheng, Liang Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University University of Chinese Academy of Sciences Australian National University

ISBN: (纸本)9781728125060

This paper focuses on the problem of vehicle re-identification (Re-ID). In our attempt, we propose a re-identification framework by exploiting vehicle location and time stamps. The location and time information have the potential to cover the shortage of appearance-based feature representations. First, we introduce an ensemble technique to combine the informative cues of multiple Re-ID models effectively. To further improve the accuracy, we then build up a system to acquire the vehicle location and time stamps. Specifically, we utilize the detected results to obtain the needed information. With the help of the proposed system, we can remove irrelevant images from a given ranking list. Our system finished 3rd place in the 2019 AI-City challenge for city-scale multi-camera vehicle re-identification. © 2019 IEEE Computer Society. All rights reserved.

关键词： Vehicles

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Plantar fasciitis detection based on deep learning architecture 19

Plantar fasciitis detection based on deep learning architect...

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3rd International Conference on Medical and Health Informatics, ICMHI 2019

作者： Chien, Ting-Ying Hsieh, Yi-Ting Lee, Hou-Cheng Hsieh, Yun-Jui Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan Taichung Veterans General Hospital Taichung City Taiwan

ISBN: (纸本)9781450371995

Background: Plantar fasciitis is one of the most common foot pain problems in adults. The current diagnosis mainly relies on the inquiry of medical history and a physical examination of the body. In the objective laboratory examination, the blood test has not yet provided an effective diagnostic reference. In this study, we combine a deep learning algorithm architecture with thermal imaging to develop a plantar fasciitis medical decision system that predicts whether the patient has the condition. Methods: This study collected patient image-related data, including 360-degree thermal video and RGB images of the affected area (foot), and patient clinical data. In data preprocessing, we first adjust the thermal image data, based on the different detection environments. After data processing, we employed the Convolutional Neural Networks (CNN) deep learning architecture to develop a prediction model. Results: In total, 1,000 frames were used as the training dataset in this study - -300 cases that had the condition and 700 cases that did not. The results showed that the CNN model can effectively predict plantar fasciitis. The inflammatory response is often accompanied by redness and swelling. This study used thermal imaging to detect the temperature of the affected area, which it combined with a deep learning algorithm to successfully detect the inflammatory condition. In the future, this technique can be used to detect other inflammatory reactions such as wound healing and hemorrhoids. © 2019 ACM.

关键词： Big data

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Study on the effect of different electrode channel combinations of motor imagery EEG signals on classification accuracy

Study on the effect of different electrode channel combinati...

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7th International Symposium on Test Automation and Instrumentation, ISTAI 2018

作者： Zhu, Kai Wang, Shuai Zheng, Dezhi Dai, Mengxi School of Instrument Science and Optoelectronic Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data-based precision Medicine Beihang University Beijing China School of Computer Science Beihang University Beijing China

In order to improve the performance of motor imagery brain–computer interface (BCI) based on deep learning algorithm, here, the authors propose an electrode channel combination method. Although motor imagery electroencephalography (EEG) signals which contain different electrode channels on the scalp surface have an effect on the classification performance, the effect of different electrode channel combinations has not been systematically explored. With the two deep learning models the authors constructed, the authors list some different electrode channel combinations to classify the left fist and right fist motor imagery EEG signals. The results show that the more the number of channels in these combinations, the higher the classification accuracy. However, when the number of channels exceeds 11, the classification accuracy increases slowly, and the classification effect is rarely improved. Therefore, the authors obtain an optimal electrode channel combination to use the electrode channels efficiently and to improve the performance of motor imagery BCI based on deep learning algorithms. © 2019 Institution of engineering and Technology. All rights reserved.

