dual-flow oil filter,double-focusing mass spectrograph

Ab initio calculations on thioformamide dimers;

硫代甲酰胺双聚体的量子化学计算

Simulating Calculation of the Dissociation-Association Equilibrium of Dimer and Monomer of Trimethylaluminum in Gas Phase;

三甲基铝双聚体和单体的气相离解-缔合平衡模拟计算

The biclustering for local correlation patterns in high dimensional data can find many valuable clusters.

并以此模型为基础,提出了适用于时序数据的确定性双聚类算法sp-TSC,该算法首先利用spCluster模型将局部相关的数据对象符号化,然后将字符序列插入到泛化后缀树中,利用后缀树的性质避免了穷举局部相关子模式的各种组合,有效减小了搜索空间,从而可以在数据矩阵尺寸的线性时间内发现全部最大δ-spCluster。

In this paper,we present a novel QMIB(quadratic mutual information-based biclustering) algorithm,which can find many correlated patterns successfully.

双聚类模型有助于聚类存在相关性的局部模式。