检索结果-内蒙古大学图书馆

A catalog of LAMOST variable sources based on time-domain photometry of ZTF

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Xu, Tingting Liu, Chao Wang, Feng Huang, Weirong Deng, Hui Mei, Ying Cao, Zhong Center For Astrophysics Guangzhou University Guangdong Guangzhou510006 China Great Bay Center National Astronomical Data Center Guangdong Guangzhou510006 China Astronomy Science and Technology Research Laboratory Department of Education of Guangdong Province Guangdong Guangzhou510006 China Key Laboratory for Astronomical Observation and Technology of Guangzhou Guangdong Guangzhou510006 China Key Laboratory of Space Astronomy and Technology National Astronomical Observatories CAS Beijing100101 China University of Chinese Academy of Sciences Beijing100049 China

The identification and analysis of different variable sources is a hot issue in astrophysical research. The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) spectroscopic survey has accumulated massive spectral data but contains no information about variable sources. Although a few related studies present variable source catalogs for the LAMOST, the studies still have a few deficiencies regarding the type and number of variable sources identified. In this study, we presented a statistical modeling approach to identify variable source candidates. We first crossed the Kepler, Sloan Digital Sky Survey (SDSS), and Zwicky Transient Facility (ZTF) catalogs to obtain light curves data of variable and non-variable sources. The data are then modeled statistically using commonly used variability parameters, respectively. And then, an optimal variable source identification model is determined using the Receiver Operating Characteristic (ROC) curve and four credible evaluation indices such as precision, accuracy, recall, and F1_score. Based on this identification model, a catalog of LAMOST variable sources (including 631,769 variable source candidates with a probability greater than 95% and so on) is obtained. To validate the correctness of the catalog, we performed a two-by-two cross-comparison with the GAIA catalog and other published variable source catalogs. We achieved the correct rate ranging from 50% to 100%. Among the 123,756 sources cross-matched, our variable source catalog identifies 85,669 with a correct rate of 69%, which indicates that the variable source catalog presented in this study is credible. © 2021, CC BY.

关键词： Statistical methods

The design and application of an web-based online examination system 4th

学校读者我要写书评

暂无评论

The design and application of an web-based online examinatio...

4th International Symposium on Emerging Technologies for Education, SETE 2019, was held in conjunction with the 18th International Conference on Web-based Learning, ICWL 2019

作者： Jiang, Jilu Wu, Baoxian Chang, Liang Liu, Kui Hao, Tianyong Audit Governance and Risk Control Research Center School of Accounting Guangdong University of Foreign Studies Guangzhou China Guangzhou Key Laboratory of Big Data and Intelligent Education School of Computer Science South China Normal University Guangzhou China Network and Modern Educational Technology Center Guangzhou University Guangzhou China

ISBN: (纸本)9783030387778

Online examination has been used more and more widely in the education and other fields due to its advantages of efficiency, convenience, and fairness. This paper proposes a new web-based online examination system, which utilizes PHP, Ajax and other technologies to implement online examination functions, including testing question collection, user management, online testing, real-time score calculation, answer checking, and result analysis. Particularly, an automated test paper generation module was designed and integrated. The system has been applied to a course involving more than 1000 students per semester at Guangzhou University of Foreign Studies. It has been proved to save efforts of teachers and students, demonstrating its effectiveness in assisting teaching and learning. © Springer Nature Switzerland AG 2020.

关键词： E-learning

Trusted AI in Multi-agent Systems: An Overview of Privacy and Security for Distributed Learning

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Ma, Chuan Li, Jun Wei, Kang Liu, Bo Ding, Ming Yuan, Long Han, Zhu Poor, H. Vincent Zhejiang Laboratory Hangzhou311121 China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China The School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing210096 China The Department of Computing Hong Kong Polytechnic University 999077 Hong Kong The University of Technology SydneyNSW2007 Australia Data61 CSIRO NSW2015 Australia The School of Computer Science Nanjing University of Science and Technology Nanjing210096 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States Department of Computer Science and Engineering Kyung Hee University Seoul Korea Republic of The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