关键词： Electrodes

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Transferring knowledge distillation for multilingual social event detection

arXiv

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arXiv 2021年

作者： Ren, Jiaqian Peng, Hao Jiang, Lei Wu, Jia Tong, Yongxin Wang, Lihong Bai, Xu Wang, Bo Yang, Qiang Institute of Information Engineering Chinese Academy of Sciences The School of Cyber Security University of Chinese Academy of Sciences Beijing100041 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China The School of Cyber Science and Technology Beihang University Beijing100083 China Institute of Information Engineering Chinese Academy of Sciences Beijing100041 China The Department of Computing Macquarie University Sydney Australia The State Key Laboratory of Software Development Environment The School of Computer Science and Engineering Beihang University Beijing100083 China The National Computer Network Emergency Response Technical Team Coordination Center of China Beijing100029 China The Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong AI Group WeBank Co. Ltd. China

Recently published graph neural networks (GNNs) show promising performance at social event detection tasks. However, most studies are oriented toward monolingual data in languages with abundant training samples. This has left the more common multilingual settings and lesser-spoken languages relatively unexplored. Thus, we present a GNN that incorporates cross-lingual word embeddings for detecting events in multilingual data streams. The first exploit is to make the GNN work with multilingual data. For this, we outline a construction strategy that aligns messages in different languages at both the node and semantic levels. Relationships between messages are established by merging entities that are the same but are referred to in different languages. Non-English message representations are converted into English semantic space via the cross-lingual word embeddings. The resulting message graph is then uniformly encoded by a GNN model. In special cases where a lesser-spoken language needs to be detected, a novel cross-lingual knowledge distillation framework, called CLKD, exploits prior knowledge learned from similar threads in English to make up for the paucity of annotated data. Experiments on both synthetic and real-world datasets show the framework to be highly effective at detection in both multilingual data and in languages where training samples are scarce. © 2021, CC BY.

关键词： Embeddings

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Adaptive Handover Decision Inspired By Biological Mechanism in Vehicle Ad-hoc Networks

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Computers, Materials & Continua 2019年第9期61卷 1117-1128页

作者： Xuting Duan Jingyi Wei Daxin Tian Jianshan Zhou Haiying Xia Xin Li Kunxian Zheng Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing100191China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems&SafetyControl Beijing100191China School of Transportation Science and Engineering Beihang UniversityBeijing100191China Department of Engineering and Design University of SussexBrightonBN19RHUK Research Institute of Highway Ministry Transport Beijing100088China Department of Computer Science and Technology Tsinghua UniversityHaidian DistrictBeijing100088China

In vehicle ad-hoc networks(VANETs),the proliferation of wireless communication will give rise to the heterogeneous access environment where network selection becomes *** by the self-adaptive paradigm of cellular attractors,this paper regards an individual communication as a cell,so that we can apply the revised attractor selection model to induce each connected *** at improving the Quality of Service(QoS),we presented the bio-inspired handover decision-making *** addition,we employ the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)for any vehicle to choose an access *** paper proposes a novel framework where the bio-inspired mechanism is combined with *** a dynamic and random mobility environment,our method achieves the coordination of performance of heterogeneous networks by guaranteeing the efficient utilization and fair distribution of network resources in a global *** experimental results confirm that the proposed method performs better when compared with conventional schemes.

关键词： Revised attraction selection model TOPSIS VANETs QoS

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Network controllability of structural connectomes in the neonatal brain

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Nature Communications 2023年第1期14卷 1-10页

作者： Sun, Huili Jiang, Rongtao Dai, Wei Dufford, Alexander J. Noble, Stephanie Spann, Marisa N. Gu, Shi Scheinost, Dustin Department of Biomedical Engineering Yale University New Haven 06520 CT United States Department of Radiology & Biomedical Imaging Yale School of Medicine New Haven 06510 CT United States Department of Biostatistics Yale School of Public Health New Haven 06510 CT United States Department of Psychiatry and Center for Mental Health Innovation Oregon Health & Science University Portland 97239 OR United States Department of Psychology Northeastern University Boston 02115 MA United States Department of Bioengineering Northeastern University Boston 02115 MA United States Center for Cognitive and Brain Health Northeastern University Boston United States Department of Psychiatry Vagelos College of Physicians and Surgeons Columbia University New York 10032 NY United States New York State Psychiatric Institute New York 10032 NY United States School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen China Department of Statistics & Data Science Yale University New Haven 06520 CT United States Child Study Center Yale School of Medicine New Haven 06510 CT United States Wu Tsai Institute Yale University 100 College Street New Haven 06510 CT United States

