Search results for "Principal component"

showing 10 items of 514 documents

L-band vegetation optical depth seasonal metrics for crop yield assessment

2018

Attenuation of surface microwave emission due to the overlying vegetation is proportional to the density of the canopy and to its water content. The vegetation optical depth (VOD) parameter measures this attenuation. VOD could be a valuable source of information on agroecosystems, especially at lower frequencies for which greater portion of the vegetation canopy contributes to the observed brightness temperature. In the past, visible-infrared indices have been used to provide yield estimates based on measuring the photosynthetic activity from the surface canopy layer. These indices are affected by clouds and apply only in the presence of solar illumination. In this study we instead use the …

CanopyTeledetecció010504 meteorology & atmospheric sciencesYield (finance)0211 other engineering and technologiesSoil Science02 engineering and technologyradiometryAtmospheric sciencesSMAPA01 natural sciencesStandard deviationopticalCrop yieldComputers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingVegetationCrop yieldMicrowave radiometerGeologyVegetation:Enginyeria de la telecomunicació [Àrees temàtiques de la UPC]Remote sensinggroecosystemsdepthL-bandPrincipal component analysisSpatial ecologyEnvironmental science
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Rethinking the sGLOH Descriptor

2018

sGLOH (shifting GLOH) is a histogram-based keypoint descriptor that can be associated to multiple quantized rotations of the keypoint patch without any recomputation. This property can be exploited to define the best distance between two descriptor vectors, thus avoiding computing the dominant orientation. In addition, sGLOH can reject incongruous correspondences by adding a global constraint on the rotations either as an a priori knowledge or based on the data. This paper thoroughly reconsiders sGLOH and improves it in terms of robustness, speed and descriptor dimension. The revised sGLOH embeds more quantized rotations, thus yielding more correct matches. A novel fast matching scheme is a…

Cascade matching0209 industrial biotechnologyHistogram binarizationRFDComputer scienceGLOHComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyCNN descriptorLIOP020901 industrial engineering & automationMROGHArtificial IntelligenceRobustness (computer science)Keypoint matchingSIFTHistogram0202 electrical engineering electronic engineering information engineeringSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticabusiness.industryApplied MathematicsCognitive neuroscience of visual object recognitionPattern recognitionRotation invariant descriptorsGLOHMIOPComputational Theory and MathematicsKeypoint matching SIFT sGLOH RFDs LIOP MIOP MROGH CNN descriptors rotation invariant descriptors histogram binarization cascade matchingPrincipal component analysis020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftware
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Computational identification of cell-specific variable regions in ChIP-seq data.

2019

ABSTRACT Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is used to identify genome-wide DNA regions bound by proteins. Several sources of variation can affect the reproducibility of a particular ChIP-seq assay, which can lead to a misinterpretation of where the protein under investigation binds to the genome in a particular cell type. Given one ChIP-seq experiment with replicates, binding sites not observed in all the replicates will usually be interpreted as noise and discarded. However, the recent discovery of high-occupancy target (HOT) regions suggests that there are regions where binding of multiple transcription factors can be identified. To investigate these regions,…

Cell typeAcademicSubjects/SCI00010Computational biologyPlasma protein bindingBiologyGenomeCell LineEvolution Molecular03 medical and health scienceschemistry.chemical_compoundMice0302 clinical medicineNarese/3Cell Line TumorGeneticsAnimalsHumansEpigeneticsBinding sitePromoter Regions GeneticTranscription factorEmbryonic Stem Cells030304 developmental biology0303 health sciencesPrincipal Component AnalysisBinding SitesNucleotidesGenetic VariationPromoterGenomicsChromatinchemistryCpG siteMCF-7 CellsChromatin Immunoprecipitation SequencingMethods OnlineR-Loop StructuresK562 CellsChromatin immunoprecipitation030217 neurology & neurosurgeryFunction (biology)DNATranscription FactorsNucleic acids research
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Cellular automata and urban development simulation : a transition rules creation process based on statistical analysis

2015

National audience; Nowadays land use evolution study has become a major stake in urban planning. The main focus is to understand the way in which land use evolves across time and to understand processes that take place. This understanding would allow to plan urban developments based on a knowledge as complete as possible covering as many fields as possible (i.e. urban planning, politics, sociology, etc.). Simulation tools can be used to merge and display different points of view and stakes from different stakeholders (Parrott & Meyer, 2012).

Cellular automataspatial analysisprincipal component analysis[SHS.GEO] Humanities and Social Sciences/Geographydecision tree[SHS.GEO]Humanities and Social Sciences/Geographyhierarchical clustering[ SHS.GEO ] Humanities and Social Sciences/Geography
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Analysis of the sensitivity to the systematic error in least-squares regression models

2004

An algorithm that calculates the sensitivity to the systematic error of the fitted parameters of a least-squares regression model, with respect to the known parameters, is developed. The algorithm can be applied to mechanistic and empirical models, obtained by linear and non-linear regression, including principal component and partial least-squares. It can be useful in identifying those parameters or calibration regions that can influence other parameters and the response mostly, and thus, whose accuracy should be particularly procured. Other applications are the weighing of experimental points and the comparison of different models and regression methods in terms of its ability of amplifyi…