Motivated by the advancing computational capacity of distributed end-user equipment (UE), as well as the increasing concerns about sharing private data, there has been considerable recent interest in machine learning (ML) and artificial intelligence (AI) that can be processed on distributed UEs. Specifically, in this paradigm, parts of a ML process are outsourced to multiple distributed UEs. Then the processed information is aggregated on a certain level at a central server, which turns a centralized ML process into a distributed one, and brings about significant benefits. However, this new distributed ML paradigm raises new risks of privacy and security issues. In this paper, we provide a survey on the emerging security and privacy risks of distributed ML from a unique perspective of information exchange levels, which are defined according to the key steps of a ML process, i.e.: i) the level of pre-processed data, ii) the level of learning models, iii) the level of extracted knowledge and, iv) the level of intermediate results. We explore and analyze the potential of threats for each information exchange level based on an overview of the current state-of-the-art attack mechanisms, and then discuss the possible defense methods against such threats. Finally, we complete the survey by providing an outlook on the challenges and possible directions for future research in this critical area. Copyright © 2022, The Authors. All rights reserved.

关键词： Multi agent systems

Unveiling the Multifaceted GRB 200613A: Prompt Emission Dynamics, Afterglow Evolution, and the Host Galaxy’s Properties

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Fu, Shao-Yu Xu, Dong Lei, Wei-Hua de Ugarte Postigo, Antonio Kann, D. Alexander Thöne, Christina C. Fernández, José Feliciano Agüí Shuang-Xi, Yi Xie, Wei Zou, Yuan-Chuan Liu, Xing Jiang, Shuai-Qing Lu, Tian-Hua An, Jie Zhu, Zi-Pei Zheng, Jie Tang, Qing-Wen Zhao, Peng-Wei Xin, Li-Ping Wei, Jian-Yan Key Laboratory of Space Astronomy and Technology National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China School of Astronomy and Space Science University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing100049 China Department of Astronomy School of Physics Huazhong University of Science and Technology Wuhan430074 China Université de la Côte d’Azur Observatoire de la Côte d’Azur CNRS Artemis Nice06304 France Aix Marseille Univ. CNRS LAM Marseille France Hessian Research Cluster ELEMENTS Giersch Science Center Goethe University Frankfurt Max-von-Laue-Straße 12 Campus Riedberg Frankfurt am MainD-60438 Germany Astronomical Institute Czech Academy of Sciences Fričova Ondřejov298 Czech Republic Centro Astronómico Hispano en Andalucía Observatorio de Calar Alto Sierra de los Filabres Gérgal Almería04550 Spain School of Physics and Physical Engineering Qufu Normal University Qufu273165 China Department of Astronomy School of Physics and Electronic Science Guizhou Normal University Guiyang550001 China Guizhou Provincial Key Laboratory of Radio Astronomy Data Processing Guizhou Normal University Guiyang550001 China CAS Key Laboratory of Optical Astronomy National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Department of Physics School of Science Nanchang University Nanchang330031 China

We present our optical observations and multi-wavelength analysis of the GRB 200613A detected by Fermi satellite. Time-resolved spectral analysis of the prompt γ-ray emission was conducted utilizing the Bayesian block method to determine statistically optimal time bins. Based on the Bayesian Information Criterion (BIC), the data generally favor the Band+Blackbody (short as BB) model. We speculate that the main Band component comes from the Blandford-Znajek mechanism, while the additional BB component comes from the neutrino annihilation process. The BB component becomes significant for a low-spin, high-accretion rate black hole central engine, as evidenced by our model comparison with the data. The afterglow light curve exhibits typical power-law decay, and its behavior can be explained by the collision between the ejecta and constant interstellar medium (ISM). Model fitting yields the following parameters: EK,iso = (2.04+11.8-1.50) × 1053 erg, Γ0 = 354+578-217, p = 2.09+0.02-0.03, n18 = (2.04+9.71-1.87)×102 cm-3, θj = 24.0-5.54+6.50 degree, ϵe = 1.66+4.09-1.39)×10-1 and ϵB = (7.76+48.5-5.9)×10-6. In addition, we employed the public Python package Prospector perform a spectral energy distribution (SED) modeling of the host galaxy. The results suggest that the host galaxy is a massive galaxy (log(M∗/M☉) = 11.75-0.09+0.10) with moderate star formation rate (SFR = 22.58+13.63-7.22 M☉/yr). This SFR is consistent with the SFR of ∼ 34.2M☉ yr-1 derived from the [OII] emission line in the observed spectrum. © 2024, CC0.

