Sustained prediction ability of net analyte preprocessing methods using reduced calibration sets. Theoretical and experimental study involving the spectrophotometric analysis of multicomponent mixtures.

PubMed

Goicoechea, H C; Olivieri, A C

2001-07-01

A newly developed multivariate method involving net analyte preprocessing (NAP) was tested using central composite calibration designs of progressively decreasing size regarding the multivariate simultaneous spectrophotometric determination of three active components (phenylephrine, diphenhydramine and naphazoline) and one excipient (methylparaben) in nasal solutions. Its performance was evaluated and compared with that of partial least-squares (PLS-1). Minimisation of the calibration predicted error sum of squares (PRESS) as a function of a moving spectral window helped to select appropriate working spectral ranges for both methods. The comparison of NAP and PLS results was carried out using two tests: (1) the elliptical joint confidence region for the slope and intercept of a predicted versus actual concentrations plot for a large validation set of samples and (2) the D-optimality criterion concerning the information content of the calibration data matrix. Extensive simulations and experimental validation showed that, unlike PLS, the NAP method is able to furnish highly satisfactory results when the calibration set is reduced from a full four-component central composite to a fractional central composite, as expected from the modelling requirements of net analyte based methods.

Chemometrics resolution and quantification power evaluation: Application on pharmaceutical quaternary mixture of Paracetamol, Guaifenesin, Phenylephrine and p-aminophenol.

PubMed

Yehia, Ali M; Mohamed, Heba M

2016-01-05

Three advanced chemmometric-assisted spectrophotometric methods namely; Concentration Residuals Augmented Classical Least Squares (CRACLS), Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Principal Component Analysis-Artificial Neural Networks (PCA-ANN) were developed, validated and benchmarked to PLS calibration; to resolve the severely overlapped spectra and simultaneously determine; Paracetamol (PAR), Guaifenesin (GUA) and Phenylephrine (PHE) in their ternary mixture and in presence of p-aminophenol (AP) the main degradation product and synthesis impurity of Paracetamol. The analytical performance of the proposed methods was described by percentage recoveries, root mean square error of calibration and standard error of prediction. The four multivariate calibration methods could be directly used without any preliminary separation step and successfully applied for pharmaceutical formulation analysis, showing no excipients' interference. Copyright © 2015 Elsevier B.V. All rights reserved.

Simultaneous Determination of Metamizole, Thiamin and Pyridoxin Using UV-Spectroscopy in Combination with Multivariate Calibration

PubMed Central

Chotimah, Chusnul; Sudjadi; Riyanto, Sugeng; Rohman, Abdul

2015-01-01

Purpose: Analysis of drugs in multicomponent system officially is carried out using chromatographic technique, however, this technique is too laborious and involving sophisticated instrument. Therefore, UV-VIS spectrophotometry coupled with multivariate calibration of partial least square (PLS) for quantitative analysis of metamizole, thiamin and pyridoxin is developed in the presence of cyanocobalamine without any separation step. Methods: The calibration and validation samples are prepared. The calibration model is prepared by developing a series of sample mixture consisting these drugs in certain proportion. Cross validation of calibration sample using leave one out technique is used to identify the smaller set of components that provide the greatest predictive ability. The evaluation of calibration model was based on the coefficient of determination (R2) and root mean square error of calibration (RMSEC). Results: The results showed that the coefficient of determination (R2) for the relationship between actual values and predicted values for all studied drugs was higher than 0.99 indicating good accuracy. The RMSEC values obtained were relatively low, indicating good precision. The accuracy and presision results of developed method showed no significant difference compared to those obtained by official method of HPLC. Conclusion: The developed method (UV-VIS spectrophotometry in combination with PLS) was succesfully used for analysis of metamizole, thiamin and pyridoxin in tablet dosage form. PMID:26819934

Salting-out assisted liquid-liquid extraction and partial least squares regression to assay low molecular weight polycyclic aromatic hydrocarbons leached from soils and sediments

NASA Astrophysics Data System (ADS)

Bressan, Lucas P.; do Nascimento, Paulo Cícero; Schmidt, Marcella E. P.; Faccin, Henrique; de Machado, Leandro Carvalho; Bohrer, Denise

2017-02-01

A novel method was developed to determine low molecular weight polycyclic aromatic hydrocarbons in aqueous leachates from soils and sediments using a salting-out assisted liquid-liquid extraction, synchronous fluorescence spectrometry and a multivariate calibration technique. Several experimental parameters were controlled and the optimum conditions were: sodium carbonate as the salting-out agent at concentration of 2 mol L- 1, 3 mL of acetonitrile as extraction solvent, 6 mL of aqueous leachate, vortexing for 5 min and centrifuging at 4000 rpm for 5 min. The partial least squares calibration was optimized to the lowest values of root mean squared error and five latent variables were chosen for each of the targeted compounds. The regression coefficients for the true versus predicted concentrations were higher than 0.99. Figures of merit for the multivariate method were calculated, namely sensitivity, multivariate detection limit and multivariate quantification limit. The selectivity was also evaluated and other polycyclic aromatic hydrocarbons did not interfere in the analysis. Likewise, high performance liquid chromatography was used as a comparative methodology, and the regression analysis between the methods showed no statistical difference (t-test). The proposed methodology was applied to soils and sediments of a Brazilian river and the recoveries ranged from 74.3% to 105.8%. Overall, the proposed methodology was suitable for the targeted compounds, showing that the extraction method can be applied to spectrofluorometric analysis and that the multivariate calibration is also suitable for these compounds in leachates from real samples.

Sensitive analytical method for simultaneous analysis of some vasoconstrictors with highly overlapped analytical signals

NASA Astrophysics Data System (ADS)

Nikolić, G. S.; Žerajić, S.; Cakić, M.

2011-10-01

Multivariate calibration method is a powerful mathematical tool that can be applied in analytical chemistry when the analytical signals are highly overlapped. The method with regression by partial least squares is proposed for the simultaneous spectrophotometric determination of adrenergic vasoconstrictors in decongestive solution containing two active components: phenyleprine hydrochloride and trimazoline hydrochloride. These sympathomimetic agents are that frequently associated in pharmaceutical formulations against the common cold. The proposed method, which is, simple and rapid, offers the advantages of sensitivity and wide range of determinations without the need for extraction of the vasoconstrictors. In order to minimize the optimal factors necessary to obtain the calibration matrix by multivariate calibration, different parameters were evaluated. The adequate selection of the spectral regions proved to be important on the number of factors. In order to simultaneously quantify both hydrochlorides among excipients, the spectral region between 250 and 290 nm was selected. A recovery for the vasoconstrictor was 98-101%. The developed method was applied to assay of two decongestive pharmaceutical preparations.

Analysis of Lard in Lipstick Formulation Using FTIR Spectroscopy and Multivariate Calibration: A Comparison of Three Extraction Methods.

PubMed

Waskitho, Dri; Lukitaningsih, Endang; Sudjadi; Rohman, Abdul

2016-01-01

Analysis of lard extracted from lipstick formulation containing castor oil has been performed using FTIR spectroscopic method combined with multivariate calibration. Three different extraction methods were compared, namely saponification method followed by liquid/liquid extraction with hexane/dichlorometane/ethanol/water, saponification method followed by liquid/liquid extraction with dichloromethane/ethanol/water, and Bligh & Dyer method using chloroform/methanol/water as extracting solvent. Qualitative and quantitative analysis of lard were performed using principle component (PCA) and partial least square (PLS) analysis, respectively. The results showed that, in all samples prepared by the three extraction methods, PCA was capable of identifying lard at wavelength region of 1200-800 cm -1 with the best result was obtained by Bligh & Dyer method. Furthermore, PLS analysis at the same wavelength region used for qualification showed that Bligh and Dyer was the most suitable extraction method with the highest determination coefficient (R 2 ) and the lowest root mean square error of calibration (RMSEC) as well as root mean square error of prediction (RMSEP) values.

A novel multivariate approach using science-based calibration for direct coating thickness determination in real-time NIR process monitoring.

PubMed

Möltgen, C-V; Herdling, T; Reich, G

2013-11-01

This study demonstrates an approach, using science-based calibration (SBC), for direct coating thickness determination on heart-shaped tablets in real-time. Near-Infrared (NIR) spectra were collected during four full industrial pan coating operations. The tablets were coated with a thin hydroxypropyl methylcellulose (HPMC) film up to a film thickness of 28 μm. The application of SBC permits the calibration of the NIR spectral data without using costly determined reference values. This is due to the fact that SBC combines classical methods to estimate the coating signal and statistical methods for the noise estimation. The approach enabled the use of NIR for the measurement of the film thickness increase from around 8 to 28 μm of four independent batches in real-time. The developed model provided a spectroscopic limit of detection for the coating thickness of 0.64 ± 0.03 μm root-mean square (RMS). In the commonly used statistical methods for calibration, such as Partial Least Squares (PLS), sufficiently varying reference values are needed for calibration. For thin non-functional coatings this is a challenge because the quality of the model depends on the accuracy of the selected calibration standards. The obvious and simple approach of SBC eliminates many of the problems associated with the conventional statistical methods and offers an alternative for multivariate calibration. Copyright © 2013 Elsevier B.V. All rights reserved.

Application of the correlation constrained multivariate curve resolution alternating least-squares method for analyte quantitation in the presence of unexpected interferences using first-order instrumental data.

PubMed

Goicoechea, Héctor C; Olivieri, Alejandro C; Tauler, Romà

2010-03-01

Correlation constrained multivariate curve resolution-alternating least-squares is shown to be a feasible method for processing first-order instrumental data and achieve analyte quantitation in the presence of unexpected interferences. Both for simulated and experimental data sets, the proposed method could correctly retrieve the analyte and interference spectral profiles and perform accurate estimations of analyte concentrations in test samples. Since no information concerning the interferences was present in calibration samples, the proposed multivariate calibration approach including the correlation constraint facilitates the achievement of the so-called second-order advantage for the analyte of interest, which is known to be present for more complex higher-order richer instrumental data. The proposed method is tested using a simulated data set and two experimental data systems, one for the determination of ascorbic acid in powder juices using UV-visible absorption spectral data, and another for the determination of tetracycline in serum samples using fluorescence emission spectroscopy.

Comparative study between derivative spectrophotometry and multivariate calibration as analytical tools applied for the simultaneous quantitation of Amlodipine, Valsartan and Hydrochlorothiazide

NASA Astrophysics Data System (ADS)

Darwish, Hany W.; Hassan, Said A.; Salem, Maissa Y.; El-Zeany, Badr A.

2013-09-01

Four simple, accurate and specific methods were developed and validated for the simultaneous estimation of Amlodipine (AML), Valsartan (VAL) and Hydrochlorothiazide (HCT) in commercial tablets. The derivative spectrophotometric methods include Derivative Ratio Zero Crossing (DRZC) and Double Divisor Ratio Spectra-Derivative Spectrophotometry (DDRS-DS) methods, while the multivariate calibrations used are Principal Component Regression (PCR) and Partial Least Squares (PLSs). The proposed methods were applied successfully in the determination of the drugs in laboratory-prepared mixtures and in commercial pharmaceutical preparations. The validity of the proposed methods was assessed using the standard addition technique. The linearity of the proposed methods is investigated in the range of 2-32, 4-44 and 2-20 μg/mL for AML, VAL and HCT, respectively.

A graphical method to evaluate spectral preprocessing in multivariate regression calibrations: example with Savitzky-Golay filters and partial least squares regression.

PubMed

Delwiche, Stephen R; Reeves, James B

2010-01-01

In multivariate regression analysis of spectroscopy data, spectral preprocessing is often performed to reduce unwanted background information (offsets, sloped baselines) or accentuate absorption features in intrinsically overlapping bands. These procedures, also known as pretreatments, are commonly smoothing operations or derivatives. While such operations are often useful in reducing the number of latent variables of the actual decomposition and lowering residual error, they also run the risk of misleading the practitioner into accepting calibration equations that are poorly adapted to samples outside of the calibration. The current study developed a graphical method to examine this effect on partial least squares (PLS) regression calibrations of near-infrared (NIR) reflection spectra of ground wheat meal with two analytes, protein content and sodium dodecyl sulfate sedimentation (SDS) volume (an indicator of the quantity of the gluten proteins that contribute to strong doughs). These two properties were chosen because of their differing abilities to be modeled by NIR spectroscopy: excellent for protein content, fair for SDS sedimentation volume. To further demonstrate the potential pitfalls of preprocessing, an artificial component, a randomly generated value, was included in PLS regression trials. Savitzky-Golay (digital filter) smoothing, first-derivative, and second-derivative preprocess functions (5 to 25 centrally symmetric convolution points, derived from quadratic polynomials) were applied to PLS calibrations of 1 to 15 factors. The results demonstrated the danger of an over reliance on preprocessing when (1) the number of samples used in a multivariate calibration is low (<50), (2) the spectral response of the analyte is weak, and (3) the goodness of the calibration is based on the coefficient of determination (R(2)) rather than a term based on residual error. The graphical method has application to the evaluation of other preprocess functions and various types of spectroscopy data.

Total anthocyanin content determination in intact açaí (Euterpe oleracea Mart.) and palmitero-juçara (Euterpe edulis Mart.) fruit using near infrared spectroscopy (NIR) and multivariate calibration.

PubMed

Inácio, Maria Raquel Cavalcanti; de Lima, Kássio Michell Gomes; Lopes, Valquiria Garcia; Pessoa, José Dalton Cruz; de Almeida Teixeira, Gustavo Henrique

2013-02-15

The aim of this study was to evaluate near-infrared reflectance spectroscopy (NIR), and multivariate calibration potential as a rapid method to determinate anthocyanin content in intact fruit (açaí and palmitero-juçara). Several multivariate calibration techniques, including partial least squares (PLS), interval partial least squares, genetic algorithm, successive projections algorithm, and net analyte signal were compared and validated by establishing figures of merit. Suitable results were obtained with the PLS model (four latent variables and 5-point smoothing) with a detection limit of 6.2 g kg(-1), limit of quantification of 20.7 g kg(-1), accuracy estimated as root mean square error of prediction of 4.8 g kg(-1), mean selectivity of 0.79 g kg(-1), sensitivity of 5.04×10(-3) g kg(-1), precision of 27.8 g kg(-1), and signal-to-noise ratio of 1.04×10(-3) g kg(-1). These results suggest NIR spectroscopy and multivariate calibration can be effectively used to determine anthocyanin content in intact açaí and palmitero-juçara fruit. Copyright © 2012 Elsevier Ltd. All rights reserved.

A graphical method to evaluate spectral preprocessing in multivariate regression calibrations: example with Savitzky-Golay filters and partial least squares regression

USDA-ARS?s Scientific Manuscript database

In multivariate regression analysis of spectroscopy data, spectral preprocessing is often performed to reduce unwanted background information (offsets, sloped baselines) or accentuate absorption features in intrinsically overlapping bands. These procedures, also known as pretreatments, are commonly ...

Comparative study between derivative spectrophotometry and multivariate calibration as analytical tools applied for the simultaneous quantitation of Amlodipine, Valsartan and Hydrochlorothiazide.

PubMed

Darwish, Hany W; Hassan, Said A; Salem, Maissa Y; El-Zeany, Badr A

2013-09-01

Four simple, accurate and specific methods were developed and validated for the simultaneous estimation of Amlodipine (AML), Valsartan (VAL) and Hydrochlorothiazide (HCT) in commercial tablets. The derivative spectrophotometric methods include Derivative Ratio Zero Crossing (DRZC) and Double Divisor Ratio Spectra-Derivative Spectrophotometry (DDRS-DS) methods, while the multivariate calibrations used are Principal Component Regression (PCR) and Partial Least Squares (PLSs). The proposed methods were applied successfully in the determination of the drugs in laboratory-prepared mixtures and in commercial pharmaceutical preparations. The validity of the proposed methods was assessed using the standard addition technique. The linearity of the proposed methods is investigated in the range of 2-32, 4-44 and 2-20 μg/mL for AML, VAL and HCT, respectively. Copyright © 2013 Elsevier B.V. All rights reserved.

Multivariate calibration in Laser-Induced Breakdown Spectroscopy quantitative analysis: The dangers of a 'black box' approach and how to avoid them

NASA Astrophysics Data System (ADS)

Safi, A.; Campanella, B.; Grifoni, E.; Legnaioli, S.; Lorenzetti, G.; Pagnotta, S.; Poggialini, F.; Ripoll-Seguer, L.; Hidalgo, M.; Palleschi, V.

2018-06-01

The introduction of multivariate calibration curve approach in Laser-Induced Breakdown Spectroscopy (LIBS) quantitative analysis has led to a general improvement of the LIBS analytical performances, since a multivariate approach allows to exploit the redundancy of elemental information that are typically present in a LIBS spectrum. Software packages implementing multivariate methods are available in the most diffused commercial and open source analytical programs; in most of the cases, the multivariate algorithms are robust against noise and operate in unsupervised mode. The reverse of the coin of the availability and ease of use of such packages is the (perceived) difficulty in assessing the reliability of the results obtained which often leads to the consideration of the multivariate algorithms as 'black boxes' whose inner mechanism is supposed to remain hidden to the user. In this paper, we will discuss the dangers of a 'black box' approach in LIBS multivariate analysis, and will discuss how to overcome them using the chemical-physical knowledge that is at the base of any LIBS quantitative analysis.

Firefly algorithm versus genetic algorithm as powerful variable selection tools and their effect on different multivariate calibration models in spectroscopy: A comparative study

NASA Astrophysics Data System (ADS)

Attia, Khalid A. M.; Nassar, Mohammed W. I.; El-Zeiny, Mohamed B.; Serag, Ahmed

2017-01-01

For the first time, a new variable selection method based on swarm intelligence namely firefly algorithm is coupled with three different multivariate calibration models namely, concentration residual augmented classical least squares, artificial neural network and support vector regression in UV spectral data. A comparative study between the firefly algorithm and the well-known genetic algorithm was developed. The discussion revealed the superiority of using this new powerful algorithm over the well-known genetic algorithm. Moreover, different statistical tests were performed and no significant differences were found between all the models regarding their predictabilities. This ensures that simpler and faster models were obtained without any deterioration of the quality of the calibration.

Coping with matrix effects in headspace solid phase microextraction gas chromatography using multivariate calibration strategies.

PubMed

Ferreira, Vicente; Herrero, Paula; Zapata, Julián; Escudero, Ana

2015-08-14

SPME is extremely sensitive to experimental parameters affecting liquid-gas and gas-solid distribution coefficients. Our aims were to measure the weights of these factors and to design a multivariate strategy based on the addition of a pool of internal standards, to minimize matrix effects. Synthetic but real-like wines containing selected analytes and variable amounts of ethanol, non-volatile constituents and major volatile compounds were prepared following a factorial design. The ANOVA study revealed that even using a strong matrix dilution, matrix effects are important and additive with non-significant interaction effects and that it is the presence of major volatile constituents the most dominant factor. A single internal standard provided a robust calibration for 15 out of 47 analytes. Then, two different multivariate calibration strategies based on Partial Least Square Regression were run in order to build calibration functions based on 13 different internal standards able to cope with matrix effects. The first one is based in the calculation of Multivariate Internal Standards (MIS), linear combinations of the normalized signals of the 13 internal standards, which provide the expected area of a given unit of analyte present in each sample. The second strategy is a direct calibration relating concentration to the 13 relative areas measured in each sample for each analyte. Overall, 47 different compounds can be reliably quantified in a single fully automated method with overall uncertainties better than 15%. Copyright © 2015 Elsevier B.V. All rights reserved.

Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model.

