Ce基大块非晶合金在纳米压人过程中的变形行为

利用纳米压入技术研究了Ce基大块非晶合金的变形行为,以及加载速率对塑性变形行为的影响规律.结果表明,Ce基大块非晶合金在纳米压入过程中表现出的变形行为与其他体系大块非晶有显著差别.Ce60Al15Cu10Ni15合金在低加载速率下为连续的塑性变形,在高加载速率下表现出显著的锯齿流变特征;而Ce65Al10Cu10Ni10Nb5合金,在所研究的加载速率范围内均为连续的塑性变形．但是,这两种合金都出现了室温蠕变现象．另外,探讨了Ce基大块非晶合金的反常塑性变形行为的产生机理．

The Relationship between Decision Trees and the Scale of Train Data Set

Decision Trees need train samples in the train data set to get classification rules. If the number of train data was too small, the important information might be missed and thus the model could not explain the classification rules of data. While it is not affirmative that large scale of train data set can get well model. This Paper analysis the relationship between decision trees and the train data scale. We use nine decision tree algorithms to experiment the accuracy, complexity and robustness of decision tree algorithms. Some results are demonstrated.