Search results for "STATISTICS"

showing 10 items of 7671 documents

Characterization of chromatographic peaks using the linearly modified Gaussian model. Comparison with the bi-Gaussian and the Foley and Dorsey approa…

2017

To characterize column performance in liquid chromatography, several parameters must be obtained from experimental data. These parameters can be computed through the numerical integration of the net signal to calculate the moments after subtraction of the baseline. This requires the establishment of the peak integration limits. The whole process introduces significant uncertainty. For this reason, several alternative procedures have been proposed to measure the area, mean time and variance, based on the assumption that the chromatographic peak can be described with a mathematical function. This allows the calculation of the peak position and variance making use of the values of the experime…

ChromatographyChemistryGaussianmedia_common.quotation_subject010401 analytical chemistryOrganic ChemistryGeneral MedicineVariance (accounting)010402 general chemistry01 natural sciencesBiochemistryMeasure (mathematics)Asymmetry0104 chemical sciencesAnalytical ChemistryNumerical integrationsymbols.namesakePosition (vector)Linear ModelssymbolsRange (statistics)Gaussian network modelChromatography Liquidmedia_commonJournal of Chromatography A
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Levels in the interpretive optimisation of selectivity in high-performance liquid chromatography: a magical mystery tour.

2006

Interpretive approaches for selectivity optimisation, which are those supported by retention models, are able to exploit efficiently the capabilities of the chromatographic system. The resolution of a mixture is usually faced in a first trial by looking for a unique experimental condition, able to resolve all compounds in the sample. If this is not possible, the problem can be outlined with less ambitious aims, focusing on only some compounds. In an extreme case, a single analyte can be individually optimised. Current strategies that give answer to the different goals pursued in the analysis, which are classified as total, partial and specific, are reviewed. Optimisation oriented to deconvo…

ChromatographyExploitChemistryComputer aidOrganic ChemistryAdrenergic beta-AntagonistsReproducibility of ResultsSample (statistics)General MedicineResolution (logic)Models TheoreticalBiochemistryHydrocarbons AromaticAnalytical ChemistryMultivariate AnalysisGradient elutionDeconvolutionAmino AcidsChromatography High Pressure LiquidJournal of chromatography. A
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Accuracy, Reliability, and Safety of Luminol in Bloodstain Investigation

2002

ABSTRACTThe reliability of luminol as a presumptive test reagent was studied in this work. The possibility of obtaining a false negative subsequent to contamination of the test specimen was determined. The behavior of luminol with respect to a contaminant was compared to other reagents used in similar tests. Following an analysis of the test results, other test sensitivity, and safety data, it was concluded that luminol is a more reliable reagent than others due to a higher improbability of producing false positives and false negatives, apart from being safer than other substances. It should, therefore, be considered as a “preferable” or “first choice” reagent for use in presumptive tests.

ChromatographyInjury controlAccident preventionbusiness.industryFalse positives and false negativesEnvironmental engineeringnutritional and metabolic diseasesPoison controlchemical and pharmacologic phenomenaTest sensitivityPathology and Forensic MedicineLuminolchemistry.chemical_compoundchemistryReagentMedicinebusinessReliability (statistics)Canadian Society of Forensic Science Journal
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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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Reliability of the retention factor estimations in liquid chromatography.

2004

The retention factor is one of the most universally used parameters in chromatography. However, large differences in the experimental retention factor values are observed when the same compound is injected in a given stationary/mobile phase system under intermediate precision conditions. Conventional protocols for estimating retention factors have problems that mainly arise from difficulties in the hold-up time measurements and the omission of the existence of extra-column times by practicing chromatographers. In the present paper, three different approaches for estimating retention factors are tested: (i) classical retention factor estimations based on the gross hold-up time, (ii) based on…

ChromatographyMicellar liquid chromatographyChemistryOrganic ChemistrySpectrophotometry UltravioletGeneral MedicineBiochemistryRetention timeReliability (statistics)Analytical ChemistryChromatography LiquidJournal of chromatography. A
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Net analyte signal as a deconvolution-oriented resolution criterion in the optimisation of chromatographic techniques

2003

The performance of two multivariate calibration measurements, multivariate selectivity (SEL(s)) and scalar net analyte signal (scalar NAS), as chromatographic objective functions (COFs), was investigated. Since both assessments are straightforwardly related to the quantification of analytes in the presence of interferents, they were expected to confer new features in the optimisation of compound resolution, not present in conventional assessments. These capabilities are especially interesting in situations of low resolution, where peak deconvolution becomes an attractive alternative. For comparison purposes, chromatographic resolution (R(s)) and peak purity (p(s)) were used as reference COF…