PubMed

Snell, Kym I E; Hua, Harry; Debray, Thomas P A; Ensor, Joie; Look, Maxime P; Moons, Karel G M; Riley, Richard D

2016-01-01

Our aim was to improve meta-analysis methods for summarizing a prediction model's performance when individual participant data are available from multiple studies for external validation. We suggest multivariate meta-analysis for jointly synthesizing calibration and discrimination performance, while accounting for their correlation. The approach estimates a prediction model's average performance, the heterogeneity in performance across populations, and the probability of "good" performance in new populations. This allows different implementation strategies (e.g., recalibration) to be compared. Application is made to a diagnostic model for deep vein thrombosis (DVT) and a prognostic model for breast cancer mortality. In both examples, multivariate meta-analysis reveals that calibration performance is excellent on average but highly heterogeneous across populations unless the model's intercept (baseline hazard) is recalibrated. For the cancer model, the probability of "good" performance (defined by C statistic ≥0.7 and calibration slope between 0.9 and 1.1) in a new population was 0.67 with recalibration but 0.22 without recalibration. For the DVT model, even with recalibration, there was only a 0.03 probability of "good" performance. Multivariate meta-analysis can be used to externally validate a prediction model's calibration and discrimination performance across multiple populations and to evaluate different implementation strategies. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Firefly algorithm versus genetic algorithm as powerful variable selection tools and their effect on different multivariate calibration models in spectroscopy: A comparative study.

PubMed

Attia, Khalid A M; Nassar, Mohammed W I; El-Zeiny, Mohamed B; Serag, Ahmed

2017-01-05

For the first time, a new variable selection method based on swarm intelligence namely firefly algorithm is coupled with three different multivariate calibration models namely, concentration residual augmented classical least squares, artificial neural network and support vector regression in UV spectral data. A comparative study between the firefly algorithm and the well-known genetic algorithm was developed. The discussion revealed the superiority of using this new powerful algorithm over the well-known genetic algorithm. Moreover, different statistical tests were performed and no significant differences were found between all the models regarding their predictabilities. This ensures that simpler and faster models were obtained without any deterioration of the quality of the calibration. Copyright © 2016 Elsevier B.V. All rights reserved.

Simultaneous determination of potassium guaiacolsulfonate, guaifenesin, diphenhydramine HCl and carbetapentane citrate in syrups by using HPLC-DAD coupled with partial least squares multivariate calibration.

PubMed

Dönmez, Ozlem Aksu; Aşçi, Bürge; Bozdoğan, Abdürrezzak; Sungur, Sidika

2011-02-15

A simple and rapid analytical procedure was proposed for the determination of chromatographic peaks by means of partial least squares multivariate calibration (PLS) of high-performance liquid chromatography with diode array detection (HPLC-DAD). The method is exemplified with analysis of quaternary mixtures of potassium guaiacolsulfonate (PG), guaifenesin (GU), diphenhydramine HCI (DP) and carbetapentane citrate (CP) in syrup preparations. In this method, the area does not need to be directly measured and predictions are more accurate. Though the chromatographic and spectral peaks of the analytes were heavily overlapped and interferents coeluted with the compounds studied, good recoveries of analytes could be obtained with HPLC-DAD coupled with PLS calibration. This method was tested by analyzing the synthetic mixture of PG, GU, DP and CP. As a comparison method, a classsical HPLC method was used. The proposed methods were applied to syrups samples containing four drugs and the obtained results were statistically compared with each other. Finally, the main advantage of HPLC-PLS method over the classical HPLC method tried to emphasized as the using of simple mobile phase, shorter analysis time and no use of internal standard and gradient elution. Copyright © 2010 Elsevier B.V. All rights reserved.

Optimal Multicomponent Analysis Using the Generalized Standard Addition Method.

ERIC Educational Resources Information Center

Raymond, Margaret; And Others

1983-01-01

Describes an experiment on the simultaneous determination of chromium and magnesium by spectophotometry modified to include the Generalized Standard Addition Method computer program, a multivariate calibration method that provides optimal multicomponent analysis in the presence of interference and matrix effects. Provides instructions for…

Determination of fragrance content in perfume by Raman spectroscopy and multivariate calibration

NASA Astrophysics Data System (ADS)

Godinho, Robson B.; Santos, Mauricio C.; Poppi, Ronei J.

2016-03-01

An alternative methodology is herein proposed for determination of fragrance content in perfumes and their classification according to the guidelines established by fine perfume manufacturers. The methodology is based on Raman spectroscopy associated with multivariate calibration, allowing the determination of fragrance content in a fast, nondestructive, and sustainable manner. The results were considered consistent with the conventional method, whose standard error of prediction values was lower than the 1.0%. This result indicates that the proposed technology is a feasible analytical tool for determination of the fragrance content in a hydro-alcoholic solution for use in manufacturing, quality control and regulatory agencies.

Enzymatic electrochemical detection coupled to multivariate calibration for the determination of phenolic compounds in environmental samples.

PubMed

Hernandez, Silvia R; Kergaravat, Silvina V; Pividori, Maria Isabel

2013-03-15

An approach based on the electrochemical detection of the horseradish peroxidase enzymatic reaction by means of square wave voltammetry was developed for the determination of phenolic compounds in environmental samples. First, a systematic optimization procedure of three factors involved in the enzymatic reaction was carried out using response surface methodology through a central composite design. Second, the enzymatic electrochemical detection coupled with a multivariate calibration method based in the partial least-squares technique was optimized for the determination of a mixture of five phenolic compounds, i.e. phenol, p-aminophenol, p-chlorophenol, hydroquinone and pyrocatechol. The calibration and validation sets were built and assessed. In the calibration model, the LODs for phenolic compounds oscillated from 0.6 to 1.4 × 10(-6) mol L(-1). Recoveries for prediction samples were higher than 85%. These compounds were analyzed simultaneously in spiked samples and in water samples collected close to tanneries and landfills. Published by Elsevier B.V.

Predicting trauma patient mortality: ICD [or ICD-10-AM] versus AIS based approaches.

PubMed

Willis, Cameron D; Gabbe, Belinda J; Jolley, Damien; Harrison, James E; Cameron, Peter A

2010-11-01

The International Classification of Diseases Injury Severity Score (ICISS) has been proposed as an International Classification of Diseases (ICD)-10-based alternative to mortality prediction tools that use Abbreviated Injury Scale (AIS) data, including the Trauma and Injury Severity Score (TRISS). To date, studies have not examined the performance of ICISS using Australian trauma registry data. This study aimed to compare the performance of ICISS with other mortality prediction tools in an Australian trauma registry. This was a retrospective review of prospectively collected data from the Victorian State Trauma Registry. A training dataset was created for model development and a validation dataset for evaluation. The multiplicative ICISS model was compared with a worst injury ICISS approach, Victorian TRISS (V-TRISS, using local coefficients), maximum AIS severity and a multivariable model including ICD-10-AM codes as predictors. Models were investigated for discrimination (C-statistic) and calibration (Hosmer-Lemeshow statistic). The multivariable approach had the highest level of discrimination (C-statistic 0.90) and calibration (H-L 7.65, P= 0.468). Worst injury ICISS, V-TRISS and maximum AIS had similar performance. The multiplicative ICISS produced the lowest level of discrimination (C-statistic 0.80) and poorest calibration (H-L 50.23, P < 0.001). The performance of ICISS may be affected by the data used to develop estimates, the ICD version employed, the methods for deriving estimates and the inclusion of covariates. In this analysis, a multivariable approach using ICD-10-AM codes was the best-performing method. A multivariable ICISS approach may therefore be a useful alternative to AIS-based methods and may have comparable predictive performance to locally derived TRISS models. © 2010 The Authors. ANZ Journal of Surgery © 2010 Royal Australasian College of Surgeons.

Uncertainty Analysis of Inertial Model Attitude Sensor Calibration and Application with a Recommended New Calibration Method

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Statistical tools, previously developed for nonlinear least-squares estimation of multivariate sensor calibration parameters and the associated calibration uncertainty analysis, have been applied to single- and multiple-axis inertial model attitude sensors used in wind tunnel testing to measure angle of attack and roll angle. The analysis provides confidence and prediction intervals of calibrated sensor measurement uncertainty as functions of applied input pitch and roll angles. A comparative performance study of various experimental designs for inertial sensor calibration is presented along with corroborating experimental data. The importance of replicated calibrations over extended time periods has been emphasized; replication provides independent estimates of calibration precision and bias uncertainties, statistical tests for calibration or modeling bias uncertainty, and statistical tests for sensor parameter drift over time. A set of recommendations for a new standardized model attitude sensor calibration method and usage procedures is included. The statistical information provided by these procedures is necessary for the uncertainty analysis of aerospace test results now required by users of industrial wind tunnel test facilities.

Determination of fragrance content in perfume by Raman spectroscopy and multivariate calibration.

PubMed

Godinho, Robson B; Santos, Mauricio C; Poppi, Ronei J

2016-03-15

An alternative methodology is herein proposed for determination of fragrance content in perfumes and their classification according to the guidelines established by fine perfume manufacturers. The methodology is based on Raman spectroscopy associated with multivariate calibration, allowing the determination of fragrance content in a fast, nondestructive, and sustainable manner. The results were considered consistent with the conventional method, whose standard error of prediction values was lower than the 1.0%. This result indicates that the proposed technology is a feasible analytical tool for determination of the fragrance content in a hydro-alcoholic solution for use in manufacturing, quality control and regulatory agencies. Copyright © 2015 Elsevier B.V. All rights reserved.

Simultaneous determination of rifampicin, isoniazid and pyrazinamide in tablet preparations by multivariate spectrophotometric calibration.

PubMed

Goicoechea, H C; Olivieri, A C

1999-08-01

The use of multivariate spectrophotometric calibration is presented for the simultaneous determination of the active components of tablets used in the treatment of pulmonary tuberculosis. The resolution of ternary mixtures of rifampicin, isoniazid and pyrazinamide has been accomplished by using partial least squares (PLS-1) regression analysis. Although the components show an important degree of spectral overlap, they have been simultaneously determined with high accuracy and precision, rapidly and with no need of nonaqueous solvents for dissolving the samples. No interference has been observed from the tablet excipients. A comparison is presented with the related multivariate method of classical least squares (CLS) analysis, which is shown to yield less reliable results due to the severe spectral overlap among the studied compounds. This is highlighted in the case of isoniazid, due to the small absorbances measured for this component.

Strategic development of a multivariate calibration model for the uniformity testing of tablets by transmission NIR analysis.

PubMed

Sasakura, D; Nakayama, K; Sakamoto, T; Chikuma, T

2015-05-01

The use of transmission near infrared spectroscopy (TNIRS) is of particular interest in the pharmaceutical industry. This is because TNIRS does not require sample preparation and can analyze several tens of tablet samples in an hour. It has the capability to measure all relevant information from a tablet, while still on the production line. However, TNIRS has a narrow spectrum range and overtone vibrations often overlap. To perform content uniformity testing in tablets by TNIRS, various properties in the tableting process need to be analyzed by a multivariate prediction model, such as a Partial Least Square Regression modeling. One issue is that typical approaches require several hundred reference samples to act as the basis of the method rather than a strategically designed method. This means that many batches are needed to prepare the reference samples; this requires time and is not cost effective. Our group investigated the concentration dependence of the calibration model with a strategic design. Consequently, we developed a more effective approach to the TNIRS calibration model than the existing methodology.

Ratio manipulating spectrophotometry versus chemometry as stability indicating methods for cefquinome sulfate determination

NASA Astrophysics Data System (ADS)

Yehia, Ali M.; Arafa, Reham M.; Abbas, Samah S.; Amer, Sawsan M.

2016-01-01

Spectral resolution of cefquinome sulfate (CFQ) in the presence of its degradation products was studied. Three selective, accurate and rapid spectrophotometric methods were performed for the determination of CFQ in the presence of either its hydrolytic, oxidative or photo-degradation products. The proposed ratio difference, derivative ratio and mean centering are ratio manipulating spectrophotometric methods that were satisfactorily applied for selective determination of CFQ within linear range of 5.0-40.0 μg mL- 1. Concentration Residuals Augmented Classical Least Squares was applied and evaluated for the determination of the cited drug in the presence of its all degradation products. Traditional Partial Least Squares regression was also applied and benchmarked against the proposed advanced multivariate calibration. Experimentally designed 25 synthetic mixtures of three factors at five levels were used to calibrate and validate the multivariate models. Advanced chemometrics succeeded in quantitative and qualitative analyses of CFQ along with its hydrolytic, oxidative and photo-degradation products. The proposed methods were applied successfully for different pharmaceutical formulations analyses. These developed methods were simple and cost-effective compared with the manufacturer's RP-HPLC method.

Classical vs. evolved quenching parameters and procedures in scintillation measurements: The importance of ionization quenching

NASA Astrophysics Data System (ADS)

Bagán, H.; Tarancón, A.; Rauret, G.; García, J. F.

2008-07-01

The quenching parameters used to model detection efficiency variations in scintillation measurements have not evolved since the decade of 1970s. Meanwhile, computer capabilities have increased enormously and ionization quenching has appeared in practical measurements using plastic scintillation. This study compares the results obtained in activity quantification by plastic scintillation of 14C samples that contain colour and ionization quenchers, using classical (SIS, SCR-limited, SCR-non-limited, SIS(ext), SQP(E)) and evolved (MWA-SCR and WDW) parameters and following three calibration approaches: single step, which does not take into account the quenching mechanism; two steps, which takes into account the quenching phenomena; and multivariate calibration. Two-step calibration (ionization followed by colour) yielded the lowest relative errors, which means that each quenching phenomenon must be specifically modelled. In addition, the sample activity was quantified more accurately when the evolved parameters were used. Multivariate calibration-PLS also yielded better results than those obtained using classical parameters, which confirms that the quenching phenomena must be taken into account. The detection limits for each calibration method and each parameter were close to those obtained theoretically using the Currie approach.

Membrane Introduction Mass Spectrometry Combined with an Orthogonal Partial-Least Squares Calibration Model for Mixture Analysis.

PubMed

Li, Min; Zhang, Lu; Yao, Xiaolong; Jiang, Xingyu

2017-01-01

The emerging membrane introduction mass spectrometry technique has been successfully used to detect benzene, toluene, ethyl benzene and xylene (BTEX), while overlapped spectra have unfortunately hindered its further application to the analysis of mixtures. Multivariate calibration, an efficient method to analyze mixtures, has been widely applied. In this paper, we compared univariate and multivariate analyses for quantification of the individual components of mixture samples. The results showed that the univariate analysis creates poor models with regression coefficients of 0.912, 0.867, 0.440 and 0.351 for BTEX, respectively. For multivariate analysis, a comparison to the partial-least squares (PLS) model shows that the orthogonal partial-least squares (OPLS) regression exhibits an optimal performance with regression coefficients of 0.995, 0.999, 0.980 and 0.976, favorable calibration parameters (RMSEC and RMSECV) and a favorable validation parameter (RMSEP). Furthermore, the OPLS exhibits a good recovery of 73.86 - 122.20% and relative standard deviation (RSD) of the repeatability of 1.14 - 4.87%. Thus, MIMS coupled with the OPLS regression provides an optimal approach for a quantitative BTEX mixture analysis in monitoring and predicting water pollution.

Simultaneous determination of Nifuroxazide and Drotaverine hydrochloride in pharmaceutical preparations by bivariate and multivariate spectral analysis

NASA Astrophysics Data System (ADS)

Metwally, Fadia H.

2008-02-01

The quantitative predictive abilities of the new and simple bivariate spectrophotometric method are compared with the results obtained by the use of multivariate calibration methods [the classical least squares (CLS), principle component regression (PCR) and partial least squares (PLS)], using the information contained in the absorption spectra of the appropriate solutions. Mixtures of the two drugs Nifuroxazide (NIF) and Drotaverine hydrochloride (DRO) were resolved by application of the bivariate method. The different chemometric approaches were applied also with previous optimization of the calibration matrix, as they are useful in simultaneous inclusion of many spectral wavelengths. The results found by application of the bivariate, CLS, PCR and PLS methods for the simultaneous determinations of mixtures of both components containing 2-12 μg ml -1 of NIF and 2-8 μg ml -1 of DRO are reported. Both approaches were satisfactorily applied to the simultaneous determination of NIF and DRO in pure form and in pharmaceutical formulation. The results were in accordance with those given by the EVA Pharma reference spectrophotometric method.

Evaluation of multivariate calibration models with different pre-processing and processing algorithms for a novel resolution and quantitation of spectrally overlapped quaternary mixture in syrup

NASA Astrophysics Data System (ADS)

Moustafa, Azza A.; Hegazy, Maha A.; Mohamed, Dalia; Ali, Omnia

2016-02-01

A novel approach for the resolution and quantitation of severely overlapped quaternary mixture of carbinoxamine maleate (CAR), pholcodine (PHL), ephedrine hydrochloride (EPH) and sunset yellow (SUN) in syrup was demonstrated utilizing different spectrophotometric assisted multivariate calibration methods. The applied methods have used different processing and pre-processing algorithms. The proposed methods were partial least squares (PLS), concentration residuals augmented classical least squares (CRACLS), and a novel method; continuous wavelet transforms coupled with partial least squares (CWT-PLS). These methods were applied to a training set in the concentration ranges of 40-100 μg/mL, 40-160 μg/mL, 100-500 μg/mL and 8-24 μg/mL for the four components, respectively. The utilized methods have not required any preliminary separation step or chemical pretreatment. The validity of the methods was evaluated by an external validation set. The selectivity of the developed methods was demonstrated by analyzing the drugs in their combined pharmaceutical formulation without any interference from additives. The obtained results were statistically compared with the official and reported methods where no significant difference was observed regarding both accuracy and precision.

Determination of alcohol and extract concentration in beer samples using a combined method of near-infrared (NIR) spectroscopy and refractometry.

PubMed

Castritius, Stefan; Kron, Alexander; Schäfer, Thomas; Rädle, Matthias; Harms, Diedrich

2010-12-22

A new approach of combination of near-infrared (NIR) spectroscopy and refractometry was developed in this work to determine the concentration of alcohol and real extract in various beer samples. A partial least-squares (PLS) regression, as multivariate calibration method, was used to evaluate the correlation between the data of spectroscopy/refractometry and alcohol/extract concentration. This multivariate combination of spectroscopy and refractometry enhanced the precision in the determination of alcohol, compared to single spectroscopy measurements, due to the effect of high extract concentration on the spectral data, especially of nonalcoholic beer samples. For NIR calibration, two mathematical pretreatments (first-order derivation and linear baseline correction) were applied to eliminate light scattering effects. A sample grouping of the refractometry data was also applied to increase the accuracy of the determined concentration. The root mean squared errors of validation (RMSEV) of the validation process concerning alcohol and extract concentration were 0.23 Mas% (method A), 0.12 Mas% (method B), and 0.19 Mas% (method C) and 0.11 Mas% (method A), 0.11 Mas% (method B), and 0.11 Mas% (method C), respectively.

Comparative artificial neural network and partial least squares models for analysis of Metronidazole, Diloxanide, Spiramycin and Cliquinol in pharmaceutical preparations.

PubMed

Elkhoudary, Mahmoud M; Abdel Salam, Randa A; Hadad, Ghada M

2014-09-15

Metronidazole (MNZ) is a widely used antibacterial and amoebicide drug. Therefore, it is important to develop a rapid and specific analytical method for the determination of MNZ in mixture with Spiramycin (SPY), Diloxanide (DIX) and Cliquinol (CLQ) in pharmaceutical preparations. This work describes simple, sensitive and reliable six multivariate calibration methods, namely linear and nonlinear artificial neural networks preceded by genetic algorithm (GA-ANN) and principle component analysis (PCA-ANN) as well as partial least squares (PLS) either alone or preceded by genetic algorithm (GA-PLS) for UV spectrophotometric determination of MNZ, SPY, DIX and CLQ in pharmaceutical preparations with no interference of pharmaceutical additives. The results manifest the problem of nonlinearity and how models like ANN can handle it. Analytical performance of these methods was statistically validated with respect to linearity, accuracy, precision and specificity. The developed methods indicate the ability of the previously mentioned multivariate calibration models to handle and solve UV spectra of the four components' mixtures using easy and widely used UV spectrophotometer. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparative artificial neural network and partial least squares models for analysis of Metronidazole, Diloxanide, Spiramycin and Cliquinol in pharmaceutical preparations

NASA Astrophysics Data System (ADS)

Elkhoudary, Mahmoud M.; Abdel Salam, Randa A.; Hadad, Ghada M.