White matter connectivity supports diverse cognitive demands by efficiently constraining dynamic brain activity. This efficiency can be inferred from network controllability, which represents the ease with which the brain moves between distinct mental states based on white matter connectivity. However, it remains unclear how brain networks support diverse functions at birth, a time of rapid changes in connectivity. Here, we investigate the development of network controllability during the perinatal period and the effect of preterm birth in 521 neonates. We provide evidence that elements of controllability are exhibited in the infant’s brain as early as the third trimester and develop rapidly across the perinatal period. Preterm birth disrupts the development of brain networks and altered the energy required to drive state transitions at different levels. In addition, controllability at birth is associated with cognitive ability at 18 months. Our results suggest network controllability develops rapidly during the perinatal period to support cognitive demands but could be altered by environmental impacts like preterm birth. © 2023, Springer Nature Limited.

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Measurement of the Eu( ) cross section up to 500 keV at the CSNS Back-n facility, and the stellar Eu( ) cross section at s-process temperatures

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The European Physical Journal A 2022年第12期58卷 1-16页

作者： Li, Xiankai An, Zhendong Jiang, Wei Yang, Gaole Qiu, Weiwei Liao, Zhengfa Zhuang, Ziyue Zhang, Xiaoping Chen, Shengli Guo, Chenchen Xiao, Erxi Fang, Xiao Li, Xinxiang Wang, Hongwei Hu, Xinrong Jiang, Bing Shen, Wenqing Wang, Jincheng Ren, Jie Ruan, Xichao Wang, Dexin Zhang, Su-Yalatu Luo, Wen Zhu, Zhichao Lan, Haoyang Cao, Zongwei Ma, Xu Liu, Yingdu Wang, Pusen Yang, Yi Su, Ping Deng, Xiangai He, Wanbing Ma, Yugang Ma, Chunwang Wang, Yuting Dai, Zhitao Li, Ertao He, Pengqin Tang, RenGuang Zhou, Tao Wang, Jing Yi, Han Zhang, Yue Chen, Yonghao Fan, Ruirui Gao, Keqing Li, Qiang Sun, Kang Tan, Zhixin Gu, Minhao Jing, Hantao Tang, Jingyu School of Nuclear Science and Technology University of South China Hengyang China School of Physics and Astronomy Sun Yat-sen University Zhuhai China Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai China State Key Laboratory of Lunar and Planetary Sciences Macau University of Science and Technology Macau China Institute of High Energy Physics Chinese Academy of Sciences Beijing China Spallation Neutron Source Science Center Dongguan China CNSA Macau Center for Space Exploration and Science Macau China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-sen University Zhuhai China University of Chinese Academy of Sciences Beijing China Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China Key Laboratory of Nuclear Data China Institute of Atomic Energy Beijing China College of Mathematics and Physics Inner Mongolia Minzu University Tongliao China Institute of Nuclear Physics Inner Mongolia Minzu University Tongliao China State Key Laboratory of Nuclear Physics and Technology and CAPT Peking University Beijing China Beijing Laser Acceleration Innovation Center Huairou Beijing China Shool of Materials Science and Engineering Xiangtan University Xiangtan China Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) Institute of Modern PhysicsDepartment of Nuclear Science and Technology Fudan University Shanghai China Institute of Particle and Nuclear Physics Henan Normal University Xinxiang China School of Physics Henan Normal University Xinxiang China Shenzhen Center Cancer hospital Chinese Academy of Medical Sciences Shenzhen China Institute for Advanced Study in Nuclear Energy and Safety College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen China

