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| 1 | Solar flare forecasting using learning vector quantity and unsupervised clustering techniques显示文摘In this paper, a combined method of unsupervised clustering and learning vector quantity (LVQ) is presented to forecast the occurrence of solar flare. Three magnetic parameters including the maximum horizontal gradient, the length of the neutral line, and the number of singular points are extracted from SOHO/MDI longitudinal magnetograms as measures. Based on these pa- rameters, the sliding-window method is used to form the sequential data by adding three days evolutionary information. Con- sidering the imbalanced problem in dataset, the K-means clustering, as an unsupervised clustering algorithm, is used to convert imbalanced data to balanced ones. Finally, the learning vector quantity is employed to predict the flares level within 48 hours. Experimental results indicate that the performance of the proposed flare forecasting model with sequential data is improved. | LI Rong WANG HuaNing CUI YanMei HUANG Xin | 2011 | Science China(Physics,Mechanics & Astronomy)2011，54，8： | 10 |
| 2 | Precise modeling of arc tooth face-gear with transition curve显示文摘A fabrication method is adopted for which an imaginary gear simultaneously realizes conjugated meshing with an arc tooth cylindrical gear and an arc tooth face-gear.The cutter fllet and tooth crest edge form the tooth root fllet of the gear,and the linear tooth surface equation of the imaginary gear and the position vector of the curvature center of the cutter fllet are constructed with certain cutter inclination to deduce a working arc tooth surface equation.The tooth root fllet equation of the arc tooth face-gear is derived from the meshing geometry and kinematics.A numerically controlled machining model of the arc tooth face-gear is established through the transformation of adjustment parameters from the cutter-tilt milling machine to a common multi-axis NC machine.Motion parameters of each movement axis of the NC machine are acquired.A processing example is presented to verify the precision of the fabrication method in processing the arc tooth face-gear.The method provides a theoretical and tentative basis for the analysis of tooth surface contact stress,tooth root bending stress and dynamics.A hobbing test is conducted to demonstrate the good meshing condition of the arc tooth face-gear pair. | Cui Yanmei Fang Zongde Su Jinzhan Feng Xianzhang Peng Xianlong | 2013 | Chinese Journal of Aeronautics2013，26，5： | 9 |
| 3 | Distortion of memory Vδ2 γδ T cells contributes to immune dysfunction in chronic HIV infection显示文摘γ δT 房间是在天生的豁免起重要作用对传染疾病的辩护首要。人的免疫不全病毒(HIV ) 感染破坏在 Vδ 之间的平衡; 1 T 房间和 Vδ在 γ 之中的 2 T 房间和原因机能障碍; δT 房间。然而,生物机制和这混乱的临床的后果要求进一步的调查。在这研究,我们执行了显型的全面分析和记忆 γ 的功能; δ在有 HIV 感染的中国个人的队的 T 房间。我们在记忆 Vδ 发现了一个动态变化; 2γ δT 房间,扭曲了向一激活并且严重地区分了受动器记忆显型 T EMRA Vδ 2γ δT 房间,可以说明 Vδ 的机能障碍, 2γ δ在 HIV 疾病的 T 房间。另外,我们发现那 IL-17-producing γ δT 房间显著地与快疾病前进在感染 HIV 的病人被增加并且断然与 HLA 医生 +γ 相关; δT 房间和 CD38 +HLA 医生 +γ δT 房间。这建议表明小径的 IL-17 涉及 γ δT 房间激活和 HIV 致病。我们的调查结果提供新奇卓见进 Vδ 的角色; 2 T 房间在 HIV 致病期间并且代表与这些房间考虑有免疫力的治疗的一个健全基础。 | Zhen Li Yanmei Jiao Yu Hu Lianxian Cui Dexi Chen Hao Wu Jianmin Zhang Wei He | 2015 | Cellular & Molecular Immunology2015，12，5： | 7 |
| 4 | Short-Term Solar Flare Prediction Using a Sequential Supervised Learning Method显示文摘 | Daren Yu Xin Huang Huaning Wang Yanmei Cui | 2009 | Solar Physics2009，，1： | 1 |
| 5 | Correlation between Solar Flare Productivity and Photospheric Magnetic Field Properties II. Magnetic Gradient and Magnetic Shear显示文摘 | Yanmei Cui Rong Li Huaning Wang Han He | 2007 | Solar Physics (-)2007，，1： | 1 |
| 6 | Correlation Between Solar Flare Productivity and Photospheric Magnetic Field Properties显示文摘 | Yanmei Cui Rong Li Liyun Zhang Yulin He Huaning Wang | 2006 | Solar Physics2006，，1： | 1 |
| 7 | Effects of calcium dobesilate on glomerulus TIMP1 and collagen IV of diabetic rats显示文摘 | Dong Junwu Liu Xiaochen Liu Shenwei Li Mingbo Xu Yanmei Cui Bing | 2005 | Journal of Huazhong University of Science and Technology2005，，4： | 1 |
| 8 | Determination of trace trichlorfon by high performance liquid chromatography with UV detection based on its catalytic effect on sodium perborate oxidizing benzidine 显示文摘 | ZHU Haizhen CUI Yanmei ZHENG Xiuwen | 2007 | Anal Chim Acta2007，584，1： | 1 |
| 9 | Flavonoids of the Genus Iris(Iridaceae)显示文摘 | Wang Hui Cui Yanmei Zhao Changqi | 2010 | Mini-Reviews in Medicinal Chemistry2010，，10： | 1 |
