In the present work, the simultaneous determination of Brilliant green (BG) and Crystal violet (CV) dyes with overlapped absorption spectra in binary mixture solution, was carreid out using the partial least squares (PLS) and direct ortogonal signal correction-partial least squares (DOSC-PLS) methods. The results obtained indicate that by applying DOSC on the calibration and prediction data for...

the multivariate calibration method, partial least square regression (pls) was applied for thesimultaneous spectrophotometric determination of lidocaine (lid) and hydrocortisone acetate(hca) in their mixtures. the parameters of chemometric technique were optimized and theproposed method was validated with synthetic samples and applied to analyze these drugs inpharmaceutical products with good a...

the present study evaluates effects of organizational culture on organizational commitment with emphasis on the role of mediator entrepreneurial orientation departments within the material procurement management at national iranian south oil company. statistic population included of 470 experts and managers, 23 departments within the material procurement management that using stratified random ...

Olmesartan medoxamil (OLM, an angiotensin II receptor blocker), amlodipine besylate (AML, a dihydropyridine calcium channel blocker) and hydrochlorothiazide (HCT, a diuretic of the class of benzothiadiazines) are co-formulated in a single-dose combination for the treatment of hypertensive patients whose blood pressure is not adequately controlled on either component monotherapy. In this work, t...

Within the context of nonlinear system identification, different variants of LS-SVM are applied to the Silver Box dataset. Starting from the dual representation of the LS-SVM, and using Nyström techniques, it is possible to compute an approximation for the nonlinear mapping to be used in the primal space. In this way, primal space based techniques as Ordinary Least Squares (OLS), Ridge Regressi...

In this paper, we discuss new formulations of both redundancy analysis (RA) and partial least squares regression (PLS) which clearly show the connection between these two methods. These new formulations also show that RA and PLS regression are the two end points of a continuum approach that we propose to investigate. Moreover, it enjoys very interesting properties which highlight the rational o...

This paper proposes learning-based methods for mapping a sparse representation of noisy speech to state likelihoods in an automatic speech recognition system. We represent speech as a sparse linear combination of exemplars extracted from training data. The weights of exemplars are mapped to speech state likelihoods using Ordinary Least Squares (OLS) and Partial Least Squares (PLS) regression. R...

We demonstrate the effectiveness of intrinsic Raman spectroscopy (IRS) at reducing errors caused by absorption and scattering. Physical tissue models, solutions of varying absorption and scattering coefficients with known concentrations of Raman scatterers, are studied. We show significant improvement in prediction error by implementing IRS to predict concentrations of Raman scatterers using bo...

This paper adds to an important aspect of Partial Least Squares (PLS) path modeling, namely the convergence of the iterative PLS path modeling algorithm. Whilst conventional wisdom says that PLS always converges in practice, there is no formal proof for path models with more than two blocks of manifest variables. This paper presents six cases of non-convergence of the PLS path modeling algorith...

This paper resumes the discussion in information systems research on the use of partial least squares (PLS) path modeling and shows that the inconsistency of PLS path coefficient estimates in the case of reflective measurement can have adverse consequences for hypothesis testing. To remedy this, the study introduces a vital extension of PLS: consistent PLS (PLSc). PLSc provides a correction for...