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LiDAR点云生成DEM的水面置平方法研究与实现 被引量:3
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作者 张(弓同) 李四海 +1 位作者 焦红波 曲辉 《测绘通报》 CSCD 北大核心 2015年第6期61-64,共4页
以LiDAR激光点云数据为基础,分析了水面信息自动识别和置平处理的技术方法,并使用C#语言编程实现,取得了理想的效果,在实际DEM生产过程中得到了很好的应用。
关键词 LIDAR 水面置平 TIN ARCGIS DEM
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First dark matter search results from the PandaX-Ⅰ experiment 被引量:13
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作者 XIAO MengJiao XIAO Xiang +43 位作者 ZHAO Li CAO XiGuang CHEN Xun CHEN YunHua CUI XiangYi FANG DeQing FU ChangBo GIBONI Karl L. GONG HaoWei GUO GuoDong HU Jie HUANG XingTao JI XiangDong JU YongLin LEI SiAo LI ShaoLi LIN Qing LIU HuaXuan LIU JiangLai LIU Xiang LORENZON Wolfgang MA YuGang MAO YaJun NI KaiXuan PUSHKIN Kirill REN XiangXiang SCHUBNELL Michael SHEN ManBing STEPHENSON Scott TAN AnDi TARL Greg WANG HongWei WANG JiMin WANG Meng WANG XuMing WANG Zhou WEI YueHuan WU ShiYong XIE PengWei YOU YingHui ZENG XiongHui ZHANG Hua ZHANG Tao ZHU ZhongHua 《Science China(Physics,Mechanics & Astronomy)》 SCIE EI CAS 2014年第11期2024-2030,共7页
We report on the first dark-matter(DM)search results from PandaX-I,a low threshold dual-phase xenon experiment operating at the China JinPing Underground Laboratory.In the 37-kg liquid xenon target with 17.4 live-days... We report on the first dark-matter(DM)search results from PandaX-I,a low threshold dual-phase xenon experiment operating at the China JinPing Underground Laboratory.In the 37-kg liquid xenon target with 17.4 live-days of exposure,no DM particle candidate event was found.This result sets a stringent limit for low-mass DM particles and disfavors the interpretation of previously-reported positive experimental results.The minimum upper limit,3.7×10-44cm2,for the spin-independent isoscalar DM-particle-nucleon scattering cross section is obtained at a DM-particle mass of 49 GeV/c2at 90%confidence level. 展开更多
关键词 dark matter direct detection XENON
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Discriminate spatial Ricci scalar dark energy from ΛCDM
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作者 YANG RongJia QI JingZhao CHEN BoHai 《Science China(Physics,Mechanics & Astronomy)》 SCIE EI CAS 2012年第10期1952-1955,共4页
We apply two geometrical diagnostics, the statefinder {s, r} and Om(x), to discriminate the Spatial Ricci scalar dark energy model from the ACDM model. We plot the evolution trajectories of those models in the state... We apply two geometrical diagnostics, the statefinder {s, r} and Om(x), to discriminate the Spatial Ricci scalar dark energy model from the ACDM model. We plot the evolution trajectories of those models in the statefinder plane and Om(x) plane. We show that the Spatial Ricci scalar dark energy model can be distinguished from the ACDM model at 68.3% confidence level for z ≤ 1. 展开更多
关键词 spatial Ricci scalar dark energy LCDM geometrical diagnostics
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