微格式就是一系列的数据格式，它利用现有的(X)HTML和CSS构造将原始数据嵌入到以人类为目标的网页的标记中。
Microformats are a series of data formats that use existing (x) HTML and CSS constructs to embed raw data within the markup of a human-targeted Web page.
显示构造出某个特定目标的任务。
构造了一个以公司和工人为目标的双目标规划模型，同时模型中考虑了库存计划的稳定性。
A multiple objective problem is constructed for the owner and the worker. At the same time, planning stability is considered in the model.
地震层析成像技术应用于精细构造和目标的探测已在许多工程勘察和检测部门得到了应用。
The use of seismic ct imaging technique in the exploration of minute structure and objects has already acquired its field of application in many departments of engineering investigation and detection.
该方法在对各个指标进行标准化后构造一个涵盖各指标的新的目标函数，并对该目标函数进行优化。
A target function was constructed from the analysis to the experiments and a new multi-index optimization experiment method was proposed.
构造良好的远程学习环境，是实现远程教育人才培养目标的基础，更是教学过程运行和质量保证的关键。
A good distance learning environment is not only the foundation of realizing the training goal of distance education, but also the key to the operation and quality guarantee of teaching.
在构造预条件因子时，采用从目标的“几何结构剖分”出发，而不是从“矩阵元素”出发确定“基权函数之间的作用量关系”，这样保证了构造预条件矩阵的计算复杂度仅为O（N）。
The preconditioner is generated from the target's "geometry structure " and not from the "matrix element", which assured the computational complexity for generating the preconditioner is only O(N) .
为了实现目标的快速检测，提出了一种新的基于拉格朗日支持向量机(L -SVM)的线性级联式分类器的构造方法。
To detect objects quickly, a new method is presented to construct a cascade of linear classifiers with L-SVM (Lagrangian Support Vector Machine, L-SVM).
对于桁架结构重量目标函数，直接推出倒变量的二阶形式，以桁架重量最小为目标的优化问题构造为标准的二次规划模型。
The objective function of minimizing truss mass was expressed in two order form, the optimal problem was formulated as a standard quadratic programming model.
从背景出发，充分利用在图像序列中占绝大部分的背景像素来构造弱小目标的检测，并提出在时域上利用背景预测技术实现检测。
And the technique of small target detection is put forward based on temporal predictions of the background in infrared image sequences.
从背景出发，充分利用在图像序列中占绝大部分的背景像素来构造弱小目标的检测，并提出在时域上利用背景预测技术实现检测。
And the technique of small target detection is put forward based on temporal predictions of the background in infrared image sequences.
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