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The GECAM Real-time Burst Alert System

Research in Astronomy and Astrophysics 2024年第10期24卷 36-47页

作者： Yue Huang Dongli Shi Xiaolu Zhang Xiang Ma Peng Zhang Shijie Zheng Liming Song Xiaoyun Zhao Wei Chen Rui Qiao Xinying Song Jin Wang Ce Cai Shuo Xiao Yanqiu Zhang Shaolin Xiong Key Laboratory of Particle Astrophysics Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China Southwest Jiaotong University Chengdu 611756China Qufu Normal University Qufu 273165China College of Electronic and Information Engineering Tongji UniversityShanghai 201804China College of Physics and Hebei Key Laboratory of Photophysics Research and Application Hebei Normal UniversityShijiazhuang 050024China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal UniversityGuiyang 550001China University of Chinese Academy of Sciences Chinese Academy of SciencesBeijing 100049China

Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor(GECAM),consisting of two microsatellites,is designed to detect gamma-ray bursts associated with gravitational-wave ***,we introduce the real-time burst alert system of GECAM,with the adoption of the BeiDou-3 short message communication *** present the post-trigger operations,the detailed ground-based analysis,and the performance of the *** the first year of the in-flight operation,GECAM was triggered by 42 gamma-ray *** GECAM real-time burst alert system has the ability to distribute the alert within~1 minute after being triggered,which enables timely follow-up observations.

关键词： (stars:)gamma-ray burst:general gravitational waves methods:data analysis

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Research on Human Eyesight Tracking Algorithm Based on Monocular Vision 2nd

Research on Human Eyesight Tracking Algorithm Based on Monoc...

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2nd World Conference on Intelligent and 3D Technologies, WCI3DT 2023

作者： Tang, Haochun Zhang, Jindong Yang, Jing College of Software Jilin University Changchun130012 China College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun130012 China

ISBN: (纸本)9789819970100

This paper focuses on the optimization and improvement of the line-of-sight tracking algorithm based on monocular vision, and aims to achieve a series of complex functions through image analysis based on line-of-sight tracking technology and more in-depth analysis of monocular images. Therefore, we use the webgaze framework and use face detection models and feature point recognition libraries to analyze the recognition rate and provide further development of the technology. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Face recognition

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Prediction of turbulent channel flow using Fourier neural operator-based machine-learning strategy

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Physical Review Fluids 2024年第8期9卷 084604-084604页

作者： Yunpeng Wang Zhijie Li Zelong Yuan Wenhui Peng Tianyuan Liu Jianchun Wang Department of Mechanics and Aerospace Engineering Guangdong Provincial Key Laboratory of Turbulence Research and Applications Guangdong-Hong Kong-Macao Joint Laboratory for Data-Driven Fluid Mechanics and Engineering Applications Qingdao Innovation and Development Base Qingdao 266000 China The College of Engineering

Fast and accurate predictions of turbulent flows are of great importance in the science and engineering field. In this paper, we investigate the implicit U-Net enhanced Fourier neural operator (IUFNO) in the stable prediction of long-time dynamics of three-dimensional (3D) turbulent channel flows. The trained IUFNO models are tested in the large-eddy simulations (LES) at coarse grids for three friction Reynolds numbers: Reτ≈180, 395, and 590. The adopted near-wall mesh grids are tangibly coarser than the general requirements for wall-resolved LES. Compared to the original Fourier neural operator (FNO), the implicit FNO (IFNO), and U-Net enhanced FNO (UFNO), the IUFNO model has a much better long-term predictive ability. The numerical experiments show that the IUFNO framework outperforms the traditional dynamic Smagorinsky model and the wall-adapted local eddy-viscosity model in the predictions of a variety of flow statistics and structures, including the mean and fluctuating velocities, the probability density functions (PDFs) and joint PDF of velocity fluctuations, the Reynolds stress profile, the kinetic energy spectrum, and the Q-criterion (vortex structures). Meanwhile, the trained IUFNO models are computationally much faster than the traditional LES models. Thus, the IUFNO model is a promising approach for the fast prediction of wall-bounded turbulent flow.