ChromatographyMultivariate statisticsAnalyteAcetonitrilesChromatographyResolution (mass spectrometry)ChemistryMethanolOrganic ChemistryAnalytical chemistryPhase (waves)Scalar (physics)WaterMultivariate calibrationGeneral MedicineModels TheoreticalHydrocarbons AromaticBiochemistrySignalAnalytical ChemistryCalibrationMultivariate AnalysisSolventsDeconvolutionChromatography High Pressure LiquidJournal of Chromatography A
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Overlapped moving windows followed by principal component analysis to extract information from chromatograms and application to classification analys…

2015

Variable generation from chromatograms is conveniently accomplished using unsupervised rather than manual techniques. With unsupervised techniques, there is no need for selecting a few peaks for manual integration and valuable information is quickly and efficiently collected. The generation of variables can be performed by using either peak searching or moving window (MW) strategies. With a MW approach, the peaks are ignored and many variables, only part of them carrying information, are generated. Thus, variable generation by MWs should be followed by data compression to generate the variables to be further used for classification or quantitation purposes. In this work, unsupervised proces…

Chromatographybusiness.industryGeneral Chemical EngineeringGeneral EngineeringPattern recognitionMoving windowLinear discriminant analysisAnalytical Chemistrylaw.inventionVariable (computer science)Window WidthlawPrincipal component analysisRange (statistics)Flame ionization detectorArtificial intelligencebusinessData compressionMathematicsAnalytical Methods
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Antibiotics and food in the American press

2021

AbstractThe emergence of antimicrobial resistant infections from food is well documented in the scientific literature but, in this kind of matter, the public opinion is an important policy driver and is vastly forged by traditional media. Here, we propose a text mining study through about 500 articles from two reference daily U.S. newspapers to assess the media coverage of this issue. Our results indicate that, since the middle of the 80s, the two journals considered here adopted a very different narrative around the issue, echoing civil society concerns in one case and the official discourse in the other.

Civil societybusiness.industry[SHS.INFO]Humanities and Social Sciences/Library and information sciences05 social sciencesMedia studiesMedia coverageScientific literature16. Peace & justicePublic opinion01 natural sciencesNewspaper010104 statistics & probabilityPolitical scienceNarrative0509 other social sciences0101 mathematics050904 information & library sciencesbusiness
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An output-only stochastic parametric approach for the identification of linear and nonlinear structures under random base excitations: Advances and c…

2014

In this paper a time domain output-only Dynamic Identification approach for Civil Structures (DICS) first formulated some years ago is reviewed and presented in a more generalized form. The approach in question, suitable for multi- and single-degrees-of-freedom systems, is based on the statistical moments and on the correlation functions of the response to base random excitations. The solving equations are obtained by applying the Itô differential stochastic calculus to some functions of the response. In the previous version ([21] Cavaleri, 2006; [22] Benfratello et al., 2009), the DICS method was based on the use of two classes of models (Restricted Potential Models and Linear Mass Proport…

Civil structureMathematical optimizationBase excitationGeneralizationMechanical EngineeringSystem identificationStochastic calculusAerospace EngineeringOcean EngineeringStatistical and Nonlinear PhysicsWhite noiseWhite noiseCondensed Matter PhysicsNonlinear systemSettore ICAR/09 - Tecnica Delle CostruzioniNuclear Energy and EngineeringNonlinear stiffneApplied mathematicsNonlinear dampingTime domainSystem identificationCivil and Structural EngineeringMathematicsParametric statisticsEquation solving
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Incremental linear model trees on massive datasets

2013

The existence of massive datasets raises the need for algorithms that make efficient use of resources like memory and computation time. Besides well-known approaches such as sampling, online algorithms are being recognized as good alternatives, as they often process datasets faster using much less memory. The important class of algorithms learning linear model trees online (incremental linear model trees or ILMTs in the following) offers interesting options for regression tasks in this sense. However, surprisingly little is known about their performance, as there exists no large-scale evaluation on massive stationary datasets under equal conditions. Therefore, this paper shows their applica…

Class (computer programming)Computer scienceProcess (engineering)business.industryComputationLinear modelSampling (statistics)computer.software_genreMachine learningKISS principleData miningArtificial intelligenceOnline algorithmbusinesscomputerProceedings of the 28th Annual ACM Symposium on Applied Computing
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