2014-09-01

Metronidazole (MNZ) is a widely used antibacterial and amoebicide drug. Therefore, it is important to develop a rapid and specific analytical method for the determination of MNZ in mixture with Spiramycin (SPY), Diloxanide (DIX) and Cliquinol (CLQ) in pharmaceutical preparations. This work describes simple, sensitive and reliable six multivariate calibration methods, namely linear and nonlinear artificial neural networks preceded by genetic algorithm (GA-ANN) and principle component analysis (PCA-ANN) as well as partial least squares (PLS) either alone or preceded by genetic algorithm (GA-PLS) for UV spectrophotometric determination of MNZ, SPY, DIX and CLQ in pharmaceutical preparations with no interference of pharmaceutical additives. The results manifest the problem of nonlinearity and how models like ANN can handle it. Analytical performance of these methods was statistically validated with respect to linearity, accuracy, precision and specificity. The developed methods indicate the ability of the previously mentioned multivariate calibration models to handle and solve UV spectra of the four components’ mixtures using easy and widely used UV spectrophotometer.

Ratio manipulating spectrophotometry versus chemometry as stability indicating methods for cefquinome sulfate determination.

PubMed

Yehia, Ali M; Arafa, Reham M; Abbas, Samah S; Amer, Sawsan M

2016-01-15

Spectral resolution of cefquinome sulfate (CFQ) in the presence of its degradation products was studied. Three selective, accurate and rapid spectrophotometric methods were performed for the determination of CFQ in the presence of either its hydrolytic, oxidative or photo-degradation products. The proposed ratio difference, derivative ratio and mean centering are ratio manipulating spectrophotometric methods that were satisfactorily applied for selective determination of CFQ within linear range of 5.0-40.0 μg mL(-1). Concentration Residuals Augmented Classical Least Squares was applied and evaluated for the determination of the cited drug in the presence of its all degradation products. Traditional Partial Least Squares regression was also applied and benchmarked against the proposed advanced multivariate calibration. Experimentally designed 25 synthetic mixtures of three factors at five levels were used to calibrate and validate the multivariate models. Advanced chemometrics succeeded in quantitative and qualitative analyses of CFQ along with its hydrolytic, oxidative and photo-degradation products. The proposed methods were applied successfully for different pharmaceutical formulations analyses. These developed methods were simple and cost-effective compared with the manufacturer's RP-HPLC method. Copyright © 2015 Elsevier B.V. All rights reserved.

Analysis of characteristics of Si in blast furnace pig iron and calibration methods in the detection by laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Mei, Yaguang; Cheng, Yuxin; Cheng, Shusen; Hao, Zhongqi; Guo, Lianbo; Li, Xiangyou; Zeng, Xiaoyan

2017-10-01

During the iron-making process in blast furnace, the Si content in liquid pig iron was usually used to evaluate the quality of liquid iron and thermal state of blast furnace. None effective method was found for rapid detecting the Si concentration of liquid iron. Laser-induced breakdown spectroscopy (LIBS) is a kind of atomic emission spectrometry technology based on laser ablation. Its obvious advantage is realizing rapid, in-situ, online analysis of element concentration in open air without sample pretreatment. The characteristics of Si in liquid iron were analyzed from the aspect of thermodynamic theory and metallurgical technology. The relationship between Si and C, Mn, S, P or other alloy elements were revealed based on thermodynamic calculation. Subsequently, LIBS was applied on rapid detection of Si of pig iron in this work. During LIBS detection process, several groups of standard pig iron samples were employed in this work to calibrate the Si content in pig iron. The calibration methods including linear, quadratic and cubic internal standard calibration, multivariate linear calibration and partial least squares (PLS) were compared with each other. It revealed that the PLS improved by normalization was the best calibration method for Si detection by LIBS.

Comparison of univariate and multivariate calibration for the determination of micronutrients in pellets of plant materials by laser induced breakdown spectrometry

NASA Astrophysics Data System (ADS)

Braga, Jez Willian Batista; Trevizan, Lilian Cristina; Nunes, Lidiane Cristina; Rufini, Iolanda Aparecida; Santos, Dário, Jr.; Krug, Francisco José

2010-01-01

The application of laser induced breakdown spectrometry (LIBS) aiming the direct analysis of plant materials is a great challenge that still needs efforts for its development and validation. In this way, a series of experimental approaches has been carried out in order to show that LIBS can be used as an alternative method to wet acid digestions based methods for analysis of agricultural and environmental samples. The large amount of information provided by LIBS spectra for these complex samples increases the difficulties for selecting the most appropriated wavelengths for each analyte. Some applications have suggested that improvements in both accuracy and precision can be achieved by the application of multivariate calibration in LIBS data when compared to the univariate regression developed with line emission intensities. In the present work, the performance of univariate and multivariate calibration, based on partial least squares regression (PLSR), was compared for analysis of pellets of plant materials made from an appropriate mixture of cryogenically ground samples with cellulose as the binding agent. The development of a specific PLSR model for each analyte and the selection of spectral regions containing only lines of the analyte of interest were the best conditions for the analysis. In this particular application, these models showed a similar performance, but PLSR seemed to be more robust due to a lower occurrence of outliers in comparison to the univariate method. Data suggests that efforts dealing with sample presentation and fitness of standards for LIBS analysis must be done in order to fulfill the boundary conditions for matrix independent development and validation.

Method for predicting dry mechanical properties from wet wood and standing trees

DOEpatents

Meglen, Robert R.; Kelley, Stephen S.

2003-08-12

A method for determining the dry mechanical strength for a green wood comprising: illuminating a surface of the wood to be determined with light between 350-2,500 nm, the wood having a green moisture content; analyzing the surface using a spectrometric method, the method generating a first spectral data, and using a multivariate analysis to predict the dry mechanical strength of green wood when dry by comparing the first spectral data with a calibration model, the calibration model comprising a second spectrometric method of spectral data obtained from a reference wood having a green moisture content, the second spectral data correlated with a known mechanical strength analytical result obtained from a reference wood when dried and having a dry moisture content.

Domain-Invariant Partial-Least-Squares Regression.

PubMed

Nikzad-Langerodi, Ramin; Zellinger, Werner; Lughofer, Edwin; Saminger-Platz, Susanne

2018-05-11

Multivariate calibration models often fail to extrapolate beyond the calibration samples because of changes associated with the instrumental response, environmental condition, or sample matrix. Most of the current methods used to adapt a source calibration model to a target domain exclusively apply to calibration transfer between similar analytical devices, while generic methods for calibration-model adaptation are largely missing. To fill this gap, we here introduce domain-invariant partial-least-squares (di-PLS) regression, which extends ordinary PLS by a domain regularizer in order to align the source and target distributions in the latent-variable space. We show that a domain-invariant weight vector can be derived in closed form, which allows the integration of (partially) labeled data from the source and target domains as well as entirely unlabeled data from the latter. We test our approach on a simulated data set where the aim is to desensitize a source calibration model to an unknown interfering agent in the target domain (i.e., unsupervised model adaptation). In addition, we demonstrate unsupervised, semisupervised, and supervised model adaptation by di-PLS on two real-world near-infrared (NIR) spectroscopic data sets.

Comparative study between univariate spectrophotometry and multivariate calibration as analytical tools for quantitation of Benazepril alone and in combination with Amlodipine.

PubMed

Farouk, M; Elaziz, Omar Abd; Tawakkol, Shereen M; Hemdan, A; Shehata, Mostafa A

2014-04-05

Four simple, accurate, reproducible, and selective methods have been developed and subsequently validated for the determination of Benazepril (BENZ) alone and in combination with Amlodipine (AML) in pharmaceutical dosage form. The first method is pH induced difference spectrophotometry, where BENZ can be measured in presence of AML as it showed maximum absorption at 237nm and 241nm in 0.1N HCl and 0.1N NaOH, respectively, while AML has no wavelength shift in both solvents. The second method is the new Extended Ratio Subtraction Method (EXRSM) coupled to Ratio Subtraction Method (RSM) for determination of both drugs in commercial dosage form. The third and fourth methods are multivariate calibration which include Principal Component Regression (PCR) and Partial Least Squares (PLSs). A detailed validation of the methods was performed following the ICH guidelines and the standard curves were found to be linear in the range of 2-30μg/mL for BENZ in difference and extended ratio subtraction spectrophotometric method, and 5-30 for AML in EXRSM method, with well accepted mean correlation coefficient for each analyte. The intra-day and inter-day precision and accuracy results were well within the acceptable limits. Copyright © 2013 Elsevier B.V. All rights reserved.

On using summary statistics from an external calibration sample to correct for covariate measurement error.

PubMed

Guo, Ying; Little, Roderick J; McConnell, Daniel S

2012-01-01

Covariate measurement error is common in epidemiologic studies. Current methods for correcting measurement error with information from external calibration samples are insufficient to provide valid adjusted inferences. We consider the problem of estimating the regression of an outcome Y on covariates X and Z, where Y and Z are observed, X is unobserved, but a variable W that measures X with error is observed. Information about measurement error is provided in an external calibration sample where data on X and W (but not Y and Z) are recorded. We describe a method that uses summary statistics from the calibration sample to create multiple imputations of the missing values of X in the regression sample, so that the regression coefficients of Y on X and Z and associated standard errors can be estimated using simple multiple imputation combining rules, yielding valid statistical inferences under the assumption of a multivariate normal distribution. The proposed method is shown by simulation to provide better inferences than existing methods, namely the naive method, classical calibration, and regression calibration, particularly for correction for bias and achieving nominal confidence levels. We also illustrate our method with an example using linear regression to examine the relation between serum reproductive hormone concentrations and bone mineral density loss in midlife women in the Michigan Bone Health and Metabolism Study. Existing methods fail to adjust appropriately for bias due to measurement error in the regression setting, particularly when measurement error is substantial. The proposed method corrects this deficiency.

A stepwise, multi-objective, multi-variable parameter optimization method for the APEX model

USDA-ARS?s Scientific Manuscript database

Proper parameterization enables hydrological models to make reliable estimates of non-point source pollution for effective control measures. The automatic calibration of hydrologic models requires significant computational power limiting its application. The study objective was to develop and eval...

Determination of main fruits in adulterated nectars by ATR-FTIR spectroscopy combined with multivariate calibration and variable selection methods.

PubMed

Miaw, Carolina Sheng Whei; Assis, Camila; Silva, Alessandro Rangel Carolino Sales; Cunha, Maria Luísa; Sena, Marcelo Martins; de Souza, Scheilla Vitorino Carvalho

2018-07-15

Grape, orange, peach and passion fruit nectars were formulated and adulterated by dilution with syrup, apple and cashew juices at 10 levels for each adulterant. Attenuated total reflectance Fourier transform mid infrared (ATR-FTIR) spectra were obtained. Partial least squares (PLS) multivariate calibration models allied to different variable selection methods, such as interval partial least squares (iPLS), ordered predictors selection (OPS) and genetic algorithm (GA), were used to quantify the main fruits. PLS improved by iPLS-OPS variable selection showed the highest predictive capacity to quantify the main fruit contents. The selected variables in the final models varied from 72 to 100; the root mean square errors of prediction were estimated from 0.5 to 2.6%; the correlation coefficients of prediction ranged from 0.948 to 0.990; and, the mean relative errors of prediction varied from 3.0 to 6.7%. All of the developed models were validated. Copyright © 2018 Elsevier Ltd. All rights reserved.

Use of partial least squares regression for the multivariate calibration of hazardous air pollutants in open-path FT-IR spectrometry

NASA Astrophysics Data System (ADS)

Hart, Brian K.; Griffiths, Peter R.

1998-06-01

Partial least squares (PLS) regression has been evaluated as a robust calibration technique for over 100 hazardous air pollutants (HAPs) measured by open path Fourier transform infrared (OP/FT-IR) spectrometry. PLS has the advantage over the current recommended calibration method of classical least squares (CLS), in that it can look at the whole useable spectrum (700-1300 cm-1, 2000-2150 cm-1, and 2400-3000 cm-1), and detect several analytes simultaneously. Up to one hundred HAPs synthetically added to OP/FT-IR backgrounds have been simultaneously calibrated and detected using PLS. PLS also has the advantage in requiring less preprocessing of spectra than that which is required in CLS calibration schemes, allowing PLS to provide user independent real-time analysis of OP/FT-IR spectra.

Determination of boiling point of petrochemicals by gas chromatography-mass spectrometry and multivariate regression analysis of structural activity relationship.

PubMed

Fakayode, Sayo O; Mitchell, Breanna S; Pollard, David A

2014-08-01

Accurate understanding of analyte boiling points (BP) is of critical importance in gas chromatographic (GC) separation and crude oil refinery operation in petrochemical industries. This study reported the first combined use of GC separation and partial-least-square (PLS1) multivariate regression analysis of petrochemical structural activity relationship (SAR) for accurate BP determination of two commercially available (D3710 and MA VHP) calibration gas mix samples. The results of the BP determination using PLS1 multivariate regression were further compared with the results of traditional simulated distillation method of BP determination. The developed PLS1 regression was able to correctly predict analytes BP in D3710 and MA VHP calibration gas mix samples, with a root-mean-square-%-relative-error (RMS%RE) of 6.4%, and 10.8% respectively. In contrast, the overall RMS%RE of 32.9% and 40.4%, respectively obtained for BP determination in D3710 and MA VHP using a traditional simulated distillation method were approximately four times larger than the corresponding RMS%RE of BP prediction using MRA, demonstrating the better predictive ability of MRA. The reported method is rapid, robust, and promising, and can be potentially used routinely for fast analysis, pattern recognition, and analyte BP determination in petrochemical industries. Copyright © 2014 Elsevier B.V. All rights reserved.

Evaluation of a stepwise, multi-objective, multi-variable parameter optimization method for the APEX model

USDA-ARS?s Scientific Manuscript database

Hydrologic models are essential tools for environmental assessment of agricultural non-point source pollution. The automatic calibration of hydrologic models, though efficient, demands significant computational power, which can limit its application. The study objective was to investigate a cost e...

Measurement of non-sugar solids content in Chinese rice wine using near infrared spectroscopy combined with an efficient characteristic variables selection algorithm.

PubMed

Ouyang, Qin; Zhao, Jiewen; Chen, Quansheng

2015-01-01

The non-sugar solids (NSS) content is one of the most important nutrition indicators of Chinese rice wine. This study proposed a rapid method for the measurement of NSS content in Chinese rice wine using near infrared (NIR) spectroscopy. We also systemically studied the efficient spectral variables selection algorithms that have to go through modeling. A new algorithm of synergy interval partial least square with competitive adaptive reweighted sampling (Si-CARS-PLS) was proposed for modeling. The performance of the final model was back-evaluated using root mean square error of calibration (RMSEC) and correlation coefficient (Rc) in calibration set and similarly tested by mean square error of prediction (RMSEP) and correlation coefficient (Rp) in prediction set. The optimum model by Si-CARS-PLS algorithm was achieved when 7 PLS factors and 18 variables were included, and the results were as follows: Rc=0.95 and RMSEC=1.12 in the calibration set, Rp=0.95 and RMSEP=1.22 in the prediction set. In addition, Si-CARS-PLS algorithm showed its superiority when compared with the commonly used algorithms in multivariate calibration. This work demonstrated that NIR spectroscopy technique combined with a suitable multivariate calibration algorithm has a high potential in rapid measurement of NSS content in Chinese rice wine. Copyright © 2015 Elsevier B.V. All rights reserved.

Study on rapid valid acidity evaluation of apple by fiber optic diffuse reflectance technique

NASA Astrophysics Data System (ADS)

Liu, Yande; Ying, Yibin; Fu, Xiaping; Jiang, Xuesong

2004-03-01

Some issues related to nondestructive evaluation of valid acidity in intact apples by means of Fourier transform near infrared (FTNIR) (800-2631nm) method were addressed. A relationship was established between the diffuse reflectance spectra recorded with a bifurcated optic fiber and the valid acidity. The data were analyzed by multivariate calibration analysis such as partial least squares (PLS) analysis and principal component regression (PCR) technique. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influence of data preprocessing and different spectra treatments were also investigated. Models based on smoothing spectra were slightly worse than models based on derivative spectra and the best result was obtained when the segment length was 5 and the gap size was 10. Depending on data preprocessing and multivariate calibration technique, the best prediction model had a correlation efficient (0.871), a low RMSEP (0.0677), a low RMSEC (0.056) and a small difference between RMSEP and RMSEC by PLS analysis. The results point out the feasibility of FTNIR spectral analysis to predict the fruit valid acidity non-destructively. The ratio of data standard deviation to the root mean square error of prediction (SDR) is better to be less than 3 in calibration models, however, the results cannot meet the demand of actual application. Therefore, further study is required for better calibration and prediction.

Spectral multivariate calibration without laboratory prepared or determined reference analyte values.

PubMed

Ottaway, Josh; Farrell, Jeremy A; Kalivas, John H

2013-02-05

An essential part to calibration is establishing the analyte calibration reference samples. These samples must characterize the sample matrix and measurement conditions (chemical, physical, instrumental, and environmental) of any sample to be predicted. Calibration usually requires measuring spectra for numerous reference samples in addition to determining the corresponding analyte reference values. Both tasks are typically time-consuming and costly. This paper reports on a method named pure component Tikhonov regularization (PCTR) that does not require laboratory prepared or determined reference values. Instead, an analyte pure component spectrum is used in conjunction with nonanalyte spectra for calibration. Nonanalyte spectra can be from different sources including pure component interference samples, blanks, and constant analyte samples. The approach is also applicable to calibration maintenance when the analyte pure component spectrum is measured in one set of conditions and nonanalyte spectra are measured in new conditions. The PCTR method balances the trade-offs between calibration model shrinkage and the degree of orthogonality to the nonanalyte content (model direction) in order to obtain accurate predictions. Using visible and near-infrared (NIR) spectral data sets, the PCTR results are comparable to those obtained using ridge regression (RR) with reference calibration sets. The flexibility of PCTR also allows including reference samples if such samples are available.

Chemiluminescence-based multivariate sensing of local equivalence ratios in premixed atmospheric methane-air flames

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tripathi, Markandey M.; Krishnan, Sundar R.; Srinivasan, Kalyan K.

Chemiluminescence emissions from OH*, CH*, C2, and CO2 formed within the reaction zone of premixed flames depend upon the fuel-air equivalence ratio in the burning mixture. In the present paper, a new partial least square regression (PLS-R) based multivariate sensing methodology is investigated and compared with an OH*/CH* intensity ratio-based calibration model for sensing equivalence ratio in atmospheric methane-air premixed flames. Five replications of spectral data at nine different equivalence ratios ranging from 0.73 to 1.48 were used in the calibration of both models. During model development, the PLS-R model was initially validated with the calibration data set using themore » leave-one-out cross validation technique. Since the PLS-R model used the entire raw spectral intensities, it did not need the nonlinear background subtraction of CO2 emission that is required for typical OH*/CH* intensity ratio calibrations. An unbiased spectral data set (not used in the PLS-R model development), for 28 different equivalence ratio conditions ranging from 0.71 to 1.67, was used to predict equivalence ratios using the PLS-R and the intensity ratio calibration models. It was found that the equivalence ratios predicted with the PLS-R based multivariate calibration model matched the experimentally measured equivalence ratios within 7%; whereas, the OH*/CH* intensity ratio calibration grossly underpredicted equivalence ratios in comparison to measured equivalence ratios, especially under rich conditions ( > 1.2). The practical implications of the chemiluminescence-based multivariate equivalence ratio sensing methodology are also discussed.« less

Uncertainty Analysis of Instrument Calibration and Application

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Experimental aerodynamic researchers require estimated precision and bias uncertainties of measured physical quantities, typically at 95 percent confidence levels. Uncertainties of final computed aerodynamic parameters are obtained by propagation of individual measurement uncertainties through the defining functional expressions. In this paper, rigorous mathematical techniques are extended to determine precision and bias uncertainties of any instrument-sensor system. Through this analysis, instrument uncertainties determined through calibration are now expressed as functions of the corresponding measurement for linear and nonlinear univariate and multivariate processes. Treatment of correlated measurement precision error is developed. During laboratory calibration, calibration standard uncertainties are assumed to be an order of magnitude less than those of the instrument being calibrated. Often calibration standards do not satisfy this assumption. This paper applies rigorous statistical methods for inclusion of calibration standard uncertainty and covariance due to the order of their application. The effects of mathematical modeling error on calibration bias uncertainty are quantified. The effects of experimental design on uncertainty are analyzed. The importance of replication is emphasized, techniques for estimation of both bias and precision uncertainties using replication are developed. Statistical tests for stationarity of calibration parameters over time are obtained.