关键词： Gamma rays

An Adaptive Model Update Object Tracking Algorithm based on DenseNet Features

学校读者我要写书评

暂无评论

An Adaptive Model Update Object Tracking Algorithm based on ...

2020 International Conference on networking and network Applications, NaNA 2020

作者： Ma, Sugang Zhang, Lei Pu, Lei Yang, Xiaobao Hou, Zhiqiang Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an University of Posts and Telecommunications Xi'an shaanxi710121 China School of Computer Science and Technology Xi'an University of Posts and Telecommunications Xi'an shaanxi710121 China School of Information and Navigation Air Force Engineering University Xi'an shaanxi710077 China

ISBN: (纸本)9781728189543

In order to further improve the ability to deal with complex scenes, a visual tracking algorithm based on DenseNet features and model adaptive updating is proposed. Aiming to improve the feature representation ability of correlation filtering algorithm, a more discriminative DenseNet model is used as feature extractor. Meanwhile, in order to improve the long-term tracking performance, an adaptive model update strategy is proposed. The average peak correlation energy (APCE) based on response map is used to judge and evaluate the tracking result and the model is updated only when the confidence is high. The experimental results show that the proposed algorithm achieves higher success rate and accuracy compared to the other five related algorithms, and improves the robustness of object tracking in complex scenes such as occlusion and deformation. © 2020 IEEE.

关键词： Tracking (position)

Minute-cadence Observations of the LAMOST Fields with the TMTS: III. Statistic Study of the Flare Stars from the First Two Years

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Liu, Qichun Lin, Jie Wang, Xiaofeng Gu, Shenghong Shi, Jianrong Zhang, Liyun Xi, Gaobo Mo, Jun Cai, Yongzhi Chen, Liyang Chen, Zhihao Guo, Fangzhou Jiang, Xiaojun Li, Gaici Li, Wenxiong Lin, Han Lin, Weili Liu, Jialian Miao, Cheng Ma, Xiaoran Peng, Haowei Xiang, Danfeng Yan, Shengyu Zhang, Jicheng Zhang, Xinhan Physics Department Tsinghua Center for Astrophysics Tsinghua University Beijing100084 China Beijing Planetarium Beijing Academy of Science and Technology Beijing100044 China Yunnan Observatories Chinese Academy of Sciences Kunming650216 China Key Laboratory for the Structure and Evolution of Celestial Objects Chinese Academy of Sciences Kunming650216 China CAS Key Laboratory of Optical Astronomy National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China School of Astronomy and Space Science University of Chinese Academy of Sciences Beijing100049 China College of Physics College of Big Data and Information Engineering Guizhou University Guiyang550025 China Center for Astronomical Mega-Science Chinese Academy of Sciences 20A Datun Road Chaoyang District Beijing100012 China The School of Physics and Astronomy Tel Aviv University Tel Aviv69978 Israel Department of Astronomy Beijing Normal University Beijing100875 China

Tsinghua University-Ma Huateng Telescopes for Survey (TMTS) aims to detect fast-evolving transients in the Universe, which has led to the discovery of thousands of short-period variables and eclipsing binaries since 2020. In this paper, we present the observed properties of 125 flare stars identified by TMTS within the first two years, with an attempt to constrain their eruption physics. As expected, most of these flares were recorded in late-type red stars with GBP − GRP > 2.0 mag;however, the flares associated with bluer stars tend to be on average more energetic and have broader profiles. The peak flux (Fpeak) of the flare is found to depend strongly on the equivalent duration (ED) of the energy release, i.e., Fpeak ∝ ED0.72±0.04, which is consistent with results derived from the Kepler and Evryscope samples. This relation is likely related to the magnetic loop emission, while, for the more popular non-thermal electron heating model, a specific time evolution may be required to generate this relation. We notice that flares produced by hotter stars have a flatter Fpeak ∝ ED relation compared to that from cooler stars. This is related to the statistical discrepancy in light-curve shape of flare events with different colors. In spectra from LAMOST, we find that flare stars have apparently stronger Hα emission than inactive stars, especially at the low temperature end, suggesting that chromospheric activity plays an important role in producing flares. On the other hand, the subclass with frequent flares is found to show Hα emission of similar strength in its spectra to that recorded with only a single flare but similar effective temperature, implying that the chromospheric activity may not be the only trigger for eruptions. Copyright © 2023, The Authors. All rights reserved.

