Search results for "partial least square"
showing 10 items of 152 documents
An Embedded Solution for Multispectral Palmprint Recognition
2018
Palmprint based identification has attracted much attention in the past decades. In some real-life applications, portable personal authentication systems with high accuracy and speed efficiency are required. This paper presents an embedded palmprint recognition solution based on the multispectral image modality. We first develop an effective recognition algorithm by using partial least squares regression, then a FPGA prototype is implemented and optimized through high-level synthesis technique. The evaluation experiments demonstrate that the proposed system can achieve a higher recognition rate at a lower running cost comparing to the reference implementations.
Modelling the enantioresolution capability of cellulose tris(3,5-dichlorophenylcarbamate) stationary phase in reversed phase conditions for neutral a…
2018
[EN] To the best of our knowledge, the prediction of the enantioresolution ability of polysaccharides-based stationary phases in liquid chromatography for structurally unrelated compounds has not been previously reported. In this study, structural information of neutral and basic compounds is used to model their enantioresolution levels obtained from an immobilised cellulose tris(3,5-dichlorophenylcarbamate) stationary phase in reversed phase conditions. Thirty-four structurally unrelated chiral drugs and pesticides, from seven families, are studied. Categorical enantioresolution levels (RsC, 0 = no baseline enantioresolution and 1 = baseline enantioresolution) are established from the expe…
Predicting Skin Permeability by Means of Computational Approaches: Reliability and Caveats in Pharmaceutical Studies
2019
The skin is the main barrier between the internal body environment and the external one. The characteristics of this barrier and its properties are able to modify and affect drug delivery and chemical toxicity parameters. Therefore, it is not surprising that permeability of many different compounds has been measured through several in vitro and in vivo techniques. Moreover, many different in silico approaches have been used to identify the correlation between the structure of the permeants and their permeability, to reproduce the skin behavior, and to predict the ability of specific chemicals to permeate this barrier. A significant number of issues, like interlaboratory variability, experim…
New cut-off criterion for uninformative variable elimination in multivariate calibration of near-infrared spectra for the determination of heroin in …
2008
A new cut-off criterion has been proposed for the selection of uninformative variables prior to chemometric partial least squares (PLS) modelling. After variable elimination, PLS regressions were made and assessed comparing the results with those obtained by PLS models based on the full spectral range. To assess the prediction capabilities, uninformative variable elimination (UVE)-PLS and PLS were applied to diffuse reflectance near-infrared spectra of heroin samples. The application of the proposed new cut-off criterion, based on the t-Students distribution, provided similar predictive capabilities of the PLS models than those obtained using the original criteria based on quantile value. H…
Comparison of different predictive models for nutrient estimation in a sequencing batch reactor for wastewater treatment
2006
Abstract In this paper different predictive models for nutrient estimation in a sequencing batch reactor (SBR) for wastewater treatment are compared: principal component regression (PCR), partial least squares (PLS), and artificial neural networks (ANNs). Two unfolding procedures were used: batch-wise and variable-wise. For the latter unfolding method, X and Y matrix augmentation with lagged variables were used in some models to incorporate process dynamics. The results have shown that batch-wise unfolding PLS models outperform the other approaches. The ANN models are good predictive models, but in this particular case-study, they do not outperform those multivariate projection models that …
On the internal multivariate quality control of analytical laboratories. A case study: the quality of drinking water
2001
Abstract Multivariate statistical process control (MSPC) tools, based on principal component analysis (PCA), partial least squares (PLS) regression and other regression models, are used in the present study for automatic detection of possible errors in the methods used for routine multiparametric analysis in order to design an internal Multivariate Analytical Quality Control (iMAQC) program. Such tools could notice possible failures in the analytical methods without resorting to any external reference since they use their own analytical results as a source for the diagnosis of the method's quality. Pseudo-univariate control charts provide an attractive alternative to traditional univariate …
Determination of vinegar acidity by attenuated total reflectance infrared measurements through the use of second-order absorbance-pH matrices and par…
2007
Univariate (zero-order), multivariate (first-order) and multiway (second-order) calibrations were assayed for the determination of vinegar acidity using a mechanized procedure based upon vibrational spectroscopy and the emerging multicommutation methodology. The second-order methodology relies on the use of a flow system based on multicommutation and binary sampling. The flow network comprises a set of three-way solenoid valves, computer-controlled to provide facilities to handle the sample and to generate a time-dependent pH gradient using two carrier solutions. The procedure is based on the volumetric fraction variation approach that maintains the same volume of sample solution and dynami…
Combination of mid- and near-infrared spectroscopy for the determination of the quality properties of beers
2006
Abstract The combination of infrared (MIR) and near-infrared (NIR) spectroscopy has been employed for the determination of important quality parameters of beers, such as original and real extract and alcohol content. A population of 43 samples obtained from the Spanish market and including different types of beer, was evaluated. For each technique, spectra were obtained in triplicate. In the case of NIR a 1 mm pathlength quartz flow cell was used, whereas attenuated total reflectance measurements were used in MIR. Cluster hierarchical analysis was employed to select calibration and validation data sets. The calibration set was composed of 15 samples, thus leaving 28 for validation. A critic…
Partial least squares X-ray fluorescence determination of trace elements in sediments from the estuary of Nerbioi-Ibaizabal River.
2010
The feasibility of partial least squares (PLS) regression modeling of X-ray fluorescence (XRF) spectra of estuarine sediments has been evaluated as a tool for rapid trace element content monitoring. Multivariate PLS calibration models were developed to predict the concentration of Al, As, Cd, Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb, Sn, V and Zn in sediments collected from different locations across the estuary of the Nerbioi-Ibaizabal River (Metropolitan Bilbao, Bay of Biscay, Basque Country). The study was carried out on a set of 116 sediment samples, previously lyophilized and sieved with a particle size lower than 63 microm. Sample reference data were obtained by inductively coupled plasma mass …
A green method for the determination of cocaine in illicit samples
2013
Abstract Direct determination of cocaine in untreated seized samples has been made based on diffuse reflectance measurements of the near infrared (NIR) radiation through samples contained inside standard glass vials. The method used a series of previously analyzed samples, by the reference gas chromatography method, to build a partial least squares calibration model which was validated using an independent set of samples. The use of a general model for samples containing from 11.38% till 86.44% (w/w) cocaine was based on the use of spectral ranges from 12500.7 to 10128.6, 9339.8 to 6967.7 and 5388.3 to 4597.6 cm−1 with previous first derivative and vector normalization data pre-processing a…