Method of predicting mechanical properties of decayed wood

DOEpatents

Kelley, Stephen S.

2003-07-15

A method for determining the mechanical properties of decayed wood that has been exposed to wood decay microorganisms, comprising: a) illuminating a surface of decayed wood that has been exposed to wood decay microorganisms with wavelengths from visible and near infrared (VIS-NIR) spectra; b) analyzing the surface of the decayed wood using a spectrometric method, the method generating a first spectral data of wavelengths in VIS-NIR spectra region; and c) using a multivariate analysis to predict mechanical properties of decayed wood by comparing the first spectral data with a calibration model, the calibration model comprising a second spectrometric method of spectral data of wavelengths in VIS-NIR spectra obtained from a reference decay wood, the second spectral data being correlated with a known mechanical property analytical result obtained from the reference decayed wood.

Variety identification of brown sugar using short-wave near infrared spectroscopy and multivariate calibration

NASA Astrophysics Data System (ADS)

Yang, Haiqing; Wu, Di; He, Yong

2007-11-01

Near-infrared spectroscopy (NIRS) with the characteristics of high speed, non-destructiveness, high precision and reliable detection data, etc. is a pollution-free, rapid, quantitative and qualitative analysis method. A new approach for variety discrimination of brown sugars using short-wave NIR spectroscopy (800-1050nm) was developed in this work. The relationship between the absorbance spectra and brown sugar varieties was established. The spectral data were compressed by the principal component analysis (PCA). The resulting features can be visualized in principal component (PC) space, which can lead to discovery of structures correlative with the different class of spectral samples. It appears to provide a reasonable variety clustering of brown sugars. The 2-D PCs plot obtained using the first two PCs can be used for the pattern recognition. Least-squares support vector machines (LS-SVM) was applied to solve the multivariate calibration problems in a relatively fast way. The work has shown that short-wave NIR spectroscopy technique is available for the brand identification of brown sugar, and LS-SVM has the better identification ability than PLS when the calibration set is small.

Multivariate postprocessing techniques for probabilistic hydrological forecasting

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Lisniak, Dmytro; Klein, Bastian

2016-04-01

Hydrologic ensemble forecasts driven by atmospheric ensemble prediction systems need statistical postprocessing in order to account for systematic errors in terms of both mean and spread. Runoff is an inherently multivariate process with typical events lasting from hours in case of floods to weeks or even months in case of droughts. This calls for multivariate postprocessing techniques that yield well calibrated forecasts in univariate terms and ensure a realistic temporal dependence structure at the same time. To this end, the univariate ensemble model output statistics (EMOS; Gneiting et al., 2005) postprocessing method is combined with two different copula approaches that ensure multivariate calibration throughout the entire forecast horizon. These approaches comprise ensemble copula coupling (ECC; Schefzik et al., 2013), which preserves the dependence structure of the raw ensemble, and a Gaussian copula approach (GCA; Pinson and Girard, 2012), which estimates the temporal correlations from training observations. Both methods are tested in a case study covering three subcatchments of the river Rhine that represent different sizes and hydrological regimes: the Upper Rhine up to the gauge Maxau, the river Moselle up to the gauge Trier, and the river Lahn up to the gauge Kalkofen. The results indicate that both ECC and GCA are suitable for modelling the temporal dependences of probabilistic hydrologic forecasts (Hemri et al., 2015). References Gneiting, T., A. E. Raftery, A. H. Westveld, and T. Goldman (2005), Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation, Monthly Weather Review, 133(5), 1098-1118, DOI: 10.1175/MWR2904.1. Hemri, S., D. Lisniak, and B. Klein, Multivariate postprocessing techniques for probabilistic hydrological forecasting, Water Resources Research, 51(9), 7436-7451, DOI: 10.1002/2014WR016473. Pinson, P., and R. Girard (2012), Evaluating the quality of scenarios of short-term wind power generation, Applied Energy, 96, 12-20, DOI: 10.1016/j.apenergy.2011.11.004. Schefzik, R., T. L. Thorarinsdottir, and T. Gneiting (2013), Uncertainty quantification in complex simulation models using ensemble copula coupling, Statistical Science, 28, 616-640, DOI: 10.1214/13-STS443.

Comparison of Portable and Bench-Top Spectrometers for Mid-Infrared Diffuse Reflectance Measurements of Soils.

PubMed

Hutengs, Christopher; Ludwig, Bernard; Jung, András; Eisele, Andreas; Vohland, Michael

2018-03-27

Mid-infrared (MIR) spectroscopy has received widespread interest as a method to complement traditional soil analysis. Recently available portable MIR spectrometers additionally offer potential for on-site applications, given sufficient spectral data quality. We therefore tested the performance of the Agilent 4300 Handheld FTIR (DRIFT spectra) in comparison to a Bruker Tensor 27 bench-top instrument in terms of (i) spectral quality and measurement noise quantified by wavelet analysis; (ii) accuracy of partial least squares (PLS) calibrations for soil organic carbon (SOC), total nitrogen (N), pH, clay and sand content with a repeated cross-validation analysis; and (iii) key spectral regions for these soil properties identified with a Monte Carlo spectral variable selection approach. Measurements and multivariate calibrations with the handheld device were as good as or slightly better than Bruker equipped with a DRIFT accessory, but not as accurate as with directional hemispherical reflectance (DHR) data collected with an integrating sphere. Variations in noise did not markedly affect the accuracy of multivariate PLS calibrations. Identified key spectral regions for PLS calibrations provided a good match between Agilent and Bruker DHR data, especially for SOC and N. Our findings suggest that portable FTIR instruments are a viable alternative for MIR measurements in the laboratory and offer great potential for on-site applications.

A novel second-order standard addition analytical method based on data processing with multidimensional partial least-squares and residual bilinearization.

PubMed

Lozano, Valeria A; Ibañez, Gabriela A; Olivieri, Alejandro C

2009-10-05

In the presence of analyte-background interactions and a significant background signal, both second-order multivariate calibration and standard addition are required for successful analyte quantitation achieving the second-order advantage. This report discusses a modified second-order standard addition method, in which the test data matrix is subtracted from the standard addition matrices, and quantitation proceeds via the classical external calibration procedure. It is shown that this novel data processing method allows one to apply not only parallel factor analysis (PARAFAC) and multivariate curve resolution-alternating least-squares (MCR-ALS), but also the recently introduced and more flexible partial least-squares (PLS) models coupled to residual bilinearization (RBL). In particular, the multidimensional variant N-PLS/RBL is shown to produce the best analytical results. The comparison is carried out with the aid of a set of simulated data, as well as two experimental data sets: one aimed at the determination of salicylate in human serum in the presence of naproxen as an additional interferent, and the second one devoted to the analysis of danofloxacin in human serum in the presence of salicylate.

Discordance between net analyte signal theory and practical multivariate calibration.

PubMed

Brown, Christopher D

2004-08-01

Lorber's concept of net analyte signal is reviewed in the context of classical and inverse least-squares approaches to multivariate calibration. It is shown that, in the presence of device measurement error, the classical and inverse calibration procedures have radically different theoretical prediction objectives, and the assertion that the popular inverse least-squares procedures (including partial least squares, principal components regression) approximate Lorber's net analyte signal vector in the limit is disproved. Exact theoretical expressions for the prediction error bias, variance, and mean-squared error are given under general measurement error conditions, which reinforce the very discrepant behavior between these two predictive approaches, and Lorber's net analyte signal theory. Implications for multivariate figures of merit and numerous recently proposed preprocessing treatments involving orthogonal projections are also discussed.

Calibration transfer of a Raman spectroscopic quantification method for the assessment of liquid detergent compositions between two at-line instruments installed at two liquid detergent production plants.

PubMed

Brouckaert, D; Uyttersprot, J-S; Broeckx, W; De Beer, T

2017-09-01

Calibration transfer of partial least squares (PLS) quantification models is established between two Raman spectrometers located at two liquid detergent production plants. As full recalibration of existing calibration models is time-consuming, labour-intensive and costly, it is investigated whether the use of mathematical correction methods requiring only a handful of standardization samples can overcome the dissimilarities in spectral response observed between both measurement systems. Univariate and multivariate standardization approaches are investigated, ranging from simple slope/bias correction (SBC), local centring (LC) and single wavelength standardization (SWS) to more complex direct standardization (DS) and piecewise direct standardization (PDS). The results of these five calibration transfer methods are compared reciprocally, as well as with regard to a full recalibration. Four PLS quantification models, each predicting the concentration of one of the four main ingredients in the studied liquid detergent composition, are aimed at transferring. Accuracy profiles are established from the original and transferred quantification models for validation purposes. A reliable representation of the calibration models performance before and after transfer is thus established, based on β-expectation tolerance intervals. For each transferred model, it is investigated whether every future measurement that will be performed in routine will be close enough to the unknown true value of the sample. From this validation, it is concluded that instrument standardization is successful for three out of four investigated calibration models using multivariate (DS and PDS) transfer approaches. The fourth transferred PLS model could not be validated over the investigated concentration range, due to a lack of precision of the slave instrument. Comparing these transfer results to a full recalibration on the slave instrument allows comparison of the predictive power of both Raman systems and leads to the formulation of guidelines for further standardization projects. It is concluded that it is essential to evaluate the performance of the slave instrument prior to transfer, even when it is theoretically identical to the master apparatus. Copyright © 2017 Elsevier B.V. All rights reserved.

Calibration sets and the accuracy of vibrational scaling factors: A case study with the X3LYP hybrid functional

NASA Astrophysics Data System (ADS)

Teixeira, Filipe; Melo, André; Cordeiro, M. Natália D. S.

2010-09-01

A linear least-squares methodology was used to determine the vibrational scaling factors for the X3LYP density functional. Uncertainties for these scaling factors were calculated according to the method devised by Irikura et al. [J. Phys. Chem. A 109, 8430 (2005)]. The calibration set was systematically partitioned according to several of its descriptors and the scaling factors for X3LYP were recalculated for each subset. The results show that the scaling factors are only significant up to the second digit, irrespective of the calibration set used. Furthermore, multivariate statistical analysis allowed us to conclude that the scaling factors and the associated uncertainties are independent of the size of the calibration set and strongly suggest the practical impossibility of obtaining vibrational scaling factors with more than two significant digits.

Calibration sets and the accuracy of vibrational scaling factors: a case study with the X3LYP hybrid functional.

PubMed

Teixeira, Filipe; Melo, André; Cordeiro, M Natália D S

2010-09-21

A linear least-squares methodology was used to determine the vibrational scaling factors for the X3LYP density functional. Uncertainties for these scaling factors were calculated according to the method devised by Irikura et al. [J. Phys. Chem. A 109, 8430 (2005)]. The calibration set was systematically partitioned according to several of its descriptors and the scaling factors for X3LYP were recalculated for each subset. The results show that the scaling factors are only significant up to the second digit, irrespective of the calibration set used. Furthermore, multivariate statistical analysis allowed us to conclude that the scaling factors and the associated uncertainties are independent of the size of the calibration set and strongly suggest the practical impossibility of obtaining vibrational scaling factors with more than two significant digits.

Elemental analysis of soils using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and laser-induced breakdown spectroscopy (LIBS) with multivariate discrimination: tape mounting as an alternative to pellets for small forensic transfer specimens.

PubMed

Jantzi, Sarah C; Almirall, José R

2014-01-01

Elemental analysis of soil is a useful application of both laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and laser-induced breakdown spectroscopy (LIBS) in geological, agricultural, environmental, archeological, planetary, and forensic sciences. In forensic science, the question to be answered is often whether soil specimens found on objects (e.g., shoes, tires, or tools) originated from the crime scene or other location of interest. Elemental analysis of the soil from the object and the locations of interest results in a characteristic elemental profile of each specimen, consisting of the amount of each element present. Because multiple elements are measured, multivariate statistics can be used to compare the elemental profiles in order to determine whether the specimen from the object is similar to one of the locations of interest. Previous work involved milling and pressing 0.5 g of soil into pellets before analysis using LA-ICP-MS and LIBS. However, forensic examiners prefer techniques that require smaller samples, are less time consuming, and are less destructive, allowing for future analysis by other techniques. An alternative sample introduction method was developed to meet these needs while still providing quantitative results suitable for multivariate comparisons. The tape-mounting method involved deposition of a thin layer of soil onto double-sided adhesive tape. A comparison of tape-mounting and pellet method performance is reported for both LA-ICP-MS and LIBS. Calibration standards and reference materials, prepared using the tape method, were analyzed by LA-ICP-MS and LIBS. As with the pellet method, linear calibration curves were achieved with the tape method, as well as good precision and low bias. Soil specimens from Miami-Dade County were prepared by both the pellet and tape methods and analyzed by LA-ICP-MS and LIBS. Principal components analysis and linear discriminant analysis were applied to the multivariate data. Results from both the tape method and the pellet method were nearly identical, with clear groupings and correct classification rates of >94%.

Improved accuracy in quantitative laser-induced breakdown spectroscopy using sub-models

USGS Publications Warehouse

Anderson, Ryan; Clegg, Samuel M.; Frydenvang, Jens; Wiens, Roger C.; McLennan, Scott M.; Morris, Richard V.; Ehlmann, Bethany L.; Dyar, M. Darby

2017-01-01

Accurate quantitative analysis of diverse geologic materials is one of the primary challenges faced by the Laser-Induced Breakdown Spectroscopy (LIBS)-based ChemCam instrument on the Mars Science Laboratory (MSL) rover. The SuperCam instrument on the Mars 2020 rover, as well as other LIBS instruments developed for geochemical analysis on Earth or other planets, will face the same challenge. Consequently, part of the ChemCam science team has focused on the development of improved multivariate analysis calibrations methods. Developing a single regression model capable of accurately determining the composition of very different target materials is difficult because the response of an element’s emission lines in LIBS spectra can vary with the concentration of other elements. We demonstrate a conceptually simple “sub-model” method for improving the accuracy of quantitative LIBS analysis of diverse target materials. The method is based on training several regression models on sets of targets with limited composition ranges and then “blending” these “sub-models” into a single final result. Tests of the sub-model method show improvement in test set root mean squared error of prediction (RMSEP) for almost all cases. The sub-model method, using partial least squares regression (PLS), is being used as part of the current ChemCam quantitative calibration, but the sub-model method is applicable to any multivariate regression method and may yield similar improvements.

Multicomponent kinetic spectrophotometric determination of pefloxacin and norfloxacin in pharmaceutical preparations and human plasma samples with the aid of chemometrics

NASA Astrophysics Data System (ADS)

Ni, Yongnian; Wang, Yong; Kokot, Serge

2008-10-01

A spectrophotometric method for the simultaneous determination of the important pharmaceuticals, pefloxacin and its structurally similar metabolite, norfloxacin, is described for the first time. The analysis is based on the monitoring of a kinetic spectrophotometric reaction of the two analytes with potassium permanganate as the oxidant. The measurement of the reaction process followed the absorbance decrease of potassium permanganate at 526 nm, and the accompanying increase of the product, potassium manganate, at 608 nm. It was essential to use multivariate calibrations to overcome severe spectral overlaps and similarities in reaction kinetics. Calibration curves for the individual analytes showed linear relationships over the concentration ranges of 1.0-11.5 mg L -1 at 526 and 608 nm for pefloxacin, and 0.15-1.8 mg L -1 at 526 and 608 nm for norfloxacin. Various multivariate calibration models were applied, at the two analytical wavelengths, for the simultaneous prediction of the two analytes including classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), radial basis function-artificial neural network (RBF-ANN) and principal component-radial basis function-artificial neural network (PC-RBF-ANN). PLS and PC-RBF-ANN calibrations with the data collected at 526 nm, were the preferred methods—%RPE T ˜ 5, and LODs for pefloxacin and norfloxacin of 0.36 and 0.06 mg L -1, respectively. Then, the proposed method was applied successfully for the simultaneous determination of pefloxacin and norfloxacin present in pharmaceutical and human plasma samples. The results compared well with those from the alternative analysis by HPLC.

Quantitative analysis of essential oils in perfume using multivariate curve resolution combined with comprehensive two-dimensional gas chromatography.

PubMed

de Godoy, Luiz Antonio Fonseca; Hantao, Leandro Wang; Pedroso, Marcio Pozzobon; Poppi, Ronei Jesus; Augusto, Fabio

2011-08-05

The use of multivariate curve resolution (MCR) to build multivariate quantitative models using data obtained from comprehensive two-dimensional gas chromatography with flame ionization detection (GC×GC-FID) is presented and evaluated. The MCR algorithm presents some important features, such as second order advantage and the recovery of the instrumental response for each pure component after optimization by an alternating least squares (ALS) procedure. A model to quantify the essential oil of rosemary was built using a calibration set containing only known concentrations of the essential oil and cereal alcohol as solvent. A calibration curve correlating the concentration of the essential oil of rosemary and the instrumental response obtained from the MCR-ALS algorithm was obtained, and this calibration model was applied to predict the concentration of the oil in complex samples (mixtures of the essential oil, pineapple essence and commercial perfume). The values of the root mean square error of prediction (RMSEP) and of the root mean square error of the percentage deviation (RMSPD) obtained were 0.4% (v/v) and 7.2%, respectively. Additionally, a second model was built and used to evaluate the accuracy of the method. A model to quantify the essential oil of lemon grass was built and its concentration was predicted in the validation set and real perfume samples. The RMSEP and RMSPD obtained were 0.5% (v/v) and 6.9%, respectively, and the concentration of the essential oil of lemon grass in perfume agreed to the value informed by the manufacturer. The result indicates that the MCR algorithm is adequate to resolve the target chromatogram from the complex sample and to build multivariate models of GC×GC-FID data. Copyright © 2011 Elsevier B.V. All rights reserved.

Simultaneous chemometric determination of pyridoxine hydrochloride and isoniazid in tablets by multivariate regression methods.

PubMed

Dinç, Erdal; Ustündağ, Ozgür; Baleanu, Dumitru

2010-08-01

The sole use of pyridoxine hydrochloride during treatment of tuberculosis gives rise to pyridoxine deficiency. Therefore, a combination of pyridoxine hydrochloride and isoniazid is used in pharmaceutical dosage form in tuberculosis treatment to reduce this side effect. In this study, two chemometric methods, partial least squares (PLS) and principal component regression (PCR), were applied to the simultaneous determination of pyridoxine (PYR) and isoniazid (ISO) in their tablets. A concentration training set comprising binary mixtures of PYR and ISO consisting of 20 different combinations were randomly prepared in 0.1 M HCl. Both multivariate calibration models were constructed using the relationships between the concentration data set (concentration data matrix) and absorbance data matrix in the spectral region 200-330 nm. The accuracy and the precision of the proposed chemometric methods were validated by analyzing synthetic mixtures containing the investigated drugs. The recovery results obtained by applying PCR and PLS calibrations to the artificial mixtures were found between 100.0 and 100.7%. Satisfactory results obtained by applying the PLS and PCR methods to both artificial and commercial samples were obtained. The results obtained in this manuscript strongly encourage us to use them for the quality control and the routine analysis of the marketing tablets containing PYR and ISO drugs. Copyright © 2010 John Wiley & Sons, Ltd.