In nuclear astrophysics, the nuclides $$^{151}$$ Eu and $$^{153}$$ Eu are both in the path of the s-process, and their (n, $$\gamma $$ ) cross sections are important input parameters for the calculation of the nuclear astrophysics network. According to the EXFOR database, the neutron capture cross section of natural europium in the resonance region has not been fully measured. The (n, $$\gamma $$ ) cross section of $$^{nat}$$ Eu was measured using the time-of-flight (TOF) technique at the Back-n white neutron source facility of the China Spallation Neutron Source (CSNS) in the 1 eV–to 500 keV range. Four C $$_{6}$$ D $$_{6}$$ liquid scintillator detectors and pulse height weighting techniques were used to measure prompt $$\gamma $$ rays and analyze the data. The results of the analysis were compared with the evaluated data of ENDF/B-VIII.0 and JENDL-5.0. It shows that there are some differences between the measurement results and different evaluated data libraries. The resonance parameters of $$^{151}$$ Eu and $$^{153}$$ Eu were extracted in the 1 eV–150 eV region using the R-Matrix code SAMMY. The accurate Maxwellian-averaged capture cross section (MACS) is derived over the temperature range of the s-process nucleosynthesis model. The result shows that at kT=30 keV, the MACS value of $$^{151}$$ Eu is 3417 ± 297 mb and the value of $$^{153}$$ Eu is 2718 ± 237 mb.

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A review of progress in coupled ocean-atmosphere model developments for ENSO studies in China

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Journal of Oceanology and Limnology 2020年第4期38卷 930-961页

作者： ZHANG Rong-Hua YU Yongqiang SONG Zhenya REN Hong-Li TANG Youmin QIAO Fangli WU Tongwen GAO Chuan HU Junya TIAN Feng ZHU Yuchao CHEN Lin LIU Hailong LIN Pengfei WU Fanghua WANG Lin Key Laboratory of Ocean Circulation and Waves Institute of Oceanologyand Center for Ocean Mega-ScienceChinese Academy of SciencesQingdao 266071China Laboratory for Ocean and Climate Dynamics Pilot National Laboratory for Marine Science and TechnologyQingdao 266237China Center for Excellence in Quaternary Science and Global Change Chinese Academy of SciencesXi’an 710061China University of Chinese Academy of Sciences Beijing 100049China LASG Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100049China First Institute of Oceanography Ministry of Natural ResourcesQingdao 266061China Laboratory for Regional Oceanography and Numerical Modeling Pilot National Laboratory for Marine Science and TechnologyQingdao 266237China Key Laboratory of Marine Science and Numerical Modeling(MASNUM) Ministry of Natural ResourcesQingdao 266061China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Qingdao 266061China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Laboratory for Climate Studies and CMA-NJU Joint Laboratory for Climate Prediction Studies National Climate CenterChina Meteorological AdministrationBeijing 100081China Environmental Science and Engineering University of Northern British ColumbiaBritish Columbia V2N 4Z9Canada State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou 310012China Key Laboratory of Meteorological Disaster Ministry of Education(KLME)and Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science and TechnologyNanjing 210044China Beijing Climate Center China Meteorological AdministrationBeijing 100081China

El Nino-Southern Oscillation(ENSO) is the strongest interannual signal that is producedby basinscale processes in the tropical Pacific,with significant effects on weather and climate *** the past,extensive and intensive international efforts have been devoted to coupled model developments for ENSO studies.A hierarchy of coupled ocean-atmo sphere models has been formulated;in terms of their complexity,they can be categorized into intermediate coupled models(ICMs),hybrid coupled models(HCMs),and fully coupled general circulation models(CGCMs).ENSO modeling has made significant progress over the past decades,reaching a stage where coupled models can now be used to successfully predict ENSO events 6 months to one year in ***,ENSO exhibits great diversity and complexity as observed in nature,which still cannot be adequately captured by current state-of-the-art coupled models,presenting a challenge to ENSO *** primarily reviewed the long-term efforts in ENSO modeling continually and steadily made at different institutions in China;some selected representative examples are presented here to review the current status of ENSO model developments and applications,which have been actively pursued with noticeable progress being made *** ENSO simulations are very sensitive to model formulations and process representations etc.,dedicated efforts have been devoted to ENSO model developments and ***,different ocean-atmosphere coupled models have been available in China,which exhibit good model performances and have already had a variety of applications to climate modeling,including the Coupled Model Intercomparison Project Phase 6(CMIP6).Nevertheless,large biases and uncertainties still exist in ENSO simulations and predictions,and there are clear rooms for their improvements,which are still an active area of researches and ***,model performances of ENSO simulations are assessed in terms of advantages and disadvantage

关键词： El Niño-Southern Oscillation(ENSO) coupled ocean-atmosphere models simulations and predictions model biases and uncertainties

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