或者大多时候，我叫它“叉积。”
Or also called... most of the time I refer to it as "the cross product."
由上述无意生成的交叉联接返回的叉积。
The cross product returned by the unintentional cross join depicted above.
叉积是计算几何中关于线段算法的核心。
In computational geometry, computing cross products is at the heart of line-segment methods.
第一单元学得叉积、法向量这些,现在就有用了。
The first unit about cross-products,normal vectors and so on is actually useful now.
为了找到带法向量的面元，我就取这两个的叉积。
To find the surface element together with a normal vector, I would just take the cross-product between these guys.
运用输入输出轴两轴线的向量叉积求出了联轴器夹角方程序。
And then, the expression of the fluctuation of the joint Angle was derived from the cross product of the centerlines of the input and output shafts.
因此，在理论上，该方案的跟踪精度要优于叉积自动频率控制环。
Therefore, in theory, tracking precision of the proposed scheme will precede CPAFC.
通过计算环的最大坐标值点处相邻两条边的切矢的叉积来判断环的方向。
The loop direction is judged through the vector product of the adjacent two edges on the vertex with maximum coordinate value.
对多元线性回归模型参数的预测，转化为对其变量集合的增广矩阵的叉积阵的预测。
Prediction to the regression parameters was converted to predict cross product matrix of the variable augmented matrix.
实践表明，该算法避免了叉积运算，有效地提高了判别速度，而且实现算法简单、稳定。
Tests show that the algorithm effectively improves identifying speed, simple and stable, because it avoids cross-product operation.
在交叉联接中，一个表中的每一行与另一个表中的每一行合并，导致生成叉积或卡迪尔积。
In a cross join, each row from one table is combined with each row from another table, resulting in what is called a cross product or a Cartesian product.
对常用的叉积自动频率跟踪环（CPAFC）进行了改进，改进后的鉴频算法具有更快的捕获速度。
This article has made the improvement to CPAFC which be commonly used. After the improvement frequency discrimination algorithm has the quicker capture speed.
您还可以在查询中联接客户和订单，方法是构建叉积并将所有相关数据位作为一个大型投影检索出来。
You can also join customers and orders in a query by forming the cross-product and retrieving all the relative bits of data as one large projection.
您还可以在查询中联接客户和订单，方法是构建叉积并将所有相关数据位作为一个大型投影检索出来。
You can also join customers and orders in a query by forming the cross-product and retrieving all the relative bits of data as one large projection.
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