关键词： Stars

Deep Learning Strategies for Addressing Anomalous Exposure in Image Processing: The FARDBUNet Approach

学校读者我要写书评

暂无评论

Deep Learning Strategies for Addressing Anomalous Exposure i...

High Performance Big data and Intelligent Systems (HPBD&IS)

作者： Qi Zhou Kai Yang Zunwang Ke Gang Wang Yugui Zhang Yizhen Jia Fengcai Cao Junxiao Ma Changlin Liu Kaijie Zhang Min Wu School of Semiconductor Science and Technology South China Normal University GuangZhou China AnnLab Institute of Semiconductors Chinese Academy of Sciences Beijing China Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology Beijing China CGNPC Uranium Industry Development Co. Ltd. Beijing China School of Software Xinjiang University Urumqi China School of Computing and Data Engineering NingboTech University Ningbo China School of Integrated Circuits University of Chinese Academy of Sciences Beijing China Zhongke Shangyi Health Technology (Beijing) Co. Ltd. Beijing China School of Information Beijing Forestry University Beijing China

In real-world scenarios, capturing scenes with excessive dynamic range often leads to the partial loss of highlight or dark area information due to irradiance variations and limitations in the capture capabilities of imaging devices caused by their size and material constraints. This phenomenon gives rise to anomalous exposure problems and triggers the loss of crucial initial details, thereby becoming a significant obstacle to achieving high image quality. Despite numerous researchers' integration of exposure compensation techniques into the imaging process, the anomalous exposure problem remains unsolved, hindering progress in image processing. Consequently, considerable research is valuable in implementing exposure calibration techniques on visual perception and multimedia devices. This dissertation proposes FARDBUNet, a novel end-to-end exposure calibration model designed to address the anomalous exposure problem. A key innovation of FARDBUNet is the incorporation of a fused attention mechanism, enabling the model to prioritize regions needing enhanced correction while accounting for the global exposure characteristics of the image. Additionally, to tackle the challenge of inadequate information availability in the localized areas due to exposure issues, we introduce an atrous residual dense block that efficiently captures local information by expanding the receptive field. Comprehensive tests validate the effectiveness of our suggested model, which performs on par with leading techniques on expansive exposure datasets.

关键词：

Larger Receptive Field and Context Information for Pose Estimation: Larger Gaussian Kernel

学校读者我要写书评

暂无评论

Larger Receptive Field and Context Information for Pose Esti...

High Performance Big data and Intelligent Systems (HPBD&IS)

作者： Junxiao Ma Kai Yang Zunwang Ke Gang Wang Yugui Zhang Fengcai Cao Qi Zhou Yang Fei School of Information Beijing Forestry University Beijing China AnnLab Institute of Semiconductors Chinese Academy of Sciences Beijing China CGNPC Uranium Industry Development Co. Ltd. Beijing China School of Software Xinjiang University Urumqi China School of Computing and Data Engineering NingboTech University Ningbo China Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology Beijing China School of Integrated Circuits University of Chinese Academy of Sciences Beijing China Zhongke Shangyi Health Technology (Beijing) Co. Ltd. Beijing China School of Semiconductor Science and Technology South China Normal University GuangZhou China

The field of pose estimation has a wide range of application prospects in various industries in the current era. With the continuous development of deep learning techniques, the effects in the field of human pose estimation are constantly being optimized. However, due to the influence of factors such as occlusion and human posture variability, it is easy to lead to inaccurate identification of keypoints and even keypoints' missing and matching errors, there is still a lot of optimization space for the effect of pose estimation. In this paper, we propose an improvement to generate heatmaps in the training process: increase the radius of the Gaussian kernel and adjust the smoothness of Gaussian distribution to get a larger receptive field, encourage the model to use more context information in prediction, and control other parameters unchanged on the premise of using heatmap regression. Improve keypoint detection performance by optimizing this item. In the experiment, for the COCO-keypoint data set, we selected different methods published in recent years, and after our improvement, we obtained better accuracy and performance than the original method, which proves the validity of our method.

