Moose （Alces alces cameloides） is typically representative of the fauna of the frigid temperate zone and has been put on the Chinese second priority list of protected animals. The moose of northeast China is on the ...Moose （Alces alces cameloides） is typically representative of the fauna of the frigid temperate zone and has been put on the Chinese second priority list of protected animals. The moose of northeast China is on the southern most edge of its distribution in Asia. To study resource selection characteristics of moose and their response to human distur- bances and forest resource variables, the field work was conducted in Heilongiiang Provincial Shengshan Forestry Farm, which is located in the northwestern slope of Lesser Khingan Mountains, northeastern China, from January to March in both 2006 and 2007. A total of 428 plots were examined within the study area. Signs of moose use were found in 19 plots. Based on the analysis of resource selection function, we found that moose selected areas with higher densities of mixed deciduous broadleaf patch and mixed coniferous and broad leaf patch, and a higher NDVI value. Moose avoided settlement 6 km away and remained low probability of occurrence within 3 km from roads,展开更多
In the research, changes of apple chemistry, and molecule, under stresses, are n terms of morphology, physiology, bio- illustrated and research and identifica- tion methods of apple resistance are explored involving ...In the research, changes of apple chemistry, and molecule, under stresses, are n terms of morphology, physiology, bio- illustrated and research and identifica- tion methods of apple resistance are explored involving drought-resistance, flood-re- sistance, salt-stress resistance, cold-hardiness and heat-resistance. In addition prospects of apple resistance research are proposed, as well.展开更多
为解决传统机器学习中训练集(源域)与测试集(目标域)数据分布不一致导致分类准确率较低的问题,提出一种基于半监督判别分析和CDMD的领域自适应算法(SDA-CDMD)。首先,使用半监督判别分析(SDA)进行数据降维,保留了映射到低维子空间中数据...为解决传统机器学习中训练集(源域)与测试集(目标域)数据分布不一致导致分类准确率较低的问题,提出一种基于半监督判别分析和CDMD的领域自适应算法(SDA-CDMD)。首先,使用半监督判别分析(SDA)进行数据降维,保留了映射到低维子空间中数据的几何结构信息。其次,提出一种衡量两个域之间分布差异的度量准则:跨域均值差异(Cross-Domain Mean Discrepancy,CDMD)。最后,将SDA与CDMD结合,将两个域投影到同一子空间中,减少两个域之间的分布差异。在手写数字图像和计算机视觉数据集上进行的大量实验结果表明,所提算法优于传统的领域自适应方法,验证了其有效性。展开更多
基于美国NCEP(National Centers for Environmental Prediction)的CFSR(Climate Forecast System Reanalysis)近20a(1991-2010)10m风场再分析数据(0.3°×0.3°,1h/次,简称CFSR风场),对我国近海风能资源分布特征进行了统计...基于美国NCEP(National Centers for Environmental Prediction)的CFSR(Climate Forecast System Reanalysis)近20a(1991-2010)10m风场再分析数据(0.3°×0.3°,1h/次,简称CFSR风场),对我国近海风能资源分布特征进行了统计分析与评估。利用天津渤海A平台观测站(118°25′E,38°27′N)逐时观测风速数据对CFSR风速数据进行了检验,发现均方根误差和平均偏差仅为均较小(分别为2.28m/s与0.16m/s)。基于此CFSR风场,本文章进一步统计并给出了我国陆地年平均风功率密度分布,结果与第三次风能普查(1971-2000年)及相关文献结果 (1991-2010年)相当一致。依据国家风电场风能资源评估方法,由CFSR风场推算了我国近海20a平均的70m高度风能资源分布。结果显示,年平均风功率密度均达到了200 W/m2以上,大于6m/s的风速累积小时数为4 000h以上;其中台湾海峡和东海南部海区风能最为丰富,黄海中部、渤海中部和辽东湾海区风能次之。参照海上风场选址要求,28°N以北的近岸海域由于水深较浅,30m/s以上风速发生频次极低,比较适合建立海上风电场。展开更多
基金financially supported by National Excellent Doctoral Dissertation of PR China-FANEDD(No.201069)""Program for New Century Excellent Talents in University–NCET(No.10-0310)""the Fundamental Research Funds for the Central Universities(No.DL12DA01)
文摘Moose （Alces alces cameloides） is typically representative of the fauna of the frigid temperate zone and has been put on the Chinese second priority list of protected animals. The moose of northeast China is on the southern most edge of its distribution in Asia. To study resource selection characteristics of moose and their response to human distur- bances and forest resource variables, the field work was conducted in Heilongiiang Provincial Shengshan Forestry Farm, which is located in the northwestern slope of Lesser Khingan Mountains, northeastern China, from January to March in both 2006 and 2007. A total of 428 plots were examined within the study area. Signs of moose use were found in 19 plots. Based on the analysis of resource selection function, we found that moose selected areas with higher densities of mixed deciduous broadleaf patch and mixed coniferous and broad leaf patch, and a higher NDVI value. Moose avoided settlement 6 km away and remained low probability of occurrence within 3 km from roads,
基金Supported by Shandong Provincial Natural Science Foundation in China(ZR2011CM034)~~
文摘In the research, changes of apple chemistry, and molecule, under stresses, are n terms of morphology, physiology, bio- illustrated and research and identifica- tion methods of apple resistance are explored involving drought-resistance, flood-re- sistance, salt-stress resistance, cold-hardiness and heat-resistance. In addition prospects of apple resistance research are proposed, as well.
文摘为解决传统机器学习中训练集(源域)与测试集(目标域)数据分布不一致导致分类准确率较低的问题,提出一种基于半监督判别分析和CDMD的领域自适应算法(SDA-CDMD)。首先,使用半监督判别分析(SDA)进行数据降维,保留了映射到低维子空间中数据的几何结构信息。其次,提出一种衡量两个域之间分布差异的度量准则:跨域均值差异(Cross-Domain Mean Discrepancy,CDMD)。最后,将SDA与CDMD结合,将两个域投影到同一子空间中,减少两个域之间的分布差异。在手写数字图像和计算机视觉数据集上进行的大量实验结果表明,所提算法优于传统的领域自适应方法,验证了其有效性。