Novel hyperspectral prediction method and apparatus

NASA Astrophysics Data System (ADS)

Kemeny, Gabor J.; Crothers, Natalie A.; Groth, Gard A.; Speck, Kathy A.; Marbach, Ralf

2009-05-01

Both the power and the challenge of hyperspectral technologies is the very large amount of data produced by spectral cameras. While off-line methodologies allow the collection of gigabytes of data, extended data analysis sessions are required to convert the data into useful information. In contrast, real-time monitoring, such as on-line process control, requires that compression of spectral data and analysis occur at a sustained full camera data rate. Efficient, high-speed practical methods for calibration and prediction are therefore sought to optimize the value of hyperspectral imaging. A novel method of matched filtering known as science based multivariate calibration (SBC) was developed for hyperspectral calibration. Classical (MLR) and inverse (PLS, PCR) methods are combined by spectroscopically measuring the spectral "signal" and by statistically estimating the spectral "noise." The accuracy of the inverse model is thus combined with the easy interpretability of the classical model. The SBC method is optimized for hyperspectral data in the Hyper-CalTM software used for the present work. The prediction algorithms can then be downloaded into a dedicated FPGA based High-Speed Prediction EngineTM module. Spectral pretreatments and calibration coefficients are stored on interchangeable SD memory cards, and predicted compositions are produced on a USB interface at real-time camera output rates. Applications include minerals, pharmaceuticals, food processing and remote sensing.

Measuring coronary calcium on CT images adjusted for attenuation differences.

PubMed

Nelson, Jennifer Clark; Kronmal, Richard A; Carr, J Jeffrey; McNitt-Gray, Michael F; Wong, Nathan D; Loria, Catherine M; Goldin, Jonathan G; Williams, O Dale; Detrano, Robert

2005-05-01

To quantify scanner and participant variability in attenuation values for computed tomographic (CT) images assessed for coronary calcium and define a method for standardizing attenuation values and calibrating calcium measurements. Institutional review board approval and participant informed consent were obtained at all study sites. An image attenuation adjustment method involving the use of available calibration phantom data to define standard attenuation values was developed. The method was applied to images from two population-based multicenter studies: the Coronary Artery Risk Development in Young Adults study (3041 participants) and the Multi-Ethnic Study of Atherosclerosis (6814 participants). To quantify the variability in attenuation, analysis of variance techniques were used to compare the CT numbers of standardized torso phantom regions across study sites, and multivariate linear regression models of participant-specific calibration phantom attenuation values that included participant age, race, sex, body mass index (BMI), smoking status, and site as covariates were developed. To assess the effect of the calibration method on calcium measurements, Pearson correlation coefficients between unadjusted and attenuation-adjusted calcium measurements were computed. Multivariate models were used to examine the effect of sex, race, BMI, smoking status, unadjusted score, and site on Agatston score adjustments. Mean attenuation values (CT numbers) of a standard calibration phantom scanned beneath participants varied significantly according to scanner and participant BMI (P < .001 for both). Values were lowest for Siemens multi-detector row CT scanners (110.0 HU), followed by GE-Imatron electron-beam (116.0 HU) and GE LightSpeed multi-detector row scanners (121.5 HU). Values were also lower for morbidly obese (BMI, > or =40.0 kg/m(2)) participants (108.9 HU), followed by obese (BMI, 30.0-39.9 kg/m(2)) (114.8 HU), overweight (BMI, 25.0-29.9 kg/m(2)) (118.5 HU), and normal-weight or underweight (BMI, <25.0 kg/m(2)) (120.1 HU) participants. Agatston score calibration adjustments ranged from -650 to 1071 (mean, -8 +/- 50 [standard deviation]) and increased with Agatston score (P < .001). The direction and magnitude of adjustment varied significantly according to scanner and BMI (P < .001 for both) and were consistent with phantom attenuation results in that calibration resulted in score decreases for images with higher phantom attenuation values. Image attenuation values vary by scanner and participant body size, producing calcium score differences that are not due to true calcium burden disparities. Use of calibration phantoms to adjust attenuation values and calibrate calcium measurements in research studies and clinical practice may improve the comparability of such measurements between persons scanned with different scanners and within persons over time.

A GPU-Based Implementation of the Firefly Algorithm for Variable Selection in Multivariate Calibration Problems

PubMed Central

de Paula, Lauro C. M.; Soares, Anderson S.; de Lima, Telma W.; Delbem, Alexandre C. B.; Coelho, Clarimar J.; Filho, Arlindo R. G.

2014-01-01

Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation. PMID:25493625

A GPU-Based Implementation of the Firefly Algorithm for Variable Selection in Multivariate Calibration Problems.

PubMed

de Paula, Lauro C M; Soares, Anderson S; de Lima, Telma W; Delbem, Alexandre C B; Coelho, Clarimar J; Filho, Arlindo R G

2014-01-01

Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation.

Improved Quantitative Analysis of Ion Mobility Spectrometry by Chemometric Multivariate Calibration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fraga, Carlos G.; Kerr, Dayle; Atkinson, David A.

2009-09-01

Traditional peak-area calibration and the multivariate calibration methods of principle component regression (PCR) and partial least squares (PLS), including unfolded PLS (U-PLS) and multi-way PLS (N-PLS), were evaluated for the quantification of 2,4,6-trinitrotoluene (TNT) and cyclo-1,3,5-trimethylene-2,4,6-trinitramine (RDX) in Composition B samples analyzed by temperature step desorption ion mobility spectrometry (TSD-IMS). The true TNT and RDX concentrations of eight Composition B samples were determined by high performance liquid chromatography with UV absorbance detection. Most of the Composition B samples were found to have distinct TNT and RDX concentrations. Applying PCR and PLS on the exact same IMS spectra used for themore » peak-area study improved quantitative accuracy and precision approximately 3 to 5 fold and 2 to 4 fold, respectively. This in turn improved the probability of correctly identifying Composition B samples based upon the estimated RDX and TNT concentrations from 11% with peak area to 44% and 89% with PLS. This improvement increases the potential of obtaining forensic information from IMS analyzers by providing some ability to differentiate or match Composition B samples based on their TNT and RDX concentrations.« less

Simultaneous quantitative analysis of olmesartan, amlodipine and hydrochlorothiazide in their combined dosage form utilizing classical and alternating least squares based chemometric methods.

PubMed

Darwish, Hany W; Bakheit, Ahmed H; Abdelhameed, Ali S

2016-03-01

Simultaneous spectrophotometric analysis of a multi-component dosage form of olmesartan, amlodipine and hydrochlorothiazide used for the treatment of hypertension has been carried out using various chemometric methods. Multivariate calibration methods include classical least squares (CLS) executed by net analyte processing (NAP-CLS), orthogonal signal correction (OSC-CLS) and direct orthogonal signal correction (DOSC-CLS) in addition to multivariate curve resolution-alternating least squares (MCR-ALS). Results demonstrated the efficiency of the proposed methods as quantitative tools of analysis as well as their qualitative capability. The three analytes were determined precisely using the aforementioned methods in an external data set and in a dosage form after optimization of experimental conditions. Finally, the efficiency of the models was validated via comparison with the partial least squares (PLS) method in terms of accuracy and precision.

Linear model correction: A method for transferring a near-infrared multivariate calibration model without standard samples.

PubMed

Liu, Yan; Cai, Wensheng; Shao, Xueguang

2016-12-05

Calibration transfer is essential for practical applications of near infrared (NIR) spectroscopy because the measurements of the spectra may be performed on different instruments and the difference between the instruments must be corrected. For most of calibration transfer methods, standard samples are necessary to construct the transfer model using the spectra of the samples measured on two instruments, named as master and slave instrument, respectively. In this work, a method named as linear model correction (LMC) is proposed for calibration transfer without standard samples. The method is based on the fact that, for the samples with similar physical and chemical properties, the spectra measured on different instruments are linearly correlated. The fact makes the coefficients of the linear models constructed by the spectra measured on different instruments are similar in profile. Therefore, by using the constrained optimization method, the coefficients of the master model can be transferred into that of the slave model with a few spectra measured on slave instrument. Two NIR datasets of corn and plant leaf samples measured with different instruments are used to test the performance of the method. The results show that, for both the datasets, the spectra can be correctly predicted using the transferred partial least squares (PLS) models. Because standard samples are not necessary in the method, it may be more useful in practical uses. Copyright © 2016 Elsevier B.V. All rights reserved.

Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy.

PubMed

Liu, Yan-De; Ying, Yi-Bin; Fu, Xia-Ping

2005-03-01

To develop nondestructive acidity prediction for intact Fuji apples, the potential of Fourier transform near infrared (FT-NIR) method with fiber optics in interactance mode was investigated. Interactance in the 800 nm to 2619 nm region was measured for intact apples, harvested from early to late maturity stages. Spectral data were analyzed by two multivariate calibration techniques including partial least squares (PLS) and principal component regression (PCR) methods. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influences of different data preprocessing and spectra treatments were also quantified. Calibration models based on smoothing spectra were slightly worse than that based on derivative spectra, and the best result was obtained when the segment length was 5 nm and the gap size was 10 points. Depending on data preprocessing and PLS method, the best prediction model yielded correlation coefficient of determination (r2) of 0.759, low root mean square error of prediction (RMSEP) of 0.0677, low root mean square error of calibration (RMSEC) of 0.0562. The results indicated the feasibility of FT-NIR spectral analysis for predicting apple valid acidity in a nondestructive way.

Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy*

PubMed Central

Liu, Yan-de; Ying, Yi-bin; Fu, Xia-ping

2005-01-01

To develop nondestructive acidity prediction for intact Fuji apples, the potential of Fourier transform near infrared (FT-NIR) method with fiber optics in interactance mode was investigated. Interactance in the 800 nm to 2619 nm region was measured for intact apples, harvested from early to late maturity stages. Spectral data were analyzed by two multivariate calibration techniques including partial least squares (PLS) and principal component regression (PCR) methods. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influences of different data preprocessing and spectra treatments were also quantified. Calibration models based on smoothing spectra were slightly worse than that based on derivative spectra, and the best result was obtained when the segment length was 5 nm and the gap size was 10 points. Depending on data preprocessing and PLS method, the best prediction model yielded correlation coefficient of determination (r 2) of 0.759, low root mean square error of prediction (RMSEP) of 0.0677, low root mean square error of calibration (RMSEC) of 0.0562. The results indicated the feasibility of FT-NIR spectral analysis for predicting apple valid acidity in a nondestructive way. PMID:15682498

Laser ablation molecular isotopic spectroscopy (LAMIS) towards the determination of multivariate LODs via PLS calibration model of 10B and 11B Boric acid mixtures

NASA Astrophysics Data System (ADS)

Harris, C. D.; Profeta, Luisa T. M.; Akpovo, Codjo A.; Johnson, Lewis; Stowe, Ashley C.

2017-05-01

A calibration model was created to illustrate the detection capabilities of laser ablation molecular isotopic spectroscopy (LAMIS) discrimination in isotopic analysis. The sample set contained boric acid pellets that varied in isotopic concentrations of 10B and 11B. Each sample set was interrogated with a Q-switched Nd:YAG ablation laser operating at 532 nm. A minimum of four band heads of the β system B2∑ -> Χ2∑transitions were identified and verified with previous literature on BO molecular emission lines. Isotopic shifts were observed in the spectra for each transition and used as the predictors in the calibration model. The spectra along with their respective 10/11B isotopic ratios were analyzed using Partial Least Squares Regression (PLSR). An IUPAC novel approach for determining a multivariate Limit of Detection (LOD) interval was used to predict the detection of the desired isotopic ratios. The predicted multivariate LOD is dependent on the variation of the instrumental signal and other composites in the calibration model space.

A Comparison of Multivariate and Pre-Processing Methods for Quantitative Laser-Induced Breakdown Spectroscopy of Geologic Samples

NASA Technical Reports Server (NTRS)

Anderson, R. B.; Morris, R. V.; Clegg, S. M.; Bell, J. F., III; Humphries, S. D.; Wiens, R. C.

2011-01-01

The ChemCam instrument selected for the Curiosity rover is capable of remote laser-induced breakdown spectroscopy (LIBS).[1] We used a remote LIBS instrument similar to ChemCam to analyze 197 geologic slab samples and 32 pressed-powder geostandards. The slab samples are well-characterized and have been used to validate the calibration of previous instruments on Mars missions, including CRISM [2], OMEGA [3], the MER Pancam [4], Mini-TES [5], and Moessbauer [6] instruments and the Phoenix SSI [7]. The resulting dataset was used to compare multivariate methods for quantitative LIBS and to determine the effect of grain size on calculations. Three multivariate methods - partial least squares (PLS), multilayer perceptron artificial neural networks (MLP ANNs) and cascade correlation (CC) ANNs - were used to generate models and extract the quantitative composition of unknown samples. PLS can be used to predict one element (PLS1) or multiple elements (PLS2) at a time, as can the neural network methods. Although MLP and CC ANNs were successful in some cases, PLS generally produced the most accurate and precise results.

Determination of glucose in a biological matrix by multivariate analysis of multiple band-pass-filtered Fourier transform near-infrared interferograms.

PubMed

Mattu, M J; Small, G W; Arnold, M A

1997-11-15

A multivariate calibration method is described in which Fourier transform near-infrared interferogram data are used to determine clinically relevant levels of glucose in an aqueous matrix of bovine serum albumin (BSA) and triacetin. BSA and triacetin are used to model the protein and triglycerides in blood, respectively, and are present in levels spanning the normal human physiological range. A full factorial experimental design is constructed for the data collection, with glucose at 10 levels, BSA at 4 levels, and triacetin at 4 levels. Gaussian-shaped band-pass digital filters are applied to the interferogram data to extract frequencies associated with an absorption band of interest. Separate filters of various widths are positioned on the glucose band at 4400 cm-1, the BSA band at 4606 cm-1, and the triacetin band at 4446 cm-1. Each filter is applied to the raw interferogram, producing one, two, or three filtered interferograms, depending on the number of filters used. Segments of these filtered interferograms are used together in a partial least-squares regression analysis to build glucose calibration models. The optimal calibration model is realized by use of separate segments of interferograms filtered with three filters centered on the glucose, BSA, and triacetin bands. Over the physiological range of 1-20 mM glucose, this 17-term model exhibits values of R2, standard error of calibration, and standard error of prediction of 98.85%, 0.631 mM, and 0.677 mM, respectively. These results are comparable to those obtained in a conventional analysis of spectral data. The interferogram-based method operates without the use of a separate background measurement and employs only a short section of the interferogram.

Improved accuracy in quantitative laser-induced breakdown spectroscopy using sub-models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, Ryan B.; Clegg, Samuel M.; Frydenvang, Jens

We report that accurate quantitative analysis of diverse geologic materials is one of the primary challenges faced by the Laser-Induced Breakdown Spectroscopy (LIBS)-based ChemCam instrument on the Mars Science Laboratory (MSL) rover. The SuperCam instrument on the Mars 2020 rover, as well as other LIBS instruments developed for geochemical analysis on Earth or other planets, will face the same challenge. Consequently, part of the ChemCam science team has focused on the development of improved multivariate analysis calibrations methods. Developing a single regression model capable of accurately determining the composition of very different target materials is difficult because the response ofmore » an element’s emission lines in LIBS spectra can vary with the concentration of other elements. We demonstrate a conceptually simple “submodel” method for improving the accuracy of quantitative LIBS analysis of diverse target materials. The method is based on training several regression models on sets of targets with limited composition ranges and then “blending” these “sub-models” into a single final result. Tests of the sub-model method show improvement in test set root mean squared error of prediction (RMSEP) for almost all cases. Lastly, the sub-model method, using partial least squares regression (PLS), is being used as part of the current ChemCam quantitative calibration, but the sub-model method is applicable to any multivariate regression method and may yield similar improvements.« less

Improved accuracy in quantitative laser-induced breakdown spectroscopy using sub-models

DOE PAGES

Anderson, Ryan B.; Clegg, Samuel M.; Frydenvang, Jens; ...

2016-12-15

We report that accurate quantitative analysis of diverse geologic materials is one of the primary challenges faced by the Laser-Induced Breakdown Spectroscopy (LIBS)-based ChemCam instrument on the Mars Science Laboratory (MSL) rover. The SuperCam instrument on the Mars 2020 rover, as well as other LIBS instruments developed for geochemical analysis on Earth or other planets, will face the same challenge. Consequently, part of the ChemCam science team has focused on the development of improved multivariate analysis calibrations methods. Developing a single regression model capable of accurately determining the composition of very different target materials is difficult because the response ofmore » an element’s emission lines in LIBS spectra can vary with the concentration of other elements. We demonstrate a conceptually simple “submodel” method for improving the accuracy of quantitative LIBS analysis of diverse target materials. The method is based on training several regression models on sets of targets with limited composition ranges and then “blending” these “sub-models” into a single final result. Tests of the sub-model method show improvement in test set root mean squared error of prediction (RMSEP) for almost all cases. Lastly, the sub-model method, using partial least squares regression (PLS), is being used as part of the current ChemCam quantitative calibration, but the sub-model method is applicable to any multivariate regression method and may yield similar improvements.« less

A Review of Calibration Transfer Practices and Instrument Differences in Spectroscopy.

PubMed

Workman, Jerome J

2018-03-01

Calibration transfer for use with spectroscopic instruments, particularly for near-infrared, infrared, and Raman analysis, has been the subject of multiple articles, research papers, book chapters, and technical reviews. There has been a myriad of approaches published and claims made for resolving the problems associated with transferring calibrations; however, the capability of attaining identical results over time from two or more instruments using an identical calibration still eludes technologists. Calibration transfer, in a precise definition, refers to a series of analytical approaches or chemometric techniques used to attempt to apply a single spectral database, and the calibration model developed using that database, for two or more instruments, with statistically retained accuracy and precision. Ideally, one would develop a single calibration for any particular application, and move it indiscriminately across instruments and achieve identical analysis or prediction results. There are many technical aspects involved in such precision calibration transfer, related to the measuring instrument reproducibility and repeatability, the reference chemical values used for the calibration, the multivariate mathematics used for calibration, and sample presentation repeatability and reproducibility. Ideally, a multivariate model developed on a single instrument would provide a statistically identical analysis when used on other instruments following transfer. This paper reviews common calibration transfer techniques, mostly related to instrument differences, and the mathematics of the uncertainty between instruments when making spectroscopic measurements of identical samples. It does not specifically address calibration maintenance or reference laboratory differences.

Calibration transfer of a Raman spectroscopic quantification method for the assessment of liquid detergent compositions from at-line laboratory to in-line industrial scale.

