Search results for "Component analysis"
showing 10 items of 562 documents
Natural oxygenation of Champagne wine during ageing on lees: A metabolomics picture of hormesis
2016
International audience; The oxygenation of Champagne wine after 4 and 6 years of aging on lees in bottle was investigated by FTICR-MS and UPLC-Q-TOF-MS. Three levels of permeability were considered for the stoppers, ranging from 0.2 to 1.8 mg/L/year of oxygen transfer rate. Our results confirmed a good repeatability of ultrahigh resolution FTICR-MS, both in terms of m/z and coefficient of variation of peak intensities among biological replicates. Vintages appeared to be the most discriminated features, and metabolite annotations suggested that the oldest wines (2006) were characterized by a higher sensitivity towards oxygenation. Within each vintage, the oxygenation mechanisms appeared to b…
Polychlorinated Biphenyls in Sediments from Sicilian Coastal Area (Scoglitti) using Automated Soxhlet, GC-MS, and Principal Component Analysis
2014
A methodology for the PAHs and PCBs congener determination in sediment samples has been revised. We determined the distributions of PAHs and PCBs in the superficial sediments of the Scoglitti (Italy) coastal area to provide data for comparison with other marine systems and to hypothesize the sources. Extraction yield, for PCB, was never less than 60% in most cases, while for PAHs, utilizing perdeuterated surrogate standard (benz[a]anthracene-d12 and anthracene-d10) was never less than 72%. The total concentration of the 16 PAHs investigated, expressed as the sum of concentrations, PAHs, varied from 1–5087 μg/kg of dry matrix, while the PCBs ranged from detection limit to 36 μg/kg of dry mat…
Applying fully tensorial ICA to fMRI data
2016
There are two aspects in functional magnetic resonance imaging (fMRI) data that make them awkward to analyse with traditional multivariate methods - high order and high dimension. The first of these refers to the tensorial nature of observations as array-valued elements instead of vectors. Although this can be circumvented by vectorizing the array, doing so simultaneously loses all the structural information in the original observations. The second aspect refers to the high dimensionality along each dimension making the concept of dimension reduction a valuable tool in the processing of fMRI data. Different methods of tensor dimension reduction are currently gaining popUlarity in literature…
Identifying critical factors for implementing good agricultural practice
2009
En este artículo se presenta la identificación de los factores críticos (FC) que afectan la implantación de un programa de buenas prácticas agrícolas (BPA) en productores de café y frutas del departamento del Huila, en Colombia, mediante la realización de un análisis factorial exploratorio utilizando como método de factorización el análisis de componentes principales (ACP); las matrices de datos se construyeron con los resultados de la aplicación de sendos instrumentos con estructura definida en las dos poblaciones objeto de estudio, el instrumento Starbucks C.A.F.E. Practices -para pequeños caficultores en el caso de los productores de café- y EUREPGAP V2.1 Oct.2004 - Checklist-listado de …
A data-driven surrogate-assisted evolutionary algorithm applied to a many-objective blast furnace optimization problem
2017
A new data-driven reference vector-guided evolutionary algorithm has been successfully implemented to construct surrogate models for various objectives pertinent to an industrial blast furnace. A total of eight objectives have been modeled using the operational data of the furnace using 12 process variables identified through a principal component analysis and optimized simultaneously. The capability of this algorithm to handle a large number of objectives, which has been lacking earlier, results in a more efficient setting of the operational parameters of the furnace, leading to a precisely optimized hot metal production process. peerReviewed
Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R
2019
We present the R package clustrd which implements a class of methods that combine dimension reduction and clustering of continuous or categorical data. In particular, for continuous data, the package contains implementations of factorial K-means and reduced K-means; both methods combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means, i-FCB and cluster correspondence analysis, which combine multiple correspondence analysis with K-means. Two examples on real data sets are provided to illustrate the usage of the main functions.
Automated detection and localization system of myocardial infarction in single-beat ECG using Dual-Q TQWT and wavelet packet tensor decomposition
2020
Background and objective. It is challenging to conduct real-time identification of myocardial infarction (MI) due to artifact corruption and high dimensionality of multi-lead electrocardiogram (ECG). In the present study, we proposed an automated single-beat MI detection and localization system using dual-Q tunable Q-factor wavelet transformation (Dual-Q TQWT) denoising algorithm. Methods. After denoising and segmentation of ECG, a fourth-order wavelet tensor (leads × subbands × samples × beats) was constructed based on thediscretewavelet packet transform (DWPT), to represent the features considering the information of inter-beat, intra-beat, inter-frequency, and inter-lead. To reduce the t…
Principal Component and Neural Network Analyses of Face Images: What Can Be Generalized in Gender Classification?
1998
We present an overview of the major findings of the principal component analysis (pca) approach to facial analysis. In a neural network or connectionist framework, this approach is known as the linear autoassociator approach. Faces are represented as a weighted sum of macrofeatures (eigenvectors or eigenfaces) extracted from a cross-product matrix of face images. Using gender categorization as an illustration, we analyze the robustness of this type of facial representation. We show that eigenvectors representing general categorical information can be estimated using a very small set of faces and that the information they convey is generalizable to new faces of the same population and to a l…
Atlas construction and image analysis using statistical cardiac models
2010
International audience; This paper presents a brief overview of current trends in the construction of population and multi-modal heart atlases in our group and their application to atlas-based cardiac image analysis. The technical challenges around the construction of these atlases are organized around two main axes: groupwise image registration of anatomical, motion and fiber images and construction of statistical shape models. Application-wise, this paper focuses on the extraction of atlas-based biomarkers for the detection of local shape or motion abnormalities, addressing several cardiac applications where the extracted information is used to study and grade different pathologies. The p…
Sperm kinematics and morphometric subpopulations analysis with CASA systems: a review
2019
Sperm kinematics and morphometric subpopulations analysis with CASA systems: a review. The subjective evaluation of seminal quality has given way to the use of objective assessment techniques by CASA technology (computer-assisted semen analysis). The application of principal components (PC) and clustering methods to reveal subpopulations of spermatozoa is a powerful tool to evaluate raw semen and processed cell suspensions, but not many researchers are aware of the technique. PC analysis is a multivariate statistical method that reduces the number of variables used in subsequent calculations used to describe the data. By integrating the original variables according to their coherence in a d…