关键词： Turbulence Large eddy simulations Machine learning

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Research and Implementation of OFC-Based Multicarrier Sliceable Bandwidth Variable Transponders in Hybrid Laser/Microwave Satellite Networks

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IEEE Access 2025年 13卷 93046-93056页

作者： Bin Wu Hao Zhang Qingchun Zhao Hebei Key Laboratory of Marine Perception Network and Data Processing School of Computer and Communication Engineering Northeastern University at Qinhuangdao Qinhuangdao China

In this paper, a multicarrier sliceable bandwidth variable transponder based on optical frequency comb (OFC) is proposed. The structure of the transponder’s internal switching unit is designed, and the principle of generating ultra-flat OFC based on a standalone dual-parallel Mach-Zehnder modulator (DPMZM) is analyzed. A scheme for dynamic allocation of multi-channel frequency slots and flexible resource configuration in hybrid laser/satellite networks is provided, and an experimental system is built to test the data transmission and bandwidth allocation capabilities of laser and microwave links. Experimental results indicate that the muticarrier generation unit can produce a 7-line flat OFC with a flatness of 1.6 dB, and the switching unit can achieve channel switching and frequency slot allocation, with a minimum slice width of 12.5 GHz. After passing through this node, the phase noise of the 2 GHz IF signal with frequency offsets at 10 kHz and 100 kHz are −59.28 dBc/Hz and −87.95 dBc/Hz, respectively, and the bit error rates (BERs) of the recovered baseband data from the laser and microwave links are less than $10^{-9}$ . These results validate the feasibility of the designed transponder to be applied in the key relay nodes of satellite networks. The proposed scheme can solve the problems of low spectrum utilization and the inability to dynamically allocate resources in traditional WDM satellite networks.

关键词： Satellites Transponders Masers Optical switches Frequency modulation Bandwidth Resource management Optical filters Microwave communication Optical fiber communication

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A molecular probe carrying anti-tropomyosin 4 for early diagnosis of cerebral ischemia/reperfusion injury

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Neural Regeneration Research 2023年第6期18卷 1321-1324页

作者： Teng-Fei Yu Kun Wang Lu Yin Wen-Zhe Li Chuan-Ping Li Wei Zhang Jie Tian Wen He Department of Ultrasound Beijing Tiantan HospitalCapital Medical UniversityBeijingChina CAS Key Laboratory of Molecular Imaging Institute of AutomationChinese Academy of SciencesBeijingChina State Key Laboratory of Natural and Biomimetic Drugs School of Pharmaceutical SciencesPeking UniversityBeijingChina Anhui Province Key Laboratory of Functional Coordinated Complexes for Materials Chemistry and Application School of Chemical and Environmental EngineeringAnhui Polytechnic UniversityWuhuAnhui ProvinceChina Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Engineering MedicineBeihang UniversityBeijingChina

In vivo imaging of cerebral ischemia/reperfusion injury remains an important *** injected porous Ag/Au@SiO_(2) bimetallic hollow nanoshells carrying anti-tropomyosin 4 as a molecular probe into mice with cerebral ischemia/reperfusion injury and observed microvascular changes in the brain using photoacoustic imaging with *** each measured time point,the total photoacoustic signal was significantly higher on the affected side than on the healthy *** hours after reperfusion,cerebral perfusion on the affected side increased,cerebrovascular injury worsened,and anti-tropomyosin 4 expression ***-four hours after reperfusion and later,perfusion on the affected side declined slowly and stabilized after 1 week;brain injury was also *** and immunohistochemical examinations confirmed the brain injury tissue *** nanoshell molecular probe carrying anti-tropomyosin 4 has potential for use in early diagnosis of cerebral ischemia/reperfusion injury and evaluating its progression.

关键词： cerebral ischemia/reperfusion injury diagnosis dynamic monitoring ischemic stroke middle cerebral artery occlusion molecular probe nanoshells photoacoustic imaging tropomyosin 4 ultrasound

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Local and Global Feature-Aware Dual-Branch Networks for Plant Disease Recognition

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植物表型组学（英文） 2024年第4期6卷 828-840页