PubMed

Brouckaert, D; Uyttersprot, J-S; Broeckx, W; De Beer, T

2018-03-01

Calibration transfer or standardisation aims at creating a uniform spectral response on different spectroscopic instruments or under varying conditions, without requiring a full recalibration for each situation. In the current study, this strategy is applied to construct at-line multivariate calibration models and consequently employ them in-line in a continuous industrial production line, using the same spectrometer. Firstly, quantitative multivariate models are constructed at-line at laboratory scale for predicting the concentration of two main ingredients in hard surface cleaners. By regressing the Raman spectra of a set of small-scale calibration samples against their reference concentration values, partial least squares (PLS) models are developed to quantify the surfactant levels in the liquid detergent compositions under investigation. After evaluating the models performance with a set of independent validation samples, a univariate slope/bias correction is applied in view of transporting these at-line calibration models to an in-line manufacturing set-up. This standardisation technique allows a fast and easy transfer of the PLS regression models, by simply correcting the model predictions on the in-line set-up, without adjusting anything to the original multivariate calibration models. An extensive statistical analysis is performed in order to assess the predictive quality of the transferred regression models. Before and after transfer, the R 2 and RMSEP of both models is compared for evaluating if their magnitude is similar. T-tests are then performed to investigate whether the slope and intercept of the transferred regression line are not statistically different from 1 and 0, respectively. Furthermore, it is inspected whether no significant bias can be noted. F-tests are executed as well, for assessing the linearity of the transfer regression line and for investigating the statistical coincidence of the transfer and validation regression line. Finally, a paired t-test is performed to compare the original at-line model to the slope/bias corrected in-line model, using interval hypotheses. It is shown that the calibration models of Surfactant 1 and Surfactant 2 yield satisfactory in-line predictions after slope/bias correction. While Surfactant 1 passes seven out of eight statistical tests, the recommended validation parameters are 100% successful for Surfactant 2. It is hence concluded that the proposed strategy for transferring at-line calibration models to an in-line industrial environment via a univariate slope/bias correction of the predicted values offers a successful standardisation approach. Copyright © 2017 Elsevier B.V. All rights reserved.

Quality evaluation of frozen guava and yellow passion fruit pulps by NIR spectroscopy and chemometrics.

PubMed

Alamar, Priscila D; Caramês, Elem T S; Poppi, Ronei J; Pallone, Juliana A L

2016-07-01

The present study investigated the application of near infrared spectroscopy as a green, quick, and efficient alternative to analytical methods currently used to evaluate the quality (moisture, total sugars, acidity, soluble solids, pH and ascorbic acid) of frozen guava and passion fruit pulps. Fifty samples were analyzed by near infrared spectroscopy (NIR) and reference methods. Partial least square regression (PLSR) was used to develop calibration models to relate the NIR spectra and the reference values. Reference methods indicated adulteration by water addition in 58% of guava pulp samples and 44% of yellow passion fruit pulp samples. The PLS models produced lower values of root mean squares error of calibration (RMSEC), root mean squares error of prediction (RMSEP), and coefficient of determination above 0.7. Moisture and total sugars presented the best calibration models (RMSEP of 0.240 and 0.269, respectively, for guava pulp; RMSEP of 0.401 and 0.413, respectively, for passion fruit pulp) which enables the application of these models to determine adulteration in guava and yellow passion fruit pulp by water or sugar addition. The models constructed for calibration of quality parameters of frozen fruit pulps in this study indicate that NIR spectroscopy coupled with the multivariate calibration technique could be applied to determine the quality of guava and yellow passion fruit pulp. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gridded Calibration of Ensemble Wind Vector Forecasts Using Ensemble Model Output Statistics

NASA Astrophysics Data System (ADS)

Lazarus, S. M.; Holman, B. P.; Splitt, M. E.

2017-12-01

A computationally efficient method is developed that performs gridded post processing of ensemble wind vector forecasts. An expansive set of idealized WRF model simulations are generated to provide physically consistent high resolution winds over a coastal domain characterized by an intricate land / water mask. Ensemble model output statistics (EMOS) is used to calibrate the ensemble wind vector forecasts at observation locations. The local EMOS predictive parameters (mean and variance) are then spread throughout the grid utilizing flow-dependent statistical relationships extracted from the downscaled WRF winds. Using data withdrawal and 28 east central Florida stations, the method is applied to one year of 24 h wind forecasts from the Global Ensemble Forecast System (GEFS). Compared to the raw GEFS, the approach improves both the deterministic and probabilistic forecast skill. Analysis of multivariate rank histograms indicate the post processed forecasts are calibrated. Two downscaling case studies are presented, a quiescent easterly flow event and a frontal passage. Strengths and weaknesses of the approach are presented and discussed.

Multivariate estimation of the limit of detection by orthogonal partial least squares in temperature-modulated MOX sensors.

PubMed

Burgués, Javier; Marco, Santiago

2018-08-17

Metal oxide semiconductor (MOX) sensors are usually temperature-modulated and calibrated with multivariate models such as partial least squares (PLS) to increase the inherent low selectivity of this technology. The multivariate sensor response patterns exhibit heteroscedastic and correlated noise, which suggests that maximum likelihood methods should outperform PLS. One contribution of this paper is the comparison between PLS and maximum likelihood principal components regression (MLPCR) in MOX sensors. PLS is often criticized by the lack of interpretability when the model complexity increases beyond the chemical rank of the problem. This happens in MOX sensors due to cross-sensitivities to interferences, such as temperature or humidity and non-linearity. Additionally, the estimation of fundamental figures of merit, such as the limit of detection (LOD), is still not standardized in multivariate models. Orthogonalization methods, such as orthogonal projection to latent structures (O-PLS), have been successfully applied in other fields to reduce the complexity of PLS models. In this work, we propose a LOD estimation method based on applying the well-accepted univariate LOD formulas to the scores of the first component of an orthogonal PLS model. The resulting LOD is compared to the multivariate LOD range derived from error-propagation. The methodology is applied to data extracted from temperature-modulated MOX sensors (FIS SB-500-12 and Figaro TGS 3870-A04), aiming at the detection of low concentrations of carbon monoxide in the presence of uncontrolled humidity (chemical noise). We found that PLS models were simpler and more accurate than MLPCR models. Average LOD values of 0.79 ppm (FIS) and 1.06 ppm (Figaro) were found using the approach described in this paper. These values were contained within the LOD ranges obtained with the error-propagation approach. The mean LOD increased to 1.13 ppm (FIS) and 1.59 ppm (Figaro) when considering validation samples collected two weeks after calibration, which represents a 43% and 46% degradation, respectively. The orthogonal score-plot was a very convenient tool to visualize MOX sensor data and to validate the LOD estimates. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantitative assessment of copper proteinates used as animal feed additives using ATR-FTIR spectroscopy and powder X-ray diffraction (PXRD) analysis.

PubMed

Cantwell, Caoimhe A; Byrne, Laurann A; Connolly, Cathal D; Hynes, Michael J; McArdle, Patrick; Murphy, Richard A

2017-08-01

The aim of the present work was to establish a reliable analytical method to determine the degree of complexation in commercial metal proteinates used as feed additives in the solid state. Two complementary techniques were developed. Firstly, a quantitative attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopic method investigated modifications in vibrational absorption bands of the ligand on complex formation. Secondly, a powder X-ray diffraction (PXRD) method to quantify the amount of crystalline material in the proteinate product was developed. These methods were developed in tandem and cross-validated with each other. Multivariate analysis (MVA) was used to develop validated calibration and prediction models. The FTIR and PXRD calibrations showed excellent linearity (R 2  > 0.99). The diagnostic model parameters showed that the FTIR and PXRD methods were robust with a root mean square error of calibration RMSEC ≤3.39% and a root mean square error of prediction RMSEP ≤7.17% respectively. Comparative statistics show excellent agreement between the MVA packages assessed and between the FTIR and PXRD methods. The methods can be used to determine the degree of complexation in complexes of both protein hydrolysates and pure amino acids.

An efficient surrogate-based simulation-optimization method for calibrating a regional MODFLOW model

NASA Astrophysics Data System (ADS)

Chen, Mingjie; Izady, Azizallah; Abdalla, Osman A.

2017-01-01

Simulation-optimization method entails a large number of model simulations, which is computationally intensive or even prohibitive if the model simulation is extremely time-consuming. Statistical models have been examined as a surrogate of the high-fidelity physical model during simulation-optimization process to tackle this problem. Among them, Multivariate Adaptive Regression Splines (MARS), a non-parametric adaptive regression method, is superior in overcoming problems of high-dimensions and discontinuities of the data. Furthermore, the stability and accuracy of MARS model can be improved by bootstrap aggregating methods, namely, bagging. In this paper, Bagging MARS (BMARS) method is integrated to a surrogate-based simulation-optimization framework to calibrate a three-dimensional MODFLOW model, which is developed to simulate the groundwater flow in an arid hardrock-alluvium region in northwestern Oman. The physical MODFLOW model is surrogated by the statistical model developed using BMARS algorithm. The surrogate model, which is fitted and validated using training dataset generated by the physical model, can approximate solutions rapidly. An efficient Sobol' method is employed to calculate global sensitivities of head outputs to input parameters, which are used to analyze their importance for the model outputs spatiotemporally. Only sensitive parameters are included in the calibration process to further improve the computational efficiency. Normalized root mean square error (NRMSE) between measured and simulated heads at observation wells is used as the objective function to be minimized during optimization. The reasonable history match between the simulated and observed heads demonstrated feasibility of this high-efficient calibration framework.

Determination of rice syrup adulterant concentration in honey using three-dimensional fluorescence spectra and multivariate calibrations

NASA Astrophysics Data System (ADS)

Chen, Quansheng; Qi, Shuai; Li, Huanhuan; Han, Xiaoyan; Ouyang, Qin; Zhao, Jiewen

2014-10-01

To rapidly and efficiently detect the presence of adulterants in honey, three-dimensional fluorescence spectroscopy (3DFS) technique was employed with the help of multivariate calibration. The data of 3D fluorescence spectra were compressed using characteristic extraction and the principal component analysis (PCA). Then, partial least squares (PLS) and back propagation neural network (BP-ANN) algorithms were used for modeling. The model was optimized by cross validation, and its performance was evaluated according to root mean square error of prediction (RMSEP) and correlation coefficient (R) in prediction set. The results showed that BP-ANN model was superior to PLS models, and the optimum prediction results of the mixed group (sunflower ± longan ± buckwheat ± rape) model were achieved as follow: RMSEP = 0.0235 and R = 0.9787 in the prediction set. The study demonstrated that the 3D fluorescence spectroscopy technique combined with multivariate calibration has high potential in rapid, nondestructive, and accurate quantitative analysis of honey adulteration.

An adaptive modeling and simulation environment for combined-cycle data reconciliation and degradation estimation

NASA Astrophysics Data System (ADS)

Lin, Tsungpo

Performance engineers face the major challenge in modeling and simulation for the after-market power system due to system degradation and measurement errors. Currently, the majority in power generation industries utilizes the deterministic data matching method to calibrate the model and cascade system degradation, which causes significant calibration uncertainty and also the risk of providing performance guarantees. In this research work, a maximum-likelihood based simultaneous data reconciliation and model calibration (SDRMC) is used for power system modeling and simulation. By replacing the current deterministic data matching with SDRMC one can reduce the calibration uncertainty and mitigate the error propagation to the performance simulation. A modeling and simulation environment for a complex power system with certain degradation has been developed. In this environment multiple data sets are imported when carrying out simultaneous data reconciliation and model calibration. Calibration uncertainties are estimated through error analyses and populated to performance simulation by using principle of error propagation. System degradation is then quantified by performance comparison between the calibrated model and its expected new & clean status. To mitigate smearing effects caused by gross errors, gross error detection (GED) is carried out in two stages. The first stage is a screening stage, in which serious gross errors are eliminated in advance. The GED techniques used in the screening stage are based on multivariate data analysis (MDA), including multivariate data visualization and principal component analysis (PCA). Subtle gross errors are treated at the second stage, in which the serial bias compensation or robust M-estimator is engaged. To achieve a better efficiency in the combined scheme of the least squares based data reconciliation and the GED technique based on hypotheses testing, the Levenberg-Marquardt (LM) algorithm is utilized as the optimizer. To reduce the computation time and stabilize the problem solving for a complex power system such as a combined cycle power plant, meta-modeling using the response surface equation (RSE) and system/process decomposition are incorporated with the simultaneous scheme of SDRMC. The goal of this research work is to reduce the calibration uncertainties and, thus, the risks of providing performance guarantees arisen from uncertainties in performance simulation.

Quantitative monitoring of sucrose, reducing sugar and total sugar dynamics for phenotyping of water-deficit stress tolerance in rice through spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Das, Bappa; Sahoo, Rabi N.; Pargal, Sourabh; Krishna, Gopal; Verma, Rakesh; Chinnusamy, Viswanathan; Sehgal, Vinay K.; Gupta, Vinod K.; Dash, Sushanta K.; Swain, Padmini

2018-03-01

In the present investigation, the changes in sucrose, reducing and total sugar content due to water-deficit stress in rice leaves were modeled using visible, near infrared (VNIR) and shortwave infrared (SWIR) spectroscopy. The objectives of the study were to identify the best vegetation indices and suitable multivariate technique based on precise analysis of hyperspectral data (350 to 2500 nm) and sucrose, reducing sugar and total sugar content measured at different stress levels from 16 different rice genotypes. Spectral data analysis was done to identify suitable spectral indices and models for sucrose estimation. Novel spectral indices in near infrared (NIR) range viz. ratio spectral index (RSI) and normalised difference spectral indices (NDSI) sensitive to sucrose, reducing sugar and total sugar content were identified which were subsequently calibrated and validated. The RSI and NDSI models had R2 values of 0.65, 0.71 and 0.67; RPD values of 1.68, 1.95 and 1.66 for sucrose, reducing sugar and total sugar, respectively for validation dataset. Different multivariate spectral models such as artificial neural network (ANN), multivariate adaptive regression splines (MARS), multiple linear regression (MLR), partial least square regression (PLSR), random forest regression (RFR) and support vector machine regression (SVMR) were also evaluated. The best performing multivariate models for sucrose, reducing sugars and total sugars were found to be, MARS, ANN and MARS, respectively with respect to RPD values of 2.08, 2.44, and 1.93. Results indicated that VNIR and SWIR spectroscopy combined with multivariate calibration can be used as a reliable alternative to conventional methods for measurement of sucrose, reducing sugars and total sugars of rice under water-deficit stress as this technique is fast, economic, and noninvasive.

Multivariate analysis of organic acids in fermented food from reversed-phase high-performance liquid chromatography data.

PubMed

Mortera, Pablo; Zuljan, Federico A; Magni, Christian; Bortolato, Santiago A; Alarcón, Sergio H

2018-02-01

Multivariate calibration coupled to RP-HPLC with diode array detection (HPLC-DAD) was applied to the identification and the quantitative evaluation of the short chain organic acids (malic, oxalic, formic, lactic, acetic, citric, pyruvic, succinic, tartaric, propionic and α-cetoglutaric) in fermented food. The goal of the present study was to get the successful resolution of a system in the combined occurrence of strongly coeluting peaks, of distortions in the time sensors among chromatograms, and of the presence of unexpected compounds not included in the calibration step. Second-order HPLC-DAD data matrices were obtained in a short time (10min) on a C18 column with a chromatographic system operating in isocratic mode (mobile phase was 20mmolL -1 phosphate buffer at pH 2.20) and a flow-rate of 1.0mLmin -1 at room temperature. Parallel factor analysis (PARAFAC) and unfolded partial least-squares combined with residual bilinearization (U-PLS/RBL) were the second-order calibration algorithms select for data processing. The performance of the analytical parameters was good with an outstanding limit of detection (LODs) for acids ranging from 0.15 to 10.0mmolL -1 in the validation samples. The improved method was applied to the analysis of many dairy products (yoghurt, cultured milk and cheese) and wine. The method was shown as an effective means for determining and following acid contents in fermented food and was characterized by reducibility with simple, high resolution and rapid procedure without derivatization of analytes. Copyright © 2017 Elsevier B.V. All rights reserved.

Fiber-optic evanescent-wave spectroscopy for fast multicomponent analysis of human blood

NASA Astrophysics Data System (ADS)

Simhi, Ronit; Gotshal, Yaron; Bunimovich, David; Katzir, Abraham; Sela, Ben-Ami

1996-07-01

A spectral analysis of human blood serum was undertaken by fiber-optic evanescent-wave spectroscopy (FEWS) by the use of a Fourier-transform infrared spectrometer. A special cell for the FEWS measurements was designed and built that incorporates an IR-transmitting silver halide fiber and a means for introducing the blood-serum sample. Further improvements in analysis were obtained by the adoption of multivariate calibration techniques that are already used in clinical chemistry. The partial least-squares algorithm was used to calculate the concentrations of cholesterol, total protein, urea, and uric acid in human blood serum. The estimated prediction errors obtained (in percent from the average value) were 6% for total protein, 15% for cholesterol, 30% for urea, and 30% for uric acid. These results were compared with another independent prediction method that used a neural-network model. This model yielded estimated prediction errors of 8.8% for total protein, 25% for cholesterol, and 21% for uric acid. spectroscopy, fiber-optic evanescent-wave spectroscopy, Fourier-transform infrared spectrometer, blood, multivariate calibration, neural networks.

Multivariate curve resolution-assisted determination of pseudoephedrine and methamphetamine by HPLC-DAD in water samples.

PubMed

Vosough, Maryam; Mohamedian, Hadi; Salemi, Amir; Baheri, Tahmineh

2015-02-01

In the present study, a simple strategy based on solid-phase extraction (SPE) with a cation exchange sorbent (Finisterre SCX) followed by fast high-performance liquid chromatography (HPLC) with diode array detection coupled with chemometrics tools has been proposed for the determination of methamphetamine and pseudoephedrine in ground water and river water. At first, the HPLC and SPE conditions were optimized and the analytical performance of the method was determined. In the case of ground water, determination of analytes was successfully performed through univariate calibration curves. For river water sample, multivariate curve resolution and alternating least squares was implemented and the second-order advantage was achieved in samples containing uncalibrated interferences and uncorrected background signals. The calibration curves showed good linearity (r(2) > 0.994).The limits of detection for pseudoephedrine and methamphetamine were 0.06 and 0.08 μg/L and the average recovery values were 104.7 and 102.3% in river water, respectively. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Gamma/Hadron Separation for the HAWC Observatory

NASA Astrophysics Data System (ADS)

Gerhardt, Michael J.

The High-Altitude Water Cherenkov (HAWC) Observatory is a gamma-ray observatory sensitive to gamma rays from 100 GeV to 100 TeV with an instantaneous field of view of ˜2 sr. It is located on the Sierra Negra plateau in Mexico at an elevation of 4,100 m and began full operation in March 2015. The purpose of the detector is to study relativistic particles that are produced by interstellar and intergalactic objects such as: pulsars, supernova remnants, molecular clouds, black holes and more. To achieve optimal angular resolution, energy reconstruction and cosmic ray background suppression for the extensive air showers detected by HAWC, good timing and charge calibration are crucial, as well as optimization of quality cuts on background suppression variables. Additions to the HAWC timing calibration, in particular automating the calibration quality checks and a new method for background suppression using a multivariate analysis are presented in this thesis.

Use of a region of the visible and near infrared spectrum to predict mechanical properties of wet wood and standing trees

DOEpatents

Meglen, Robert R.; Kelley, Stephen S.

2003-01-01

In a method for determining the dry mechanical strength for a green wood, the improvement comprising: (a) illuminating a surface of the wood to be determined with a reduced range of wavelengths in the VIS-NIR spectra 400 to 1150 nm, said wood having a green moisture content; (b) analyzing the surface of the wood using a spectrometric method, the method generating a first spectral data of a reduced range of wavelengths in VIS-NIR spectra; and (c) using a multivariate analysis technique to predict the mechanical strength of green wood when dry by comparing the first spectral data with a calibration model, the calibration model comprising a second spectrometric method of spectral data of a reduced range of wavelengths in VIS-NIR spectra obtained from a reference wood having a green moisture content, the second spectral being correlated with a known mechanical strength analytical result obtained from the reference wood when dried and a having a dry moisture content.

Rapid quantification of multi-components in alcohol precipitation liquid of Codonopsis Radix using near infrared spectroscopy (NIRS).