关键词：

Record High Temperatures in the Ocean in 2024

学校读者我要写书评

暂无评论

Advances in Atmospheric sciences 2025年第6期42卷 1092-1109页

作者： Lijing CHENG John ABRAHAM Kevin E.TRENBERTH James REAGAN Huai-Min ZHANG Andrea STORTO Karina VON SCHUCKMANN Yuying PAN Yujing ZHU Michael E.MANN Jiang ZHU Fan WANG Fujiang YU Ricardo LOCARNINI John FASULLO Boyin HUANG Garrett GRAHAM Xungang YIN Viktor GOURETSKI Fei ZHENG Yuanlong LI Bin ZHANG Liying WAN Xingrong CHEN Dakui WANG Licheng FENG Xiangzhou SONG Yulong LIU Franco RESEGHETTI Simona SIMONCELLI Gengxin CHEN Rongwang ZHANG Alexey MISHONOV Zhetao TAN Wangxu WEI Huifeng YUAN Guancheng LI Qiuping REN Lijuan CAO Yayang LU Juan DU Kewei LYU Albertus SULAIMAN Michael MAYER Huizan WANG Zhanhong MA Senliang BAO Henqian YAN Zenghong LIU Chunxue YANG Xu LIU Zeke HAUSFATHER Tanguy SZEKELY Flora GUES National Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of St.Thomas School of EngineeringMinnesota 55105USA NSF National Center for Atmospheric Research BoulderColorado 80307USA University of Auckland Auckland 0630New Zealand National Oceanic and Atmospheric Administration National Centers for Environmental InformationSilver SpringMaryland 20910USA National Oceanic and Atmospheric Administration National Centers for Environmental InformationAshevilleNC 28801USA National Research Council(CNR)Institute of Marine Sciences(ISMAR) Rome 00133Italy Mercator Ocean International Toulouse 31400France Department of Earth and Environmental Science University of PennsylvaniaPhiladelphiaPennsylvania 19104USA Institute of Oceanology Chinese Academy of SciencesQingdao 266071China National Marine Environmental Forecasting Center Ministry of Natural Resources of ChinaBeijing 100081China North Carolina Institute for Climate Studies(NCICS) North Carolina State UniversityAshevilleNC 28804USA Oceanographic Data Center Chinese Academy of SciencesQingdao 266071China College of Oceanography Hohai UniversityNanjing 210098China National Marine Data and Information Service Tianjin 300171China Istituto Nazionale di Geofisica e Vulcanologia Sede di BolognaBologna 40128Italy South China Sea Institute of Oceanology Chinese Academy of SciencesGuangzhou 510301China ESSIC/CISESS-MD University of MarylandCollege ParkMD 20740USA Computer Network Information Center Chinese Academy of SciencesBeijing 100083China Eco-Environmental Monitoring and Research Center Pearl River Valley and South China Sea Ecology and Environment AdministrationMinistry of Ecology and EnvironmentGuangzhou 510611China National Meteorological Information Center China Meteorological AdministrationBeijing 100081China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China Xiamen Universit

Heating in the ocean has continued in 2024 in response to increased greenhouse gas concentrations in the atmosphere,despite the transition from an El Ni?o to neutral conditions. In 2024, both global sea surface temperature(SST) and upper2000 m ocean heat content(OHC) reached unprecedented highs in the historical record. The 0–2000 m OHC in 2024exceeded that of 2023 by 16 ± 8 ZJ(1 Zetta Joules = 1021 Joules, with a 95% confidence interval)(IAP/cas data), which is confirmed by two other data products: 18 ± 7 ZJ(CIGAR-RT reanalysis data) and 40 ± 31 ZJ(Copernicus Marine data,updated to November 2024). The Indian Ocean, tropical Atlantic, Mediterranean Sea, North Atlantic, North Pacific, and Southern Ocean also experienced record-high OHC values in 2024. The global SST continued its record-high values from2023 into the first half of 2024, and declined slightly in the second half of 2024, resulting in an annual mean of 0.61°C ±0.02°C(IAP/cas data) above the 1981–2010 baseline, slightly higher than the 2023 annual-mean value(by 0.07°C ±0.02°C for IAP/cas, 0.05°C ± 0.02°C for NOAA/NCEI, and 0.06°C ± 0.11°C for Copernicus Marine). The record-high values of 2024 SST and OHC continue to indicate unabated trends of global heating.

关键词： ocean heat content sea surface temperature ocean temperature global warming climate