本文研究了用膜分相法分离环氧大豆油中乏酸的可能性，并且进行了试验。
The separative possibility. of acid-used from epoxidized soybean oil (ESO) was studied, and the test was carried out in factory.
本文采用将高斯波束法，射线追迹和矢量衍射积分相结合的方法来分析单波束的点聚焦透镜天线。
We adopted Gaussian beam, ray tracing and vector diffraction integration together to analyze single beam spot-focusing lens antenna.
将小波配置法与广义能量积分相结合，提出了一种求解非线性偏微分方程的高精度数值方法。
A high accuracy algorithm for numerical solution of nonlinear partial differential equation (PDE) is suggested combining wavelet collocation method with generalized energy integral.
这十分相似某人接收服药适量的大脑休克医治法。
It is very similar to someone who receives an overdose from a shock treatment to the brain.
根据部分相干光的相干模表示法，推导了由部分相干光源所产生光束的相位一空间积Q。
The generalized expression for the phase-space product Q of a beam generated from a partially coherent source is presented by using coherent-mode representation of partially coherent beams.
通过主成分分析法与专家打分相结合的方法，建立了一个移民安置区的选优模型，根据模型计算所得到的各个综合分值即可判断各安置区的优劣顺序。
This paper USES the combination of main component analysis method with expert's opinions to set up an optimization model of settlement area for relocated people.
电子舌测定结合主成分分析法(pca)的结果显示，在第一和第二主成分的得分图上，电子舌可以区分特征十分相近的不同等级的普洱茶。
The electronic tongue was used in combination with principal component analysis (PCA) for the classification of tea samples from three quality grades.
方法采用CO2超临界流体萃取飞机草地上部分的挥发油，GC - MS法鉴定化学成分，归一化法测定各成分相对含量。
METHODS the essential oils were extracted by CO2 supercritical fluid extraction (SFE-CO2) method, then separated and identified by GC-MS.
该方法与相关系数法检测移动目标的方法相比减少了计算量，并且相邻图像中存在部分相同背景的情况不影响检测结果。
This method reduce the calculation greatly compare to the method using correlative parameter, and the method is not subject to the same background between the neighbouring frames.
电子舌测定结合主成分分析法（PCA）的结果显示，在第一和第二主成分的得分图上，电子舌可以区分特征十分相近的不同等级的普洱茶。
Results Analyzing the data with principal component analysis(PCA) by model recognition, the different agents can be distinguished in the scattered plots.
电子舌测定结合主成分分析法（PCA）的结果显示，在第一和第二主成分的得分图上，电子舌可以区分特征十分相近的不同等级的普洱茶。
Results Analyzing the data with principal component analysis(PCA) by model recognition, the different agents can be distinguished in the scattered plots.
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