| 10 | Opening and Sharing of Large-scale Instruments and Equipment in Agricultural Research Institutes:A Case Study of Environment and Plant Protection Institute of Chinese Academy of Tropical Agricultural Sciences显示文摘The article introduces the main practices and achievements of the Environment and Plant Protection Institute of Chinese Academy of Tropical Agricultural Sciences in promoting the sharing of large-scale instruments and equipment in recent years,analyzes the existing problems in the management system,management team,assessment incentives and maintenance guarantee,and proposes improvement measures and suggestions from aspects of improving the sharing management system,strengthening management team building,strengthening sharing assessment and incentives,improving maintenance capabilities and expanding external publicity,to further improve the sharing management of large-scale instruments and equipment. | Yanmei CUI Xiaoqiang CHU Huaping HUANG Xinchun ZHANG Ye LI Shuchang WANG | 2020 | Asian Agricultural Research2020，12，12： | 0 |
| 11 | Development of New Capabilities Using Machine Learning for Space Weather Prediction显示文摘With the development of space exploration and space environment measurements,the numerous observations of solar,solar wind,and near Earth space environment have been obtained in last 20 years.The accumulation of multiple data makes it possible to better use machine learning technique,which has achieved unforeseen results in industrial applications in last decades,for developing new approaches and models in space weather investigation and prediction.In this paper,the efforts on the forecasting methods for space weather indices,events,and parameters using machine learning are briefly introduced based on the study works in recent years.These investigations indicate that machine learning,especially deep learning technique can be used in automatic characteristic identification,solar eruption prediction,space weather forecasting for solar and geomagnetic indices,and modeling of space environment parameters. | LIU Siqing CHEN Yanhong LUO Bingxian CUI Yanmei ZHONG Qiuzhen WANG Jingjing YUAN Tianjiao HU Qinghua HUANG Xin CHEN Hong | 2020 | 空间科学学报2020，40，5： | 0 |
| 12 | Impacts of CMEs on Earth Based on Logistic Regression and Recommendation Algorithm显示文摘Coronal mass ejections(CMEs)are one of the major disturbance sources of space weather.Therefore,it is of great significance to determine whether CMEs will reach the earth.Utilizing the method of logistic regression,we first calculate and analyze the correlation coefficients of the characteristic parameters of CMEs.These parameters include central position angle,angular width,and linear velocity,which are derived from the Large Angle and Spectrometric Coronagraph(LASCO)images.We have developed a logistic regression model to predict whether a CME will reach the earth,and the model yields an F1 score of 30%and a recall of 53%.Besides,for each CME,we use the recommendation algorithm to single out the most similar historical event,which can be a reference to forecast CMEs geoeffectiveness forecasting and for comparative analysis. | Yurong Shi Jingjing Wang Yanhong Chen Siqing Liu Yanmei Cui Xianzhi Ao | 2022 | Space(Science & Technology)2022，，1： | 0 |
| 13 | A focused transcriptomic analysis of the TP53-regulated genes identifies the GPI-anchored molecule-like protein(GML)as a favorable prognostic predictor of lung cancer显示文摘Lung cancer is the most common cause of cancer-related mortality worldwide.1 The current clinical staging systems cannot adequately predict the prognosis of patients with lung cancer,making it difficult to individualize the clinical treatment of the disease,resulting in poorer outcomes. | Yutong Wang Shanshan Wang Yanmei Cui Jie Zhang Shuang Geng Honglei Yin Simiao Zhang Qiufang Li Yunliang Wang | 2023 | Genes & Diseases2023，10，2： | 0 |
| 14 | Verification of SPE probability forecasts at the Space Environment Prediction Center(SEPC)显示文摘In space weather forecasting, forecast verification is necessary so that the forecast quality can be assessed. This paper provides an example of how to choose and devise verification methods and techniques according to different space weather forecast products. Solar proton events(SPEs) are hazardous space weather events, and forecasting them is one of the major tasks of the Space Environment Prediction Center(SEPC) at the National Space Science Center of the Chinese Academy of Sciences. Through analyzing SPE occurrence characteristics, SPE forecast properties, and verification requirements at SEPC, verification methods for SPE probability forecasts are identified, and verification results obtained. Overall, SPE probability forecasts at SEPC exhibit good accuracy, reliability, and discrimination. Compared with climatology and persistence forecasts, the SPE forecasts are more accurate. However, the forecasts for SPE onset days are substantially underestimated and need to be considerably improved. | CUI YanMei LIU SiQing A Er Cha ZHONG QiuZhen LUO BingXian AO XianZhi | 2016 | Science China Earth Sciences2016，59，6： | 0 |
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