作者： Jianwu Lin Xin Zhang Yongbin Qin Shengxian Yang Xingtian Wen Tomislav Cernava Quirico Migheli Xiaoyulong Chen Text Computing & Cognitive Intelligence Engineering Research Center of National Education Ministry College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China Guizhou-Europe Environmental Biotechnology and Agricultural Informatics Oversea Innovation Center in Guizhou University Guizhou Provincial Science and Technology DepartmentGuiyang 550025China Text Computing & Cognitive Intelligence Engineering Research Center of National Education Ministry College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China Guizhou-Europe Environmental Biotechnology and Agricultural Informatics Oversea Innovation Center in Guizhou University Guizhou Provincial Science and Technology DepartmentGuiyang 550025China College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China School of Biological Sciences Faculty of Environmental and Life SciencesUniversity of SouthamptonSouthampton S017 1BJUK Dipartimento di Agraria and NRD-Nucleo di Ricerca sulla Desertificazione Università degli Studi di SassariSassariItaly Guizhou-Europe Environmental Biotechnology and Agricultural Informatics Oversea Innovation Center in Guizhou University Guizhou Provincial Science and Technology DepartmentGuiyang 550025China College of Life Sciences Guizhou UniversityGuiyang 550025China

Accurate identification of plant diseases is important for ensuring the safety of agricultural *** neural networks(CNNs)and visual transformers(VTs)can extract effective representations of images and have been widely used for the intelligent recognition of plant disease ***,CNNs have excellent local perception with poor global perception,and VTs have excellent global perception with poor local *** makes it difficult to further improve the performance of both CNNs and VTs on plant disease recognition *** this paper,we propose a local and global feature-aware dual-branch network,named LGNet,for the identification of plant *** specifically,we first design a dual-branch structure based on CNNs and VTs to extract the local and global ***,an adaptive feature fusion(AFF)module is designed to fuse the local and global features,thus driving the model to dynamically perceive the weights of different ***,we design a hierarchical mixed-scale unit-guided feature fusion(HMUFF)module to mine the key information in the features at different levels and fuse the differentiated information among them,thereby enhancing the model's multiscale perception ***,extensive experiments were conducted on the Al Challenger 2018 dataset and the self-collected corn disease(SCD)*** experimental results demonstrate that our proposed LGNet achieves state-of-the-art recognition performance on both the Al Challenger 2018 dataset and the SCD dataset,with accuracies of 88.74％and 99.08％,respectively.

关键词： global plant disease dual-branch feature-aware local networks recognition

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Semi-Supervised Learning via Weight-aware Distillation under Class Distribution Mismatch

arXiv

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arXiv 2023年

作者： Du, Pan Zhao, Suyun Sheng, Zisen Li, Cuiping Chen, Hong Key Lab of Data Engineering and Knowledge Engineering of MOE Renmin University of China China Renmin University of China Beijing China

Semi-Supervised Learning (SSL) under class distribution mismatch aims to tackle a challenging problem wherein unlabeled data contain lots of unknown categories unseen in the labeled ones. In such mismatch scenarios, traditional SSL suffers severe performance damage due to the harmful invasion of the instances with unknown categories into the target classifier. In this study, by strict mathematical reasoning, we reveal that the SSL error under class distribution mismatch is composed of pseudo-labeling error and invasion error, both of which jointly bound the SSL population risk. To alleviate the SSL error, we propose a robust SSL framework called Weight-Aware Distillation (WAD) that, by weights, selectively transfers knowledge beneficial to the target task from unsupervised contrastive representation to the target classifier. Specifically, WAD captures adaptive weights and high-quality pseudo-labels to target instances by exploring point mutual information (PMI) in representation space to maximize the role of unlabeled data and filter unknown categories. Theoretically, we prove that WAD has a tight upper bound of population risk under class distribution mismatch. Experimentally, extensive results demonstrate that WAD outperforms five state-of-the-art SSL approaches and one standard baseline on two benchmark datasets, CIFAR10 and CIFAR100, and an artificial cross-dataset. The code is available at https://***/RUC-DWBI-ML/research/tree/main/WAD-master. Copyright © 2023, The Authors. All rights reserved.

关键词： Distillation

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Calibration Method for Driving Behavior Parameters in Simulation Model of Asphalt Pavement with Different Gradations 5

Calibration Method for Driving Behavior Parameters in Simula...

