Incremental wrapper-based gene selection from microarray data for cancer classification

Gene expression microarray is a rapidly maturing technology that provides the opportunity to assay the expression levels of thousands or tens of thousands of genes in a single experiment. We present a new heuristic to select relevant gene subsets in order to further use them for the classification task. Our method is based on the statistical significance of adding a gene from a ranked-list to the final subset. The efficiency and effectiveness of our technique is demonstrated through extensive comparisons with other representative heuristics. Our approach shows an excellent performance, not only at identifying relevant genes, but also with respect to the computational cost.     

美国C.F布朗公司大型合成氨装置用材简介

介绍了美国Ｃ．Ｆ布朗公司大型合成氨装置根据操作条件和介质腐蚀程度不同，如何选择管道和设备材料，并对其用材进行逐一剖析。     

A clustering method for automatic biometric template selection

The problem addressed in this paper is the template selection and update in biometrics based on clustering. Template selection is a reliable method to reduce the number of templates used in a biometric system to account for variations observed in a person's biometric data. An efficient method based on clustering with automatic selection of the number of clusters is proposed in this work for finding subgroups of similar templates which are used for prototype selection.Experimental results confirm the advantage of the new method and the importance of adopting a procedure to perform template selection.     

Development of an Expert System for Selection of Dam Type on Alluvium Foundations

. A knowledge-based expert system was developed to aid in the selection of the type of dam. The dam type selector expert system (DTSA ES) was designed to determine the type of dam on the alluvium foundations. Detailed expert knowledge is required to estimate the type of dam and to develop an expert system. The DTSA ES utilizes rules of thumb used by an expert for determining the selection of the type of dam. The DTSA ES was developed using a shell program. The expert system was tested on several dam sites in order to validate the decision obtained. The use of this expert system, containing knowledge about the selection of dam type, can be helpful to students, potential owners or contractors in selecting dam types. The current prototype always needs additional parameters for more detailed analyses of new developments. However, the current DTSA ES is designed to include existing information about dam types.     

Adaptive flexibility and maladaptive routines in selecting fast and frugal decision strategies.

Decision routines unburden the cognitive capacity of the decision maker. In changing environments, however, routines may become maladaptive. In 2 experiments with a hypothetical stock market game (n = 241), the authors tested whether decision routines tend to persist at the level of decision strategies rather than at the level of options in strategy selection. The payoff structure of the task was changed after 80 decision trials, rendering a new strategy optimal with respect to expected payoff. Whereas most participants detected the appropriate strategy at the beginning of the task, they tended to retain it even when it was no longer optimal. A hint about a possible change had only a small influence on this maladaptive routine; a monetary incentive had none. Switching to a similar but not identical task relaxed the routine, but not much. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

供水管网中阀门的选择

针对供水企业对供水管网阀门的使用要求，从供水的安全性、技术的先进性、水流的密封性、检验的真实性、质量的可靠性、操作的灵活性、价格的合理性、售后服务的保证性、订供货的一致性以及建立比较完善的检验与复验制度等方面。提出了对供水管网阀门的选择意见。     

基于类间分散度和类内集中度的文本特征选择。

特征选择是文本分类的关键步骤之一,所选特征子集的优劣直接影响文本分类的结果。论文首先定义了两种特征分类能力：一种是特征对类间文档的分散程度,该分散度越大越好;另一种是特征对类内文档的聚集程度,该集中度越大越好。然后把这两种特征影响度有机地结合起来设计了一个新的特征选择方法,该方法能够对所选特征进行综合考虑,从而使获得的特征集具有较好的代表性。仿真实验表明所提特征选择方法在一定程度上能够提高文本分类性能。     

基于特征选择的集成分类器抗噪性能分析

特征选择有助于增强集成分类器成员间的随机差异性,从而提高泛化精度。研究了随机子空间法（RandomSub-space）和旋转森林法（RotationForest）两种基于特征选择的集成分类器构造算法,分析讨论了两算法特征选择的方式与随机差异程度之间的关系。通过对UCI数据集引入噪声,比较两者在噪声环境下的分类精度。实验结果表明：当噪声增加及特征关联度下降时,基本学习算法及噪声程度对集成效果均有影响,当噪声增强到一定程度后。集成效果和单分类器的性能趋于一致。     

母线保护选型配置原则及整定计算

以220kV变电站母线保护为例,介绍母线保护选型配置及整定计算原则。     

C++程序设计教学中的技能培养

本文阐述了知识与技能的关系,以及C++程序设计教学中知识和技能的双重性要求。以选择语句为例,演示了"先知识后技能"的教学过程。实践证明,这样的教学安排行之有效。