Application of acoustic Doppler current profiler combined with a scientific echo sounder for krill Euphausia pacifica density estimation

ABSTRACT:   An application of the acoustic Doppler current profiler (ADCP, 153.6 kHz) in combination with a scientific echo sounder (EK60, 38 and 200 kHz) was investigated to estimate the density of krill Euphausia pacifica . The acoustic backscattering strength from sound scattering layers was compared with biomass estimates from midwater trawls. Euphausia pacifica was targeted among mixed species populations in the sound scattering layer in the offshore Funka Bay area of Hokkaido, Japan. The frequency characteristics of acoustic backscattering by krill were calculated using a distorted wave Born approximation scattering model at three frequencies. Krill aggregations identified from the EK60 data were extracted as the mean volume backscattering strength difference between two frequencies. They were then used to identify similar aggregations in the ADCP data by matching observation times and depths for the two methods, which were applied simultaneously. Results from the comparison of the mean volume backscattering strength and the density calculated from the ADCP and EK60 showed that ADCP can be used to measure density and spatial–temporal distribution of krill aggregations. Current speed and direction at the study site were found to be 16.1 cm/s and 187.0°, respectively, and krill speed and direction (including the current component) were found to be 19.8 cm/s and 172.2°, respectively. Based on the ADCP data, the net speed and direction of the krill aggregations were found to be 5.9 cm/s and 128.0°, respectively.     

QUICK格式与中心差分格式在土壤水盐运移数值模拟中的适用性分析

中心差分格式选用粗网格离散土壤水盐运移方程中的对流项时,数值解容易发生数值振荡.采用一种三阶精度的离散格式———QUICK格式可以有效地降低数值振荡这一“伪物理”现象.引用几个数值模型,通过与解析解的比较说明了QUICK格式对提高模拟结果准确性具有较好的作用,为分析一维土壤水分垂直运动问题离散格式的稳定性提供科学依据.     

四川巨桉短周期工业原料人工林一元材积表的编制

本文调查、收集了四川省仁寿、高县、纳溪等县不同立地条件的巨桉短周期工业原料人工林标准地72块,样木112株。采用SAS程序,进行多方程拟合并比较各模型优劣,筛选出巨按材积模型:V=-0.0196154 0.0007494d2,编制了巨按短周期工业原料人工林一元材积表。经检验,平均误差为-0.01%,,标准差为±9.6%,均方误为±1.4%,精度达到要求。     

基于SVM算法的区域农田灌溉短期用水量预测方法

常规方法对区域农田灌溉短期用水量预测时易出现预测数据误差大,预测过程复杂等现象。设计基于SVM算法对区域农田灌溉短期用水量进行预测。以某沿黄区域位于全景属于黄河流域东南方向一区域农田为研究对象,首先基于SVM算法选择用水量特征,选取一对一的构造方法将农田灌溉短期用水量数据分为两个类别。通过SVM算法中支持向量机分类功能将农田灌溉短期用水量特征子集进行获取,并在此基础上可以根据特征子集通过预测模型进行用水量预测。由于用水量序列波动性较强,将GM(1,N)模型与机器学习算法LSSVR模型相结合来进行用水量预测,并确定模型评价指标。结果证明基于SVM算法的区域农田灌溉短期用水量预测方法误差在允许范围内且在农业中具有可使用性。     

叶片被毛对干旱区短命植物狭果鹤虱生理生态特征的影响

以荒漠短命植物狭果鹤虱为研究对象,通过野外控制实验,研究叶片被毛(leaf hairs)对狭果鹤虱生理生态特征的影响。结果表明:对于叶片有被毛的植物,模拟凝结水能显著提高叶厚、叶重、叶片水势、净光合速率、气孔导度以及地上生物量(干重),而对根径、根长与地下生物量(干重)表现出较小的效应;对于人工去除叶片被毛的植物,模拟凝结水对其根长、根径、叶厚、叶重、叶片水势、净光合速率、气孔导度、地上与地下生物量的影响不大。由此可知,被毛的存在能显著增加狭果鹤虱叶片吸附凝结水的量,同时也能增强其对干旱环境的适应能力。     

小麦淀粉峰值粘度的选择指标

淀粉是小麦籽粒的主要成分,对面制食品的加工品质有重要影响.糊化特性是淀粉最重要的品质指标[1,2],而峰值粘度是衡量糊化特性的主要参数,与面条品质呈显著或极显著正相关[3～10],与馒头体积、比容、结构和评分亦呈显著或极显著正相关[8,11].     

一种大规模体数据压缩体绘制策略

针对基于GPU的大规模体数据直接体绘制过程中遇到的显存不足的问题，提出了一种大规模体数据的压缩绘制策略.该策略结合小波变换和分类矢量量化进行数据压缩，采用基于GPU的光线投射算法进行绘制，在绘制时，只解压变换当前绘制所需要的极少数数据，并结合多分辨率绘制，实现实时交互.基于CUDA的实验表明：该压缩绘制策略有效解决了显存不足问题，并且在保证交互绘制帧率的前提下获得了较好的成像质量.     

炭化条件对竹原纤维炭孔隙结构的影响分析

为研究炭化竹原纤维的特性,进一步提升竹原纤维的使用性能,拓宽竹原纤维的应用领域,采用可控电炉制备了不同炭化温度和不同保温时间条件下的炭化竹原纤维,利用全自动比表面积及孔隙度分析仪测试了炭化竹原纤维的比表面积、比孔容及平均孔径,探讨了炭化条件对其性能的影响。结果表明：随炭化温度的升高和保温时间的延长,炭化竹原纤维的比表面积、比孔容和孔径分布先增大后减小,在较优的工艺条件下,炭化竹原纤维的比表面积和比孔容最大值分别可达819.35m2/g和0.7358cm3/g,平均孔径最小可达2.0836nm。     

Respond of Stock Trading Volume to Earning Report

Earning report is a main accounting report that transmits earning information to users. It is the core of financial reports system. Earning information is significant to users' decision making. This paper studies the respond of stock trading volume to earning report and draws the curve of trading volume before and after earning report. This paper further does a regression analysis of accidental earning and abnormal return rate, and draws the relation curve of them on the earning report date to prove stock trading volume does have remarkable respond to earning report. This research is significant to either lessen small investors blindness investment and help them make reasonable forecast to markets and regulate the disclosure of listed companies.     

基于激光雷达数据的东北林区航空林分材积表编制

利用东北林区云冷杉林、落叶松林、樟子松林、红松林、栎树林、桦树林、杨树林、榆树林、椴树林和水胡黄林10种森林类型的1947个样地的激光雷达数据和地面实测蓄积量数据,首先通过多元线性回归和非线性回归方法,分别建立基于机载激光雷达数据的森林蓄积量回归估计模型,并通过对比分析,确定统一形式的基础回归模型;然后利用哑变量建模方法,建立基于不同森林类型参数和相同激光雷达变量的蓄积量模型。结果表明,研究建立的10种森林类型的线性蓄积量回归模型的解释变量个数在2~7之间,确定系数在0.460~0.858之间;非线性蓄积量回归模型的解释变量个数在2~4之间,确定系数在0.461~0.846之间。基于点云平均高度和平均强度建立的10种森林类型的二元蓄积量模型(研究称之为标准模型),其确定系数在0.440~0.815之间,平均预估误差在2.88%~4.42%之间,平均百分标准误差在16.76%~25.52%之间,预估精度基本达到森林资源规划设计调查技术规定要求。依据研究建立的10种森林类型的蓄积量模型,可以编制基于激光雷达数据的航空林分材积表,在森林资源调查实践中推广应用。