Search results for "Partial least squares regression"
showing 10 items of 122 documents
Quantitative Transfer Function Approaches in Palaeoclimatic Reconstruction Using Quaternary Ostracods
2012
Abstract Quantifying (palaeo-)environmental changes is a key challenge for aquatic biological proxies, but the number of published transfer functions is increasing rapidly for the main palaeoecologically relevant groups such as diatoms and chironomids, and several transfer functions have also been developed during the past decades based on ostracod findings. The main environmental variables influencing the species assemblage composition in ostracod training sets are specific ion concentrations or ratios, salinity, water temperature and/or water depth. The available transfer functions and training sets are globally scattered, but often regionally restricted in their application. The most com…
Multivariate Methods Based Soft Measurement for Wine Quality Evaluation
2014
Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/740754 Open Access Soft measurement is a new, developing, and promising industry technology and has been widely used in the industry nowadays. This technology plays a significant role especially in the case where some key variables are difficult to be measured by traditional measurement methods. In this paper, the quality of the wine is evaluated given the wine physicochemical indexes according to multivariate methods based soft measurement. The multivariate methods used in this paper include ordinary least squares regression (OLSR), principal c…
Semisupervised kernel orthonormalized partial least squares
2012
This paper presents a semisupervised kernel orthonormalized partial least squares (SS-KOPLS) algorithm for non-linear feature extraction. The proposed method finds projections that minimize the least squares regression error in Hilbert spaces and incorporates the wealth of unlabeled information to deal with small size labeled datasets. The method relies on combining a standard RBF kernel using labeled information, and a generative kernel learned by clustering all available data. The positive definiteness of the kernels is proven, and the structure and information content of the derived kernels is studied. The effectiveness of the proposed method is successfully illustrated in standard UCI d…
Use of pH gradients in continuous-flow systems and multivariate regression techniques applied to the determination of methionine and cysteine in phar…
1997
Abstract The simultaneous spectrophotometric determination of methionine and cysteine in presence of cystine and other compounds in pharmaceuticals, using a multivariate calibration method, was studied. The method is based on the reaction between the analytes and the o- phthalaldehyde -N- acetyl - l - cysteine (OPA-NAC) reagent performed in a continuous-flow system (FI). The FI system allows the generation of a local pH gradient in order to produce spectral and/or kinetic changes in the UV-Vis spectra of the amino acid-OPA-NAC derivatives. This information is used to improve the prediction ability of the Partial Least-Squares (PLS) models. The performance of two FI assemblies, the selection…
Determination of fatty acids and lipid classes in salmon oil by near infrared spectroscopy
2017
International audience; Near-infrared (NIR) spectroscopy was evaluated as a rapid method for the determination of oleic, palmitic, linoleic and linolenic acids as well as omega-3, omega-6, and to predict polyunsaturated, monounsaturated and saturated fatty acids, together with triacylglycerides, diglycerides, free fatty acids and ergosterol in salmon oil. To do it, Partial Least Squares (PLS) regression models were applied to correlate NIR spectra with aforementioned fatty acids and lipid classes. Results obtained were validated in front of reference procedures based on high performance thin layer and gas chromatography. PLS-NIR has a good predictive capability with relative root mean squar…
Analysis of Caffeine, Sweeteners, and Other Additives in Beverages by Vibrational Spectroscopy
2001
This chapter presents a review of the scientific literature on the use of vibrational spectroscopy, near-infrared (NIR), mid-infrared (mid-IR), and Raman, for the analysis of caffeine, sweeteners, and other additives in beverages and related products. Direct analysis procedures of coffee and tea, for both classification according to precedence or variety and quantitative determination of caffeine, are available. For beverage analysis, caffeine has been determined by direct attenuated total reflection (ATR) measurement or by transmission spectroscopy in the mid-IR region after extraction with chloroform. Different strategies have been employed for the analysis of sweeteners in beverages and …
Fusion of the 1H NMR data of serum, urine and exhaled breath condensate in order to discriminate chronic obstructive pulmonary disease and obstructiv…
2015
Chronic obstructive pulmonary disease, COPD, affects the condition of the entire human organism and causes multiple comorbidities. Pathological lung changes lead to quantitative changes in the composition of the metabolites in different body fluids. The obstructive sleep apnea syndrome, OSAS, occurs in conjunction with chronic obstructive pulmonary disease in about 10–20 % of individuals who have COPD. Both conditions share the same comorbidities and this makes differentiating them difficult. The aim of this study was to investigate whether it is possible to diagnose a patient with either COPD or the OSA syndrome using a set of selected metabolites and to determine whether the metabolites t…
An Emulator Toolbox to Approximate Radiative Transfer Models with Statistical Learning
2015
Physically-based radiative transfer models (RTMs) help in understanding the processes occurring on the Earth’s surface and their interactions with vegetation and atmosphere. When it comes to studying vegetation properties, RTMs allows us to study light interception by plant canopies and are used in the retrieval of biophysical variables through model inversion. However, advanced RTMs can take a long computational time, which makes them unfeasible in many real applications. To overcome this problem, it has been proposed to substitute RTMs through so-called emulators. Emulators are statistical models that approximate the functioning of RTMs. Emulators are advantageous in real practice because…
Customer Value Framework and Recommendation Intention: The Moderating Role of Customer Characteristics in an Online Travel Community
2019
The aim of this study was to develop and test a model that examined the interactions among the customer value framework, recommendation intention and customer characteristics in an online travel community (OTC). Data were obtained using Amazon Mechanical Turk from 251 members of an OTC as a sample. The partial least squares method was used to analyse the data. We found that all the variables of the customer value framework, including functional value, hedonic value and social value, were positively related to recommendation intention. In addition, using multi-group analyses, the study found differences between how different customer segments perceive each of the value dimensions and their e…
Optimal Spectral Wavelengths for Discriminating Orchard Species Using Multivariate Statistical Techniques
2019
Sustainable management of orchard fields requires detailed information about the tree types, which is a main component of precision agriculture programs. To this end, hyperspectral imagery can play a major role in orchard tree species mapping. Efficient use of hyperspectral data in combination with field measurements requires the development of optimized band selection strategies to separate tree species. In this study, field spectroscopy (350 to 2500 nm) was performed through scanning 165 spectral leaf samples of dominant orchard tree species (almond, walnut, and grape) in Chaharmahal va Bakhtiyari province, Iran. Two multivariable methods were employed to identify the optimum wavelengths:…