The main objective of this study is to examine gender differences and the adoption of technology in higher education students. TAM model is the tool used to measure the acceptance and use of e-learning of the respondents. We used Partial Least Squares (PLS), specifically, the PLS multi-group analysis was used to compare differences between groups. In summary, results show that students’ behavio...

Over the past 15 years, the use of Partial Least Squares (PLS) in academic research has enjoyed increasing popularity in many social sciences including Information Systems, marketing, and organizational behavior. PLS can be considered an alternative to covariance-based SEM and has greater flexibility in handling various modeling problems in situations where it is difficult to meet the hard assu...

Dimension reduction is important during the analysis of gene expression microarray data, because the high dimensionality of data sets hurts the generalization performance of classifiers. Partial Least Squares (PLS) based dimension reduction is a frequently used method, since it is specialized in handling high dimensional data set and leads to satisfying classification performance. This paper in...

chemometric techniques in spectral analysis have gained importance in the quality control of  the drugs mixtures and pharmaceutical formulations containing two or more drugs with overlapping spectra. since theophylline and etophylline have common chromophore, they cannot be analyzed simultaneously using conventional uv methods. simultaneous spectrophotometric determination of etophylline and th...

a simple and rapid method for the determination of 137ba isotope abundances in water samples by inductively coupled plasma-optical emission spectrometry (icp-oes) coupled with least-squares support vector machine regression (ls-svm) is reported. by evaluation of emission lines of barium, it was found that the emission line at 493.408 nm provides the best results for the determination of 137ba a...

This paper reports on the use of Artificial Neural Networks (ANN) and Partial Least Squareregression (PLS) combined with NIR spectroscopy (900-1700 nm) to design calibration models for thedetermination of sugar content in sugar beet. In this study a total of 80 samples were used as the calibration set,whereas 40 samples were used for prediction. Three pre-processing methods, including Multiplic...

Building classification models plays an important role in DNA mircroarray data analyses. An essential feature of DNA microarray data sets is that the number of input variables (genes) is far greater than the number of samples. As such, most classification schemes employ variable selection or feature selection methods to pre-process DNA microarray data. This paper investigates various aspects of...

Simultaneous spectrophotometric determination of Mn, Zn and Co was studied by two methods, classical partial least-squares (PLS) and kernel partial least-squares (KPLS), with 2-(5-bromo-2- pyridylazo)-5-diethylaminephenol (5-Br-PADAP) and cetyl pyridinium bromide (CPB). Two programs, SPGRPLS and SPGRKPLS, were designed to perform the calculations. Eight error functions were calculated for deduc...

This paper compares and discusses four techniques for model order reduction based on compressed sensing (CS), less relevant basis removal (LRBR), principal component analysis (PCA) and partial least squares (PLS). CS and PCA have already been used for reducing the order of power amplifier (PA) behavioral models for digital predistortion (DPD) purposes. While PLS, despite being popular in some s...

Two multivariable problems of general interest are factor analysis and regression. This paper examines partial least squares (PLS) as a tool for both problems. For single output data sets, the familiar PLS algorithm is applicable to both problems. For multiple output problems the familiar PLS algorithm 1, 2, 3] (called fact-PLS in this paper) is appropriate for factor analysis. However fact-PLS...