Search results for "principal component analysi"

showing 10 items of 489 documents

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…

education.field_of_studyArtificial neural networkbusiness.industryApplied MathematicsPopulationPattern recognitionMachine learningcomputer.software_genreComputingMethodologies_PATTERNRECOGNITIONEigenfaceCategorizationRobustness (computer science)Face (geometry)Principal component analysisArtificial intelligencebusinesseducationcomputerCategorical variableGeneral PsychologyMathematicsJournal of Mathematical Psychology
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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…

education.field_of_studySpermatozoonmedicine.diagnostic_testurogenital systemPopulationSemenBiologySemen analysisSpermmedicine.anatomical_structureEvolutionary biologyPrincipal component analysismedicineGeneral Agricultural and Biological SciencesCluster analysiseducationSperm competitionRevista de Biología Tropical
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Application of Electronic Nose for Evaluation of Wastewater Treatment Process Effects at Full-Scale WWTP

2019

This paper presents the results of studies aiming at the assessment and classification of wastewater using an electronic nose. During the experiment, an attempt was made to classify the medium based on an analysis of signals from a gas sensor array, the intensity of which depended on the levels of volatile compounds in the headspace gas mixture above the wastewater table. The research involved samples collected from the mechanical and biological treatment devices of a full-scale wastewater treatment plant (WWTP), as well as wastewater analysis. The measurements were carried out with a metal-oxide-semiconductor (MOS) gas sensor array, when coupled with a computing unit (e.g., a computer with…

electronic noseBioengineering010501 environmental scienceslcsh:Chemical technology01 natural scienceslcsh:ChemistrySensor arraywastewater treatment processesChemical Engineering (miscellaneous)lcsh:TP1-1185multidimensional data analysisProcess engineering0105 earth and related environmental sciencesMultidimensional analysisElectronic nosebusiness.industryProcess Chemistry and TechnologyDimensionality reduction010401 analytical chemistrySupervised learningodor nuisances0104 chemical sciencesgas sensor arraylcsh:QD1-999WastewaterPrincipal component analysiswastewater qualityEnvironmental scienceSewage treatmentbusinessProcesses
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Prototyping Crop Traits Retrieval Models for CHIME: Dimensionality Reduction Strategies Applied to PRISMA Data

2022

In preparation for new-generation imaging spectrometer missions and the accompanying unprecedented inflow of hyperspectral data, optimized models are needed to generate vegetation traits routinely. Hybrid models, combining radiative transfer models with machine learning algorithms, are preferred, however, dealing with spectral collinearity imposes an additional challenge. In this study, we analyzed two spectral dimensionality reduction methods: principal component analysis (PCA) and band ranking (BR), embedded in a hybrid workflow for the retrieval of specific leaf area (SLA), leaf area index (LAI), canopy water content (CWC), canopy chlorophyll content (CCC), the fraction of absorbed photo…

feature selectionCHIMEactive learningGeneral Earth and Planetary Scienceshybrid methodPRISMAprincipal component analysibiochemical and biophysical traitGaussian process regressionPRISMA; CHIME; hybrid methods; biochemical and biophysical traits; Gaussian process regression; active learning; principal component analysis; feature selectionRemote Sensing
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Adulteration detection of argan oil by inductively coupled plasma optical emission spectrometry

2010

Abstract The singularity of the trace element profile of argan oil has been demonstrated by means of inductively coupled plasma optical emission measurement in combination with different chemometric approaches. The ability of multivariate analysis methods; such as hierarchical cluster analysis (HCA), principal component analysis (PCA), classification trees using Chi -squared Automatic Interaction Detector (CHAID) and discriminant analysis (DA) to achieve edible oils classification based on its type or variety from their elemental content have been investigated. The calculations were performed using 16 variables (contents of Na, Mg, Al, K, Ca, Ti, Fe, Co, Ni, Cu, Zn, Cd, Pr, Sm, Er and Bi at…

food.ingredientChromatographyChemistrySunflower oilAnalytical chemistryTrace elementArgan oilGeneral MedicineSunflowerAnalytical ChemistryChemometricsfoodVegetable oilPrincipal component analysisInductively coupled plasmaFood ScienceFood Chemistry
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1H NMR-based metabolic profiling for evaluating poppy seed rancidity and brewing

2015

Poppy seeds are widely used in household and commercial confectionery. The aim of this study was to demonstrate the application of metabolic profiling for industrial monitoring of the molecular changes which occur during minced poppy seed rancidity and brewing processes performed on raw seeds. Both forms of poppy seeds were obtained from a confectionery company. Proton nuclear magnetic resonance (1H NMR) was applied as the analytical method of choice together with multivariate statistical data analysis. Metabolic fingerprinting was applied as a bioprocess control tool to monitor rancidity with the trajectory of change and brewing progressions. Low molecular weight compounds were found to be…

food.ingredientProton Magnetic Resonance SpectroscopyGerminationPoppy seedBiochemistryChemometricsfoodMetabolomicsPoppyPapaverFood scienceBioprocessMolecular BiologyPrincipal Component Analysisbiologybusiness.industryTemperatureDiscriminant Analysisfood and beveragesCell Biologybiology.organism_classificationBiotechnologyPapaverSeedsMetabolomeProton NMRBrewingbusinessBiomarkersCellular and Molecular Biology Letters
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Characterization of Sicilian Olive Genotypes by Multivariate Analysis of Leaf and Fruit Chemical and Morphological Properties