PubMed

Luo, Yu; Li, Wen-Long; Huang, Wen-Hua; Liu, Xue-Hua; Song, Yan-Gang; Qu, Hai-Bin

2017-05-01

A near infrared spectroscopy (NIRS) approach was established for quality control of the alcohol precipitation liquid in the manufacture of Codonopsis Radix. By applying NIRS with multivariate analysis, it was possible to build variation into the calibration sample set, and the Plackett-Burman design, Box-Behnken design, and a concentrating-diluting method were used to obtain the sample set covered with sufficient fluctuation of process parameters and extended concentration information. NIR data were calibrated to predict the four quality indicators using partial least squares regression (PLSR). In the four calibration models, the root mean squares errors of prediction (RMSEPs) were 1.22 μg/ml, 10.5 μg/ml, 1.43 μg/ml, and 0.433% for lobetyolin, total flavonoids, pigments, and total solid contents, respectively. The results indicated that multi-components quantification of the alcohol precipitation liquid of Codonopsis Radix could be achieved with an NIRS-based method, which offers a useful tool for real-time release testing (RTRT) of intermediates in the manufacture of Codonopsis Radix.

Reliable noninvasive measurement of blood gases

DOEpatents

Thomas, Edward V.; Robinson, Mark R.; Haaland, David M.; Alam, Mary K.

1994-01-01

Methods and apparatus for, preferably, determining noninvasively and in vivo at least two of the five blood gas parameters (i.e., pH, PCO.sub.2, [HCO.sub.3.sup.- ], PO.sub.2, and O.sub.2 sat.) in a human. The non-invasive method includes the steps of: generating light at three or more different wavelengths in the range of 500 nm to 2500 nm; irradiating blood containing tissue; measuring the intensities of the wavelengths emerging from the blood containing tissue to obtain a set of at least three spectral intensities v. wavelengths; and determining the unknown values of at least two of pH, [HCO.sub.3.sup.- ], PCO.sub.2 and a measure of oxygen concentration. The determined values are within the physiological ranges observed in blood containing tissue. The method also includes the steps of providing calibration samples, determining if the spectral intensities v. wavelengths from the tissue represents an outlier, and determining if any of the calibration samples represents an outlier. The determination of the unknown values is performed by at least one multivariate algorithm using two or more variables and at least one calibration model. Preferably, there is a separate calibration for each blood gas parameter being determined. The method can be utilized in a pulse mode and can also be used invasively. The apparatus includes a tissue positioning device, a source, at least one detector, electronics, a microprocessor, memory, and apparatus for indicating the determined values.

Accuracy enhancement of a multivariate calibration for lead determination in soils by laser induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Zaytsev, Sergey M.; Krylov, Ivan N.; Popov, Andrey M.; Zorov, Nikita B.; Labutin, Timur A.

2018-02-01

We have investigated matrix effects and spectral interferences on example of lead determination in different types of soils by laser induced breakdown spectroscopy (LIBS). Comparison between analytical performances of univariate and multivariate calibrations with the use of different laser wavelength for ablation (532, 355 and 266 nm) have been reported. A set of 17 soil samples (Ca-rich, Fe-rich, lean soils etc., 8.5-280 ppm of Pb) was involved into construction of the calibration models. Spectral interferences from main components (Ca, Fe, Ti, Mg) and trace components (Mn, Nb, Zr) were estimated by spectra modeling, and they were a reason for significant differences between the univariate calibration models obtained for a three different soil types (black, red, gray) separately. Implementation of 3rd harmonic of Nd:YAG laser in combination with multivariate calibration model based on PCR with 3 principal components provided the best analytical results: the RMSEC has been lowered down to 8 ppm. The sufficient improvement of the relative uncertainty (up to 5-10%) in comparison with univariate calibration was observed at the Pb concentration level > 50 ppm, while the problem of accuracy still remains for some samples with Pb concentration at the 20 ppm level. We have also discussed a few possible ways to estimate LOD without a blank sample. The most rigorous criterion has resulted in LOD of Pb in soils being 13 ppm. Finally, a good agreement between the values of lead content predicted by LIBS (46 ± 5 ppm) and XRF (42.1 ± 3.3 ppm) in the unknown soil sample from Lomonosov Moscow State University area was demonstrated.

Updating a synchronous fluorescence spectroscopic virgin olive oil adulteration calibration to a new geographical region.

PubMed

Kunz, Matthew Ross; Ottaway, Joshua; Kalivas, John H; Georgiou, Constantinos A; Mousdis, George A

2011-02-23

Detecting and quantifying extra virgin olive adulteration is of great importance to the olive oil industry. Many spectroscopic methods in conjunction with multivariate analysis have been used to solve these issues. However, successes to date are limited as calibration models are built to a specific set of geographical regions, growing seasons, cultivars, and oil extraction methods (the composite primary condition). Samples from new geographical regions, growing seasons, etc. (secondary conditions) are not always correctly predicted by the primary model due to different olive oil and/or adulterant compositions stemming from secondary conditions not matching the primary conditions. Three Tikhonov regularization (TR) variants are used in this paper to allow adulterant (sunflower oil) concentration predictions in samples from geographical regions not part of the original primary calibration domain. Of the three TR variants, ridge regression with an additional 2-norm penalty provides the smallest validation sample prediction errors. Although the paper reports on using TR for model updating to predict adulterant oil concentration, the methods should also be applicable to updating models distinguishing adulterated samples from pure extra virgin olive oil. Additionally, the approaches are general and can be used with other spectroscopic methods and adulterants as well as with other agriculture products.

Determination of propranolol hydrochloride in pharmaceutical preparations using near infrared spectrometry with fiber optic probe and multivariate calibration methods.

PubMed

Marques Junior, Jucelino Medeiros; Muller, Aline Lima Hermes; Foletto, Edson Luiz; da Costa, Adilson Ben; Bizzi, Cezar Augusto; Irineu Muller, Edson

2015-01-01

A method for determination of propranolol hydrochloride in pharmaceutical preparation using near infrared spectrometry with fiber optic probe (FTNIR/PROBE) and combined with chemometric methods was developed. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). The treatments based on the mean centered data and multiplicative scatter correction (MSC) were selected for models construction. A root mean square error of prediction (RMSEP) of 8.2 mg g(-1) was achieved using siPLS (s2i20PLS) algorithm with spectra divided into 20 intervals and combination of 2 intervals (8501 to 8801 and 5201 to 5501 cm(-1)). Results obtained by the proposed method were compared with those using the pharmacopoeia reference method and significant difference was not observed. Therefore, proposed method allowed a fast, precise, and accurate determination of propranolol hydrochloride in pharmaceutical preparations. Furthermore, it is possible to carry out on-line analysis of this active principle in pharmaceutical formulations with use of fiber optic probe.

Spectrophotometric determination of ternary mixtures of thiamin, riboflavin and pyridoxal in pharmaceutical and human plasma by least-squares support vector machines.

PubMed

Niazi, Ali; Zolgharnein, Javad; Afiuni-Zadeh, Somaie

2007-11-01

Ternary mixtures of thiamin, riboflavin and pyridoxal have been simultaneously determined in synthetic and real samples by applications of spectrophotometric and least-squares support vector machines. The calibration graphs were linear in the ranges of 1.0 - 20.0, 1.0 - 10.0 and 1.0 - 20.0 microg ml(-1) with detection limits of 0.6, 0.5 and 0.7 microg ml(-1) for thiamin, riboflavin and pyridoxal, respectively. The experimental calibration matrix was designed with 21 mixtures of these chemicals. The concentrations were varied between calibration graph concentrations of vitamins. The simultaneous determination of these vitamin mixtures by using spectrophotometric methods is a difficult problem, due to spectral interferences. The partial least squares (PLS) modeling and least-squares support vector machines were used for the multivariate calibration of the spectrophotometric data. An excellent model was built using LS-SVM, with low prediction errors and superior performance in relation to PLS. The root mean square errors of prediction (RMSEP) for thiamin, riboflavin and pyridoxal with PLS and LS-SVM were 0.6926, 0.3755, 0.4322 and 0.0421, 0.0318, 0.0457, respectively. The proposed method was satisfactorily applied to the rapid simultaneous determination of thiamin, riboflavin and pyridoxal in commercial pharmaceutical preparations and human plasma samples.

Multivariate analysis of remote LIBS spectra using partial least squares, principal component analysis, and related techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clegg, Samuel M; Barefield, James E; Wiens, Roger C

2008-01-01

Quantitative analysis with LIBS traditionally employs calibration curves that are complicated by the chemical matrix effects. These chemical matrix effects influence the LIBS plasma and the ratio of elemental composition to elemental emission line intensity. Consequently, LIBS calibration typically requires a priori knowledge of the unknown, in order for a series of calibration standards similar to the unknown to be employed. In this paper, three new Multivariate Analysis (MV A) techniques are employed to analyze the LIBS spectra of 18 disparate igneous and highly-metamorphosed rock samples. Partial Least Squares (PLS) analysis is used to generate a calibration model from whichmore » unknown samples can be analyzed. Principal Components Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA) are employed to generate a model and predict the rock type of the samples. These MV A techniques appear to exploit the matrix effects associated with the chemistries of these 18 samples.« less

Rapid analysis of pharmaceutical drugs using LIBS coupled with multivariate analysis.

PubMed

Tiwari, P K; Awasthi, S; Kumar, R; Anand, R K; Rai, P K; Rai, A K

2018-02-01

Type 2 diabetes drug tablets containing voglibose having dose strengths of 0.2 and 0.3 mg of various brands have been examined, using laser-induced breakdown spectroscopy (LIBS) technique. The statistical methods such as the principal component analysis (PCA) and the partial least square regression analysis (PLSR) have been employed on LIBS spectral data for classifying and developing the calibration models of drug samples. We have developed the ratio-based calibration model applying PLSR in which relative spectral intensity ratios H/C, H/N and O/N are used. Further, the developed model has been employed to predict the relative concentration of element in unknown drug samples. The experiment has been performed in air and argon atmosphere, respectively, and the obtained results have been compared. The present model provides rapid spectroscopic method for drug analysis with high statistical significance for online control and measurement process in a wide variety of pharmaceutical industrial applications.

Partial Least Squares Calibration Modeling Towards the Multivariate Limit of Detection for Enriched Isotopic Mixtures via Laser Ablation Molecular Isotopic Spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, Candace; Profeta, Luisa; Akpovo, Codjo

The psuedo univariate limit of detection was calculated to compare to the multivariate interval. ompared with results from the psuedounivariate LOD, the multivariate LOD includes other factors (i.e. signal uncertainties) and the reveals the significance in creating models that not only use the analyte’s emission line but also its entire molecular spectra.

Cider fermentation process monitoring by Vis-NIR sensor system and chemometrics.

PubMed

Villar, Alberto; Vadillo, Julen; Santos, Jose I; Gorritxategi, Eneko; Mabe, Jon; Arnaiz, Aitor; Fernández, Luis A

2017-04-15

Optimization of a multivariate calibration process has been undertaken for a Visible-Near Infrared (400-1100nm) sensor system, applied in the monitoring of the fermentation process of the cider produced in the Basque Country (Spain). The main parameters that were monitored included alcoholic proof, l-lactic acid content, glucose+fructose and acetic acid content. The multivariate calibration was carried out using a combination of different variable selection techniques and the most suitable pre-processing strategies were selected based on the spectra characteristics obtained by the sensor system. The variable selection techniques studied in this work include Martens Uncertainty test, interval Partial Least Square Regression (iPLS) and Genetic Algorithm (GA). This procedure arises from the need to improve the calibration models prediction ability for cider monitoring. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of Multivariable Analysis and FTIR-ATR Spectroscopy to the Prediction of Properties in Campeche Honey

PubMed Central

Pat, Lucio; Ali, Bassam; Guerrero, Armando; Córdova, Atl V.; Garduza, José P.

2016-01-01

Attenuated total reflectance-Fourier transform infrared spectrometry and chemometrics model was used for determination of physicochemical properties (pH, redox potential, free acidity, electrical conductivity, moisture, total soluble solids (TSS), ash, and HMF) in honey samples. The reference values of 189 honey samples of different botanical origin were determined using Association Official Analytical Chemists, (AOAC), 1990; Codex Alimentarius, 2001, International Honey Commission, 2002, methods. Multivariate calibration models were built using partial least squares (PLS) for the measurands studied. The developed models were validated using cross-validation and external validation; several statistical parameters were obtained to determine the robustness of the calibration models: (PCs) optimum number of components principal, (SECV) standard error of cross-validation, (R 2 cal) coefficient of determination of cross-validation, (SEP) standard error of validation, and (R 2 val) coefficient of determination for external validation and coefficient of variation (CV). The prediction accuracy for pH, redox potential, electrical conductivity, moisture, TSS, and ash was good, while for free acidity and HMF it was poor. The results demonstrate that attenuated total reflectance-Fourier transform infrared spectrometry is a valuable, rapid, and nondestructive tool for the quantification of physicochemical properties of honey. PMID:28070445

Simultaneous estimation of ramipril, acetylsalicylic acid and atorvastatin calcium by chemometrics assisted UV-spectrophotometric method in capsules.

PubMed

Sankar, A S Kamatchi; Vetrichelvan, Thangarasu; Venkappaya, Devashya

2011-09-01

In the present work, three different spectrophotometric methods for simultaneous estimation of ramipril, aspirin and atorvastatin calcium in raw materials and in formulations are described. Overlapped data was quantitatively resolved by using chemometric methods, viz. inverse least squares (ILS), principal component regression (PCR) and partial least squares (PLS). Calibrations were constructed using the absorption data matrix corresponding to the concentration data matrix. The linearity range was found to be 1-5, 10-50 and 2-10 μg mL-1 for ramipril, aspirin and atorvastatin calcium, respectively. The absorbance matrix was obtained by measuring the zero-order absorbance in the wavelength range between 210 and 320 nm. A training set design of the concentration data corresponding to the ramipril, aspirin and atorvastatin calcium mixtures was organized statistically to maximize the information content from the spectra and to minimize the error of multivariate calibrations. By applying the respective algorithms for PLS 1, PCR and ILS to the measured spectra of the calibration set, a suitable model was obtained. This model was selected on the basis of RMSECV and RMSEP values. The same was applied to the prediction set and capsule formulation. Mean recoveries of the commercial formulation set together with the figures of merit (calibration sensitivity, selectivity, limit of detection, limit of quantification and analytical sensitivity) were estimated. Validity of the proposed approaches was successfully assessed for analyses of drugs in the various prepared physical mixtures and formulations.

Dissolution testing of isoniazid, rifampicin, pyrazinamide and ethambutol tablets using near-infrared spectroscopy (NIRS) and multivariate calibration.

PubMed

de Oliveira Neves, Ana Carolina; Soares, Gustavo Mesquita; de Morais, Stéphanie Cavalcante; da Costa, Fernanda Saadna Lopes; Porto, Dayanne Lopes; de Lima, Kássio Michell Gomes

2012-01-05

This work utilized the near-infrared spectroscopy (NIRS) and multivariate calibration to measure the percentage drug dissolution of four active pharmaceutical ingredients (APIs) (isoniazid, rifampicin, pyrazinamide and ethambutol) in finished pharmaceutical products produced in the Federal University of Rio Grande do Norte (Brazil). The conventional analytical method employed in quality control tests of the dissolution by the pharmaceutical industry is high-performance liquid chromatography (HPLC). The NIRS is a reliable method that offers important advantages for the large-scale production of tablets and for non-destructive analysis. NIR spectra of 38 samples (in triplicate) were measured using a Bomen FT-NIR 160 MB in the range 1100-2500nm. Each spectrum was the average of 50 scans obtained in the diffuse reflectance mode. The dissolution test, which was initially carried out in 900mL of 0.1N hydrochloric acid at 37±0.5°C, was used to determine the percentage a drug that dissolved from each tablet measured at the same time interval (45min) at pH 6.8. The measurement of the four API was performed by HPLC (Shimadzu, Japan) in the gradiente mode. The influence of various spectral pretreatments (Savitzky-Golay smoothing, Multiplicative Scatter Correction (MSC), and Savitzky-Golay derivatives) and multivariate analysis using the partial least squares (PLS) regression algorithm was calculated by the Unscrambler 9.8 (Camo) software. The correlation coefficient (R(2)) for the HPLC determination versus predicted values (NIRS) ranged from 0.88 to 0.98. The root-mean-square error of prediction (RMSEP) obtained from PLS models were 9.99%, 8.63%, 8.57% and 9.97% for isoniazid, rifampicin, ethambutol and pyrazinamide, respectively, indicating that the NIR method is an effective and non-destructive tool for measurement of drug dissolution from tablets. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

Exploration of attenuated total reflectance mid-infrared spectroscopy and multivariate calibration to measure immunoglobulin G in human sera.

PubMed

Hou, Siyuan; Riley, Christopher B; Mitchell, Cynthia A; Shaw, R Anthony; Bryanton, Janet; Bigsby, Kathryn; McClure, J Trenton

2015-09-01

Immunoglobulin G (IgG) is crucial for the protection of the host from invasive pathogens. Due to its importance for human health, tools that enable the monitoring of IgG levels are highly desired. Consequently there is a need for methods to determine the IgG concentration that are simple, rapid, and inexpensive. This work explored the potential of attenuated total reflectance (ATR) infrared spectroscopy as a method to determine IgG concentrations in human serum samples. Venous blood samples were collected from adults and children, and from the umbilical cord of newborns. The serum was harvested and tested using ATR infrared spectroscopy. Partial least squares (PLS) regression provided the basis to develop the new analytical methods. Three PLS calibrations were determined: one for the combined set of the venous and umbilical cord serum samples, the second for only the umbilical cord samples, and the third for only the venous samples. The number of PLS factors was chosen by critical evaluation of Monte Carlo-based cross validation results. The predictive performance for each PLS calibration was evaluated using the Pearson correlation coefficient, scatter plot and Bland-Altman plot, and percent deviations for independent prediction sets. The repeatability was evaluated by standard deviation and relative standard deviation. The results showed that ATR infrared spectroscopy is potentially a simple, quick, and inexpensive method to measure IgG concentrations in human serum samples. The results also showed that it is possible to build a united calibration curve for the umbilical cord and the venous samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Online low-field NMR spectroscopy for process control of an industrial lithiation reaction-automated data analysis.

PubMed

Kern, Simon; Meyer, Klas; Guhl, Svetlana; Gräßer, Patrick; Paul, Andrea; King, Rudibert; Maiwald, Michael

2018-05-01

Monitoring specific chemical properties is the key to chemical process control. Today, mainly optical online methods are applied, which require time- and cost-intensive calibration effort. NMR spectroscopy, with its advantage being a direct comparison method without need for calibration, has a high potential for enabling closed-loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and rough environments for process monitoring and advanced process control strategies. We present a fully automated data analysis approach which is completely based on physically motivated spectral models as first principles information (indirect hard modeling-IHM) and applied it to a given pharmaceutical lithiation reaction in the framework of the European Union's Horizon 2020 project CONSENS. Online low-field NMR (LF NMR) data was analyzed by IHM with low calibration effort, compared to a multivariate PLS-R (partial least squares regression) approach, and both validated using online high-field NMR (HF NMR) spectroscopy. Graphical abstract NMR sensor module for monitoring of the aromatic coupling of 1-fluoro-2-nitrobenzene (FNB) with aniline to 2-nitrodiphenylamine (NDPA) using lithium-bis(trimethylsilyl) amide (Li-HMDS) in continuous operation. Online 43.5 MHz low-field NMR (LF) was compared to 500 MHz high-field NMR spectroscopy (HF) as reference method.

Headspace-programmed temperature vaporization-mass spectrometry for the rapid determination of possible volatile biomarkers of lung cancer in urine.