ChemistryCalibration (statistics)Regression analysisBiochemistryRegressionAnalytical ChemistryPrincipal component analysisLinear regressionStatisticsEnvironmental ChemistryErrors-in-variables modelsSensitivity (control systems)Nonlinear regressionAlgorithmSpectroscopyAnalytica Chimica Acta
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Authentication of protected designation of origin artichokes by spectroscopy methods

2016

Abstract Artichoke samples with the protected designation of origin (PDO) ‘Alcachofa de Benicarlo’ were discriminated from those produced in other towns surrounding Valencia and Murcia, outside the PDO frame. Inductively coupled plasma (ICP-OES), near infrared (NIR) and X-ray fluorescence (XRF) were assayed in order to achieve a correct sample classification of the three different origin sample groups (Benicarlo, Valencia and Murcia). Chemometrics was used to compare the ability of classification of artichoke from their origin by using concentration data of mineral elements, determined by ICP-OES, NIR spectra and XRF spectra. Multivariate analysis tools, as principal component analysis (PCA…

ChemistrySpectroscopy methods010401 analytical chemistryAnalytical chemistry04 agricultural and veterinary sciences040401 food science01 natural sciencesData treatment0104 chemical sciencesChemometrics0404 agricultural biotechnologySample classificationPrincipal component analysisNir spectraFood ScienceBiotechnologyFood Control
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Evaluation of infrared spectroscopy as a screening tool for serum analysis

2013

Abstract The application of attenuated total reflectance Fourier transform infrared (ATR-FT-IR) spectroscopy to the determination of clinical parameters in serum using partial least squares (PLS) has been evaluated as a point-of-care diagnostic tool. In this study the effect of using an increased size of the calibration set and the influence of the origin of samples and their interyear variation on the prediction capability of the method were considered. PLS-ATR-FT-IR provides a green, fast and cheap point-of-care tool for the determination of total protein. Albumin, glucose, urea, HDL, LDL and total cholesterol were predicted with relative errors between 15 and 32%. The analytical predicti…

ChemometricsAnalyteStandard errorChemistryCalibration (statistics)Attenuated total reflectionPrincipal component analysisPartial least squares regressionStatisticsSample (statistics)SpectroscopyAnalytical ChemistryMicrochemical Journal
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Archaeopolymetallurgical study of materials from an Iberian culture site in Spain by scanning electron microscopy with X-ray microanalysis, chemometr…

2010

Abstract Archaeometallurgical materials from “La Bastida de Moixent”, a site in Valencia (Spain), from the second Iberian iron age (4th Century B.C.) have been studied using metallographic techniques, microanalysis, chemometrics and image analysis. The materials come from various phases of iron production and cupellation of argentiferous lead to obtain silver. Scanning electron microscopy (SEM) is used to determine the morphological, microstructural and topographic characteristics of the samples. Image analysis was used to obtain a numeric estimate of the main components in these materials. X-ray microanalysis (SEM/EDX) provides qualitative and quantitative information about the elements in…

ChemometricsCupellationMaterials scienceScanning electron microscopePrincipal component analysisMetallurgyMineralogyIron productionTechnical skillsMicroanalysisSpectroscopyAnalytical ChemistryX ray microanalysisMicrochemical Journal
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Multivariate data analysis and bivariate regression studies applied to comparison of two multi-elemental methods for analysing wine samples

2002

Two inductively coupled plasma mass spectrometry (ICP-MS) methods which permit multi-elemental analysis in wine samples have been compared following two strategies. First, a multivariate tool based on principal component analysis (PCA) was employed for a global (all analytes) qualitative comparison of the two methods. A single plot based on the confidence limits of the Q and T2 PCA model statistics corresponding to the ‘standard’ method results (calibration set) was used to check the comparability of the ‘candidate’ method (test samples). The residual matrix (after test matrix interpolation into the PCA model) gives qualitative information about the nature of the main errors. This approach …

ChemometricsMultivariate statisticsApplied MathematicsPrincipal component analysisStatisticsLinear regressionEconometricsBivariate analysisMissing dataLeast squaresAnalytical ChemistryMathematicsInterpolationJournal of Chemometrics
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Origin based classification of crude oils by infrared spectrometry and chemometrics

2019

Abstract Crude oil samples from different Iranian petrol resources in both, raw and mixture forms have been characterized by attenuated total reflectance mid infrared spectroscopy. Obtained spectra were classified by chemometric techniques to propose a method for geological based classification of crude oil samples. Totally 251 samples from 7 petrol fields and 3 mixtures were analyzed. Mean centering and principal component analysis (PCA) supported – leverage value based outlier detection were used as preprocessing approaches. PCA, cluster analysis and soft independent modeling of class analogy (SIMCA) were utilized to classify the spectra. Obtained results confirmed that SIMCA is a robust …

ChromatographyMean squared error020209 energyGeneral Chemical EngineeringOrganic ChemistryEnergy Engineering and Power TechnologyInfrared spectroscopy02 engineering and technologyChemometricsFuel TechnologyMean centering020401 chemical engineeringAttenuated total reflectionPrincipal component analysisLinear regression0202 electrical engineering electronic engineering information engineeringLeverage (statistics)0204 chemical engineeringMathematicsFuel
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