2013

Leaf and fruit size and shape were measured and mannitol, glucose, sucrose and malic acid were quantified in leaf, bark and fruit of 25 Sicilian olive genotypes. Multivariate analysis was used to individuate groups with similar chemical composition and morphological traits suggesting potential for stress tolerance and/or oil yield and quality. Mannitol content varied greatly among genotypes and was the most abundant carbohydrate in leaf and bark, whereas glucose was the most abundant in fruit. Sucrose and malic acid were generally low indicating a marginal role in olive tissues. Mannitol and glucose were directly related in both leaf and fruit tissues. Genotypes also differed for carbohydra…

glucose leaf size linear discriminant analysis mannitol principal component analysis sucroseSucroseAbiotic stressfungifood and beveragesBiologyCarbohydrateSettore AGR/03 - Arboricoltura Generale E Coltivazioni ArboreeHorticultureOleic acidchemistry.chemical_compoundchemistryPolyphenolvisual_artBotanyvisual_art.visual_art_mediummedicineBarkMalic acidMannitolmedicine.drugJournal of Agricultural Science
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Hippocampal event-related potentials to tone-CS during classical conditioning of the rabbit nictitating membrane response

2004

hippocampusprincipal component analysisdelay classical conditioningevent-related potentialsrabbit nictitating membrane response
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ANALYSING RELATIONSHIPS BETWEEN URBAN LAND USE FRAGMENTATION METRICS AND SOCIO-ECONOMIC VARIABLES

2016

Abstract. Analysing urban regions is essential for their correct monitoring and planning. This is mainly accounted for the sharp increase of people living in urban areas, and consequently, the need to manage them. At the same time there has been a rise in the use of spatial and statistical datasets, such as the Urban Atlas, which offers high-resolution urban land use maps obtained from satellite imagery, and the Urban Audit, which provides statistics of European cities and their surroundings. In this study, we analyse the relations between urban fragmentation metrics derived from Land Use and Land Cover (LULC) data from the Urban Atlas dataset, and socio-economic data from the Urban Audit f…

lcsh:Applied optics. Photonics010504 meteorology & atmospheric sciencesLand usebusiness.industrylcsh:TEnvironmental resource management0211 other engineering and technologieslcsh:TA1501-1820021107 urban & regional planning02 engineering and technologyAuditLand coverUrban land01 natural scienceslcsh:TechnologyGeographylcsh:TA1-2040Linear regressionPrincipal component analysisSatellite imagerybusinesslcsh:Engineering (General). Civil engineering (General)Cartography0105 earth and related environmental sciencesThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Hazardous air pollutants and primary liver cancer in Texas.

2016

The incidence of hepatocellular carcinoma (HCC), the most common primary liver cancer, is increasing in the US and tripled during the past two decades. The reasons for such phenomenon remain poorly understood. Texas is among continental states with the highest incidence of liver cancer with an annual increment of 5.7%. Established risk factors for HCC include Hepatitis B and C (HBV, HCV) viral infection, alcohol, tobacco and suspected risk factors include obesity and diabetes. While distribution of these risk factors in the state of Texas is similar to the national data and homogeneous, the incidence of HCC in this state is exceptionally higher than the national average and appears to be di…

lcsh:Medicine010501 environmental sciences01 natural sciencesGeographical locations0302 clinical medicineRisk FactorsEpidemiology of cancerMedicine and Health SciencesMedicineOrganic Chemicalslcsh:Scienceeducation.field_of_studyAir PollutantsPrincipal Component AnalysisMultidisciplinaryOrganic CompoundsIncidence (epidemiology)IncidenceLiver DiseasesLiver NeoplasmsHepatitis BTexasPollutionChemistryOncology030220 oncology & carcinogenesisPhysical SciencesEngineering and TechnologyLiver cancerEnvironmental MonitoringResearch ArticlePollutantsCarcinoma HepatocellularEnvironmental EngineeringPopulationGastroenterology and HepatologyXylenesCarcinomas03 medical and health sciencesEnvironmental healthAir PollutionAromatic HydrocarbonsGastrointestinal TumorsHumansEnvironmental ChemistryRisk factoreducation0105 earth and related environmental sciencesbusiness.industrylcsh:REcology and Environmental SciencesOrganic ChemistryChemical CompoundsCancerCancers and NeoplasmsBenzeneEnvironmental ExposureHepatocellular Carcinomamedicine.diseaseUnited StatesHydrocarbonsCancer registryNorth Americalcsh:QHydrochloric AcidPeople and placesbusinessAcidsToluenePloS one
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