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5th International Conference on Image, Video Processing, and Artificial Intelligence, IVPAI 2023

作者： Li, Yuqi Liang, Zijun Wang, Ruihan Deng, Ran Wang, Ruipeng Niu, Yiran Sun, Pei School of Urban Construction and Transportation Hefei University 230601 China Anhui Provincial Key Laboratory of Urban Rail Transit Safety and Emergency Management 230601 China Anhui Province Transportation Big Data Analysis and Application Engineering Laboratory 230601 China

ISBN: (纸本)9781510674660

The calibration of driving behavior parameters in the traffic simulation model for pavement formed by different aggregate mixtures is of crucial significance in ensuring the effectiveness of traffic simulation evaluation results for various asphalt pavement. This study first examines different aggregate asphalt mixtures as asphalt pavement materials through experiments. Subsequently, using queue length as the evaluation indicator, a sensitivity analysis is conducted based on VISSIM traffic simulation software to identify the set of sensitive parameter set data among the driving behavior parameters for asphalt pavement under study. The study then uses the traffic simulation model to determine the value of the driving behavior parameter set that result in the smallest error rate between simulated queue length and measured queue length on asphalt pavement. This completes the calibration of driving behavior parameters for the studied asphalt pavement in the traffic simulation model. Finally, the proposed method is validated through real-world case studies. This study proposes a feasible parameter calibration method for traffic simulation scenarios of asphalt pavement formed by different gradations of asphalt mixtures. At the same time, it establishes the foundation for optimizing and controlling intersection signals for corresponding asphalt pavement. © 2024 SPIE. All rights reserved.

关键词： Sensitivity analysis

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Identifying Scientific and Technical“Unicorns”

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Journal of data and Information Science 2021年第2期6卷 96-115页

作者： Lucy L.Xu Miao Qi Fred Y.Ye Jiangsu Key Laboratory of Data Engineering and Knowledge Service School of Information ManagementNanjing UniversityNanjing 210023China University Library Nantong UniversityNantong 226019China

Purpose:Using the metaphor of"unicorn,"we identify the scientific papers and technical patents characterized by the informetric feature of very high citations in the first ten years after publishing,which may provide a new pattern to understand very high impact works in science and ***/methodology/approach:When we set CT as the total citations of papers or patents in the first ten years after publication,with CT≥5,000 for scientific"unicorn"and CT≥500 for technical"unicorn,"we have an absolute standard for identifying scientific and technical"unicorn"***:We identify 165 scientific"unicorns"in 14,301,875 WoS papers and 224 technical"unicorns"in 13,728,950 DII patents during 2001–*** 50%of"unicorns"belong to biomedicine,in which selected cases are individually *** rare"unicorns"increase following linear model,the fitting data show 95%confidence with the RMSE of scientific"unicorn"is 0.2127 while the RMSE of technical"unicorn"is *** limitations:A"unicorn"is a pure quantitative consideration without concerning its quality,and"potential unicorns"as CT≤5,000 for papers and CT≤500 for patents are left in future *** implications:Scientific and technical"unicorns"provide a new pattern to understand high-impact works in science and ***"unicorn"pattern supplies a concise approach to identify very high-impact scientific papers and technical ***/value:The"unicorn"pattern supplies a concise approach to identify very high impact scientific papers and technical patents.

关键词： Unicorn Scientific paper Technical patent Citation analysis Patent analysis

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Wind turbine detection based on high spatial resolution four-band reflectance images 6

Wind turbine detection based on high spatial resolution four...

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6th International Conference on Geoscience and Remote Sensing Mapping, GRSM 2024

作者： Deng, Fengying Qiao, Baojun Li, Kaitao Zhao, Limin Chen, Xingfeng Li, Jiaguo Liu, Jun Sun, Yuan Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China Aerospace Information Research Institute Chinese Academy of Science Beijing China School of Space Information Space Engineering University Beijing China

ISBN: (纸本)9781510688018

Wind turbine detection is essential for the power industry and regulatory agencies to efficiently and accurately determine their number and spatial distribution. Under complex underlying surface conditions, the detection accuracy of conventional methods is low, especially when dealing with multi-scale wind turbine targets. In addition, the underutilization of the near-infrared (NIR) band limits the capability of optical remote sensing sensors in wind turbine detection. To address the above problems, this paper proposes a wind turbine detection algorithm YOLOv8m-BD based on high spatial resolution four-band reflectance images using YOLOv8m as the baseline model. Firstly, the four-band image is input through channel adaptation modification. Next, the CSPDarknet53 to 2-stage FPN (C2f) module is enhanced by introducing deformable convolution (DCN) to expand the receptive field. Finally, the effectiveness of our design was validated through extensive experiments on a self-built wind turbine dataset. Compared to the YOLOv8m baseline model that only inputs RGB three bands, the improved YOLOv8m-BD achieves an accuracy of 96.4% and a false alarm rate of 2.0%, an increase of 3.4% in accuracy and a decrease of 2.5% in false alarm rate. © 2025 SPIE.

关键词： Proximity sensors

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