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Near Earth Vortices Driving of Field Aligned Currents Based on Magnetosphere Multiscale and Swarm Observations
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作者 ZHANG C SHEN C +8 位作者 yang y y DUNLOP M W TI S RUSSELL C T LüHR H BURCH J L LINDQVIST P A TORBERT R B FRIIS-CHRISTENSEN E 《空间科学学报》 CAS CSCD 北大核心 2019年第1期9-17,共9页
A long-standing mystery in the study of Field-Aligned Currents(FACs) has been that: how the currents are generated and why they appear to be much stronger at high altitudes than in the ionosphere. Here we present two ... A long-standing mystery in the study of Field-Aligned Currents(FACs) has been that: how the currents are generated and why they appear to be much stronger at high altitudes than in the ionosphere. Here we present two events of magnetotail FACs observed by the Magnetospheric Multiscale Spacecraft(MMS) on 1 st July and 14 th July 2016, to show how the Substorm Current Wedges(SCW) were formed. The results show that particles were transferred heading towards the Earth during the expansion phase of substorms.The azimuthal flow formed clockwise(counter-clockwise) vortex-like motion, and then generated downward(upward) FACs on the tailward/poleward side of the distorted field with opposite vorticity on their Earthward/equatorward side. We also analyzed the Region 1 FACs observed by the Earth Explorer Swarm spacecraft on 1 st July 2016 and found that they were associated with FACs observed by MMS, although differing by a factor of 10. This difference suggests that either there was the closure of the currents at altitudes above 500 km or the currents were not strictly parallel to B and closed at longitudes away from where they were generated. 展开更多
关键词 SUBSTORM current WEDGE MAGNETOSPHERE Field-aligned CURRENTS Flow VORTICITY Multiple spacecraft measurements
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点云数据与深度学习相结合的稻种品种分类
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作者 Qian y Xu Q J +3 位作者 yang y y Lu H Li H Feng X B 《中国农业文摘(农业工程)》 2022年第2期90-90,共1页
水稻品种选择和品质检测是水稻种植过程中的关键环节。与二维图像相比,水稻种子的三维信息更全面、准确地反映了水稻种子的外观特征。该研究提出了一种利用水稻种子表面三维点云数据与深度学习网络相结合的水稻品种分类方法,实现了水稻... 水稻品种选择和品质检测是水稻种植过程中的关键环节。与二维图像相比,水稻种子的三维信息更全面、准确地反映了水稻种子的外观特征。该研究提出了一种利用水稻种子表面三维点云数据与深度学习网络相结合的水稻品种分类方法,实现了水稻品种快速准确识别。 展开更多
关键词 水稻种子 品种分类 外观特征 品质检测 水稻种植 深度学习 水稻品种 点云数据
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