response surface methodology (rsm) is a statistical method useful in the modeling and analysis of problems in which the response variable receives the influence of several independent variables, in order to determine which are the conditions under which should operate these variables to optimize a corrugated box production process. the purpose of this research is to create response surface mode...

In this paper two dimensional wave propagation is used for power combining in drain nodes of a distributed amplifier (DA). The proposed two dimensional DA uses an electrical funnel to add the currents of drain nodes. The proposed structure is modified due to gate lines considerations. Total gain improvement is achieved by engineering the characteristic impedance of gate lines and also make appr...

We can reach by DNA microarray gene expression to such wealth of information with thousands of variables (genes). Analysis of this information can show genetic reasons of disease and tumor differences. In this study we try to reduce high-dimensional data by statistical method to select valuable genes with high impact as biomarkers and then classify ovarian tumor based on gene expression data of...

In this work, characteristics of various ball bearing parameters are studied under different loads and rotational speeds. By using Dimensional Analysis (DA), dimensionless parameters are computed which provides solution for a group of parameters. This analysis can be accomplished by using the Buckingham π-theorem. DA leads to reduction of the number of independent parameters involved in a probl...

when the number of training samples is limited, feature reduction plays an important role in classification of hyperspectral images. in this paper, we propose a supervised feature extraction method based on discriminant analysis (da) which uses the first principal component (pc1) to weight the scatter matrices. the proposed method, called da-pc1, copes with the small sample size problem and has...

In the past few decades, researchers have proposed many discriminant analysis (DA) algorithms for the study of high-dimensional data in a variety of problems. Most DA algorithms for feature extraction are based on transformations that simultaneously maximize the between-class scatter and minimize the withinclass scatter matrices. This paper presents a novel DA algorithm for feature extraction u...