This paper studies the application of principal component analysis, multiple polynomial regression, and artificial neural network ANN techniques to the quantitative analysis of binary mixture of dye solution. The binary mixtures of three textile dyes including blue, red and yellow colors were analyzed by PCA-Multiple polynomial Regression and PCA-Artificial Neural network PCA-ANN methods. The o...

Principal component analysis (PCA) is a ubiquitous statistical technique for data analysis. PCA is however limited by its linearity and may sometimes be too simple for dealing with real-world data especially when the relations among variables are nonlinear. Recent years have witnessed the emergence of nonlinear generalizations of PCA, as for instance nonlinear principal component analysis (NLPC...

Many applications have benefited remarkably from high resolution (HR) imaging models such as, astronomical and biomedical imaging system. In recent years, image enhancement and resolution approach has been embark the great result, and received great deal of attention of the researcher, and many researchers have proposed several methods to achieve the goal of high resolution image. In this paper...

Safeguarding the energy security is an important energy policy goal of every country. Assuring sufficient and reliable resources of energy at affordable prices is the main objective of energy security. Due to such reasons as special geopolitical position, terrorist attacks and other unrest in the Middle East, securing Iran’s energy demand and increasing her natural gas exports have turned into ...

In this study, a multi objective optimization for end milling of Al 6061 alloy has been presented to provide better surface quality and higher Material Removal Rate (MRR). The input parameters considered for the analysis are spindle speed, depth of cut and feed. The experiments were planned as per Taguchis design of experiment, with L27 orthogonal array. The Grey Relational Analysis (GRA) has b...

adulteration in milk and other dairy products not only is a serious threat to human health but also leads to the economic losses in the dairy industry. utilization of the materials reducing microbial load is a common adulteration. in this study, a machine olfaction (electronic nose) based on 8 metal oxide semiconductor (mos) sensors was fabricated and developed and its capability to formalin de...

A multivariate spatial objective analysis (MVOA) assimilating high spatio-temporal resolution of hydrographic (CTD) and acoustic (ADCP) observations near Barbados provided a comprehensive view of the local surface circulation (0–100m) during early spring of two consecutive years (1996 and 1997). Significant submesoscale fluctuations of the velocity and salinity fields exhibit a very dynamic env...

Recently, the robustification of principal component analysis has attracted lots of attention from statisticians, engineers and computer scientists. In this work we study the type of outliers that are not necessarily apparent in the original observation space but can seriously affect the principal subspace estimation. Based on a mathematical formulation of such transformed outliers, a novel rob...

We study sequential monitoring procedures that detect instabilities of the regression operator in an underlying (fully) functional regression model allowing for dependence. These open-end and closed-end procedures are built on a functional principal components analysis of both the predictor and response functions, thus giving rise to multivariate detector functions, whose fluctuations are compa...