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Established in 2001, Puyang Zhong Yuan Restar Petroleum Equipment Co.,Ltd, “RSD” for short, is Henan’s high-tech enterprise with intellectual property advantages and independent legal person qualification. With registered capital of RMB 50 million, the Company has two subsidiaries-Henan Restar Separation Equipment Technology Co., Ltd We are mainly specialized in R&D, production and service of various intelligent separation and control systems in oil&gas drilling,engineering environmental protection and mining industries.We always take the lead in Chinese market shares of drilling fluid shale shaker for many years. Our products have been exported more than 20 countries and always extensively praised by customers. We are Class I network supplier of Sinopec,CNPC and CNOOC and registered supplier of ONGC, OIL India,KOC. High quality and international standard products make us gain many Large-scale drilling fluids recycling systems for Saudi Aramco and Gazprom projects.

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What Is Principal Component Analysis (PCA) and How It Is Used?
What Is Principal Component Analysis (PCA) and How It Is Used?

The mean-centering procedure corresponds to, moving the origin of the coordinate system to coincide with the average point, (here in red). The first principal component After mean-centering and scaling to unit variance, the data set is ready for computation of the first summary index, the first principal component (PC1).

Automotive Touch Up Paint from PaintScratch - Order Pro ...
Automotive Touch Up Paint from PaintScratch - Order Pro ...

"Received touch up ,paint, several days ago. It was a perfect match. I wish I had found your company months earlier. Thanks" R. Freddi Forest Hills , NY "I just got around to using my touch up ,paint, today and I just want to say that color match is excellent! I will purchase from your company again."

Tidying up with PCA: An Introduction to Principal ...
Tidying up with PCA: An Introduction to Principal ...

13/11/2019, · PCA creates the new variables by, transforming, the, original (mean-centered) observations (records) in a dataset to a new set of variables (dimensions) using, the eigenvectors, and, eigenvalues calculated from a covariance matrix of your original variables. That is a mouthful. Let’s break it down, starting with mean-centering the original variables.

Does mean centering or feature scaling affect a Principal ...
Does mean centering or feature scaling affect a Principal ...

1. Mean, centering does not affect, the covariance, matrix., Here, the rational is: If the covariance is the same whether the variables are centered or not, the result of the PCA will be the same. Let’s assume we have the 2 variables x and y. Then the covariance between the attributes is calculated as. Let us write the centered variables as

The Effect of Data Centering on PCA Models
The Effect of Data Centering on PCA Models

Early applications of PCA often worked with, mean-centered, data and showed that the PCA eigenvalues are proportional to the “variance” captured in the covariance matrix.[1,2], Mean-centering, is used to create models of multivariate data in multivariate statistical process control.[3] However, PCA is

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