PubMed

Pérez Antón, Ana; Ramos, Álvaro García; Del Nogal Sánchez, Miguel; Pavón, José Luis Pérez; Cordero, Bernardo Moreno; Pozas, Ángel Pedro Crisolino

2016-07-01

We propose a new method for the rapid determination of five volatile compounds described in the literature as possible biomarkers of lung cancer in urine samples. The method is based on the coupling of a headspace sampler, a programmed temperature vaporizer in solvent-vent injection mode, and a mass spectrometer (HS-PTV-MS). This configuration is known as an electronic nose based on mass spectrometry. Once the method was developed, it was used for the analysis of urine samples from lung cancer patients and healthy individuals. Multivariate calibration models were employed to quantify the biomarker concentrations in the samples. The detection limits ranged between 0.16 and 21 μg/L. For the assignment of the samples to the patient group or the healthy individuals, the Wilcoxon signed-rank test was used, comparing the concentrations obtained with the median of a reference set of healthy individuals. To date, this is the first time that multivariate calibration and non-parametric methods have been combined to classify biological samples from profile signals obtained with an electronic nose. When significant differences in the concentration of one or more biomarkers were found with respect to the reference set, the sample is considered as a positive one and a new analysis was performed using a chromatographic method (HS-PTV-GC/MS) to confirm the result. The main advantage of the proposed HS-PTV-MS methodology is that no prior chromatographic separation and no sample manipulation are required, which allows an increase of the number of samples analyzed per hour and restricts the use of time-consuming techniques to only when necessary. Graphical abstract Schematic diagram of the developed methodology.

Two Analyte Calibration From The Transient Response Of Potentiometric Sensors Employed With The SIA Technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cartas, Raul; Mimendia, Aitor; Valle, Manel del

2009-05-23

Calibration models for multi-analyte electronic tongues have been commonly built using a set of sensors, at least one per analyte under study. Complex signals recorded with these systems are formed by the sensors' responses to the analytes of interest plus interferents, from which a multivariate response model is then developed. This work describes a data treatment method for the simultaneous quantification of two species in solution employing the signal from a single sensor. The approach used here takes advantage of the complex information recorded with one electrode's transient after insertion of sample for building the calibration models for both analytes.more » The departure information from the electrode was firstly processed by discrete wavelet for transforming the signals to extract useful information and reduce its length, and then by artificial neural networks for fitting a model. Two different potentiometric sensors were used as study case for simultaneously corroborating the effectiveness of the approach.« less

On-line monitoring the extract process of Fu-fang Shuanghua oral solution using near infrared spectroscopy and different PLS algorithms

NASA Astrophysics Data System (ADS)

Kang, Qian; Ru, Qingguo; Liu, Yan; Xu, Lingyan; Liu, Jia; Wang, Yifei; Zhang, Yewen; Li, Hui; Zhang, Qing; Wu, Qing

2016-01-01

An on-line near infrared (NIR) spectroscopy monitoring method with an appropriate multivariate calibration method was developed for the extraction process of Fu-fang Shuanghua oral solution (FSOS). On-line NIR spectra were collected through two fiber optic probes, which were designed to transmit NIR radiation by a 2 mm flange. Partial least squares (PLS), interval PLS (iPLS) and synergy interval PLS (siPLS) algorithms were used comparatively for building the calibration regression models. During the extraction process, the feasibility of NIR spectroscopy was employed to determine the concentrations of chlorogenic acid (CA) content, total phenolic acids contents (TPC), total flavonoids contents (TFC) and soluble solid contents (SSC). High performance liquid chromatography (HPLC), ultraviolet spectrophotometric method (UV) and loss on drying methods were employed as reference methods. Experiment results showed that the performance of siPLS model is the best compared with PLS and iPLS. The calibration models for AC, TPC, TFC and SSC had high values of determination coefficients of (R2) (0.9948, 0.9992, 0.9950 and 0.9832) and low root mean square error of cross validation (RMSECV) (0.0113, 0.0341, 0.1787 and 1.2158), which indicate a good correlation between reference values and NIR predicted values. The overall results show that the on line detection method could be feasible in real application and would be of great value for monitoring the mixed decoction process of FSOS and other Chinese patent medicines.

Chemometric methods for the simultaneous determination of some water-soluble vitamins.

PubMed

Mohamed, Abdel-Maaboud I; Mohamed, Horria A; Mohamed, Niveen A; El-Zahery, Marwa R

2011-01-01

Two spectrophotometric methods, derivative and multivariate methods, were applied for the determination of binary, ternary, and quaternary mixtures of the water-soluble vitamins thiamine HCI (I), pyridoxine HCI (II), riboflavin (III), and cyanocobalamin (IV). The first method is divided into first derivative and first derivative of ratio spectra methods, and the second into classical least squares and principal components regression methods. Both methods are based on spectrophotometric measurements of the studied vitamins in 0.1 M HCl solution in the range of 200-500 nm for all components. The linear calibration curves were obtained from 2.5-90 microg/mL, and the correlation coefficients ranged from 0.9991 to 0.9999. These methods were applied for the analysis of the following mixtures: (I) and (II); (I), (II), and (III); (I), (II), and (IV); and (I), (II), (III), and (IV). The described methods were successfully applied for the determination of vitamin combinations in synthetic mixtures and dosage forms from different manufacturers. The recovery ranged from 96.1 +/- 1.2 to 101.2 +/- 1.0% for derivative methods and 97.0 +/- 0.5 to 101.9 +/- 1.3% for multivariate methods. The results of the developed methods were compared with those of reported methods, and gave good accuracy and precision.

Kinetic approach for the enzymatic determination of levodopa and carbidopa assisted by multivariate curve resolution-alternating least squares.

PubMed

Grünhut, Marcos; Garrido, Mariano; Centurión, Maria E; Fernández Band, Beatriz S

2010-07-12

A combination of kinetic spectroscopic monitoring and multivariate curve resolution-alternating least squares (MCR-ALS) was proposed for the enzymatic determination of levodopa (LVD) and carbidopa (CBD) in pharmaceuticals. The enzymatic reaction process was carried out in a reverse stopped-flow injection system and monitored by UV-vis spectroscopy. The spectra (292-600 nm) were recorded throughout the reaction and were analyzed by multivariate curve resolution-alternating least squares. A small calibration matrix containing nine mixtures was used in the model construction. Additionally, to evaluate the prediction ability of the model, a set with six validation mixtures was used. The lack of fit obtained was 4.3%, the explained variance 99.8% and the overall prediction error 5.5%. Tablets of commercial samples were analyzed and the results were validated by pharmacopeia method (high performance liquid chromatography). No significant differences were found (alpha=0.05) between the reference values and the ones obtained with the proposed method. It is important to note that a unique chemometric model made it possible to determine both analytes simultaneously. Copyright 2010 Elsevier B.V. All rights reserved.

Fast Detection of Copper Content in Rice by Laser-Induced Breakdown Spectroscopy with Uni- and Multivariate Analysis.

PubMed

Liu, Fei; Ye, Lanhan; Peng, Jiyu; Song, Kunlin; Shen, Tingting; Zhang, Chu; He, Yong

2018-02-27

Fast detection of heavy metals is very important for ensuring the quality and safety of crops. Laser-induced breakdown spectroscopy (LIBS), coupled with uni- and multivariate analysis, was applied for quantitative analysis of copper in three kinds of rice (Jiangsu rice, regular rice, and Simiao rice). For univariate analysis, three pre-processing methods were applied to reduce fluctuations, including background normalization, the internal standard method, and the standard normal variate (SNV). Linear regression models showed a strong correlation between spectral intensity and Cu content, with an R 2 more than 0.97. The limit of detection (LOD) was around 5 ppm, lower than the tolerance limit of copper in foods. For multivariate analysis, partial least squares regression (PLSR) showed its advantage in extracting effective information for prediction, and its sensitivity reached 1.95 ppm, while support vector machine regression (SVMR) performed better in both calibration and prediction sets, where R c 2 and R p 2 reached 0.9979 and 0.9879, respectively. This study showed that LIBS could be considered as a constructive tool for the quantification of copper contamination in rice.

Fast Detection of Copper Content in Rice by Laser-Induced Breakdown Spectroscopy with Uni- and Multivariate Analysis

PubMed Central

Ye, Lanhan; Song, Kunlin; Shen, Tingting

2018-01-01

Fast detection of heavy metals is very important for ensuring the quality and safety of crops. Laser-induced breakdown spectroscopy (LIBS), coupled with uni- and multivariate analysis, was applied for quantitative analysis of copper in three kinds of rice (Jiangsu rice, regular rice, and Simiao rice). For univariate analysis, three pre-processing methods were applied to reduce fluctuations, including background normalization, the internal standard method, and the standard normal variate (SNV). Linear regression models showed a strong correlation between spectral intensity and Cu content, with an R2 more than 0.97. The limit of detection (LOD) was around 5 ppm, lower than the tolerance limit of copper in foods. For multivariate analysis, partial least squares regression (PLSR) showed its advantage in extracting effective information for prediction, and its sensitivity reached 1.95 ppm, while support vector machine regression (SVMR) performed better in both calibration and prediction sets, where Rc2 and Rp2 reached 0.9979 and 0.9879, respectively. This study showed that LIBS could be considered as a constructive tool for the quantification of copper contamination in rice. PMID:29495445

Salicylic acid deposition from wash-off products: comparison of in vivo and porcine deposition models.

PubMed

Davies, M A

2015-10-01

Salicylic acid (SA) is a widely used active in anti-acne face wash products. Only about 1-2% of the total dose is actually deposited on skin during washing, and more efficient deposition systems are sought. The objective of this work was to develop an improved method, including data analysis, to measure deposition of SA from wash-off formulae. Full fluorescence excitation-emission matrices (EEMs) were acquired for non-invasive measurement of deposition of SA from wash-off products. Multivariate data analysis methods - parallel factor analysis and N-way partial least-squares regression - were used to develop and compare deposition models on human volunteers and porcine skin. Although both models are useful, there are differences between them. First, the range of linear response to dosages of SA was 60 μg cm(-2) in vivo compared to 25 μg cm(-2) on porcine skin. Second, the actual shape of the SA band was different between substrates. The methods employed in this work highlight the utility of the use of EEMs, in conjunction with multivariate analysis tools such as parallel factor analysis and multiway partial least-squares calibration, in determining sources of spectral variability in skin and quantification of exogenous species deposited on skin. The human model exhibited the widest range of linearity, but porcine model is still useful up to deposition levels of 25 μg cm(-2) or used with nonlinear calibration models. © 2015 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Prospects of second generation artificial intelligence tools in calibration of chemical sensors.

PubMed

Braibanti, Antonio; Rao, Rupenaguntla Sambasiva; Ramam, Veluri Anantha; Rao, Gollapalli Nageswara; Rao, Vaddadi Venkata Panakala

2005-05-01

Multivariate data driven calibration models with neural networks (NNs) are developed for binary (Cu++ and Ca++) and quaternary (K+, Ca++, NO3- and Cl-) ion-selective electrode (ISE) data. The response profiles of ISEs with concentrations are non-linear and sub-Nernstian. This task represents function approximation of multi-variate, multi-response, correlated, non-linear data with unknown noise structure i.e. multi-component calibration/prediction in chemometric parlance. Radial distribution function (RBF) and Fuzzy-ARTMAP-NN models implemented in the software packages, TRAJAN and Professional II, are employed for the calibration. The optimum NN models reported are based on residuals in concentration space. Being a data driven information technology, NN does not require a model, prior- or posterior- distribution of data or noise structure. Missing information, spikes or newer trends in different concentration ranges can be modeled through novelty detection. Two simulated data sets generated from mathematical functions are modeled as a function of number of data points and network parameters like number of neurons and nearest neighbors. The success of RBF and Fuzzy-ARTMAP-NNs to develop adequate calibration models for experimental data and function approximation models for more complex simulated data sets ensures AI2 (artificial intelligence, 2nd generation) as a promising technology in quantitation.

Multivariate calibration standardization across instruments for the determination of glucose by Fourier transform near-infrared spectrometry.

PubMed

Zhang, Lin; Small, Gary W; Arnold, Mark A

2003-11-01

The transfer of multivariate calibration models is investigated between a primary (A) and two secondary Fourier transform near-infrared (near-IR) spectrometers (B, C). The application studied in this work is the use of bands in the near-IR combination region of 5000-4000 cm(-)(1) to determine physiological levels of glucose in a buffered aqueous matrix containing varying levels of alanine, ascorbate, lactate, triacetin, and urea. The three spectrometers are used to measure 80 samples produced through a randomized experimental design that minimizes correlations between the component concentrations and between the concentrations of glucose and water. Direct standardization (DS), piecewise direct standardization (PDS), and guided model reoptimization (GMR) are evaluated for use in transferring partial least-squares calibration models developed with the spectra of 64 samples from the primary instrument to the prediction of glucose concentrations in 16 prediction samples measured with each secondary spectrometer. The three algorithms are evaluated as a function of the number of standardization samples used in transferring the calibration models. Performance criteria for judging the success of the calibration transfer are established as the standard error of prediction (SEP) for internal calibration models built with the spectra of the 64 calibration samples collected with each secondary spectrometer. These SEP values are 1.51 and 1.14 mM for spectrometers B and C, respectively. When calibration standardization is applied, the GMR algorithm is observed to outperform DS and PDS. With spectrometer C, the calibration transfer is highly successful, producing an SEP value of 1.07 mM. However, an SEP of 2.96 mM indicates unsuccessful calibration standardization with spectrometer B. This failure is attributed to differences in the variance structure of the spectra collected with spectrometers A and B. Diagnostic procedures are presented for use with the GMR algorithm that forecasts the successful calibration transfer with spectrometer C and the unsatisfactory results with spectrometer B.

Classical and Bayesian Seismic Yield Estimation: The 1998 Indian and Pakistani Tests

NASA Astrophysics Data System (ADS)

Shumway, R. H.

2001-10-01

- The nuclear tests in May, 1998, in India and Pakistan have stimulated a renewed interest in yield estimation, based on limited data from uncalibrated test sites. We study here the problem of estimating yields using classical and Bayesian methods developed by Shumway (1992), utilizing calibration data from the Semipalatinsk test site and measured magnitudes for the 1998 Indian and Pakistani tests given by Murphy (1998). Calibration is done using multivariate classical or Bayesian linear regression, depending on the availability of measured magnitude-yield data and prior information. Confidence intervals for the classical approach are derived applying an extension of Fieller's method suggested by Brown (1982). In the case where prior information is available, the posterior predictive magnitude densities are inverted to give posterior intervals for yield. Intervals obtained using the joint distribution of magnitudes are comparable to the single-magnitude estimates produced by Murphy (1998) and reinforce the conclusion that the announced yields of the Indian and Pakistani tests were too high.

Classical and Bayesian Seismic Yield Estimation: The 1998 Indian and Pakistani Tests

NASA Astrophysics Data System (ADS)

Shumway, R. H.

The nuclear tests in May, 1998, in India and Pakistan have stimulated a renewed interest in yield estimation, based on limited data from uncalibrated test sites. We study here the problem of estimating yields using classical and Bayesian methods developed by Shumway (1992), utilizing calibration data from the Semipalatinsk test site and measured magnitudes for the 1998 Indian and Pakistani tests given by Murphy (1998). Calibration is done using multivariate classical or Bayesian linear regression, depending on the availability of measured magnitude-yield data and prior information. Confidence intervals for the classical approach are derived applying an extension of Fieller's method suggested by Brown (1982). In the case where prior information is available, the posterior predictive magnitude densities are inverted to give posterior intervals for yield. Intervals obtained using the joint distribution of magnitudes are comparable to the single-magnitude estimates produced by Murphy (1998) and reinforce the conclusion that the announced yields of the Indian and Pakistani tests were too high.

FT-IR/ATR univariate and multivariate calibration models for in situ monitoring of sugars in complex microalgal culture media.

PubMed

Girard, Jean-Michel; Deschênes, Jean-Sébastien; Tremblay, Réjean; Gagnon, Jonathan

2013-09-01

The objective of this work is to develop a quick and simple method for the in situ monitoring of sugars in biological cultures. A new technology based on Attenuated Total Reflectance-Fourier Transform Infrared (FT-IR/ATR) spectroscopy in combination with an external light guiding fiber probe was tested, first to build predictive models from solutions of pure sugars, and secondly to use those models to monitor the sugars in the complex culture medium of mixotrophic microalgae. Quantification results from the univariate model were correlated with the total dissolved solids content (R(2)=0.74). A vector normalized multivariate model was used to proportionally quantify the different sugars present in the complex culture medium and showed a predictive accuracy of >90% for sugars representing >20% of the total. This method offers an alternative to conventional sugar monitoring assays and could be used at-line or on-line in commercial scale production systems. Copyright © 2013 Elsevier Ltd. All rights reserved.

Assessing Principal Component Regression Prediction of Neurochemicals Detected with Fast-Scan Cyclic Voltammetry

PubMed Central

2011-01-01

Principal component regression is a multivariate data analysis approach routinely used to predict neurochemical concentrations from in vivo fast-scan cyclic voltammetry measurements. This mathematical procedure can rapidly be employed with present day computer programming languages. Here, we evaluate several methods that can be used to evaluate and improve multivariate concentration determination. The cyclic voltammetric representation of the calculated regression vector is shown to be a valuable tool in determining whether the calculated multivariate model is chemically appropriate. The use of Cook’s distance successfully identified outliers contained within in vivo fast-scan cyclic voltammetry training sets. This work also presents the first direct interpretation of a residual color plot and demonstrated the effect of peak shifts on predicted dopamine concentrations. Finally, separate analyses of smaller increments of a single continuous measurement could not be concatenated without substantial error in the predicted neurochemical concentrations due to electrode drift. Taken together, these tools allow for the construction of more robust multivariate calibration models and provide the first approach to assess the predictive ability of a procedure that is inherently impossible to validate because of the lack of in vivo standards. PMID:21966586

Assessing principal component regression prediction of neurochemicals detected with fast-scan cyclic voltammetry.

PubMed

Keithley, Richard B; Wightman, R Mark

2011-06-07

Principal component regression is a multivariate data analysis approach routinely used to predict neurochemical concentrations from in vivo fast-scan cyclic voltammetry measurements. This mathematical procedure can rapidly be employed with present day computer programming languages. Here, we evaluate several methods that can be used to evaluate and improve multivariate concentration determination. The cyclic voltammetric representation of the calculated regression vector is shown to be a valuable tool in determining whether the calculated multivariate model is chemically appropriate. The use of Cook's distance successfully identified outliers contained within in vivo fast-scan cyclic voltammetry training sets. This work also presents the first direct interpretation of a residual color plot and demonstrated the effect of peak shifts on predicted dopamine concentrations. Finally, separate analyses of smaller increments of a single continuous measurement could not be concatenated without substantial error in the predicted neurochemical concentrations due to electrode drift. Taken together, these tools allow for the construction of more robust multivariate calibration models and provide the first approach to assess the predictive ability of a procedure that is inherently impossible to validate because of the lack of in vivo standards.

Risk prediction models for major adverse cardiac event (MACE) following percutaneous coronary intervention (PCI): A review

NASA Astrophysics Data System (ADS)

Manan, Norhafizah A.; Abidin, Basir

2015-02-01

Five percent of patients who went through Percutaneous Coronary Intervention (PCI) experienced Major Adverse Cardiac Events (MACE) after PCI procedure. Risk prediction of MACE following a PCI procedure therefore is helpful. This work describes a review of such prediction models currently in use. Literature search was done on PubMed and SCOPUS database. Thirty literatures were found but only 4 studies were chosen based on the data used, design, and outcome of the study. Particular emphasis was given and commented on the study design, population, sample size, modeling method, predictors, outcomes, discrimination and calibration of the model. All the models had acceptable discrimination ability (C-statistics >0.7) and good calibration (Hosmer-Lameshow P-value >0.05). Most common model used was multivariate logistic regression and most popular predictor was age.

Multivariate Analysis for Quantification of Plutonium(IV) in Nitric Acid Based on Absorption Spectra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lines, Amanda M.; Adami, Susan R.; Sinkov, Sergey I.

Development of more effective, reliable, and fast methods for monitoring process streams is a growing opportunity for analytical applications. Many fields can benefit from on-line monitoring, including the nuclear fuel cycle where improved methods for monitoring radioactive materials will facilitate maintenance of proper safeguards and ensure safe and efficient processing of materials. On-line process monitoring with a focus on optical spectroscopy can provide a fast, non-destructive method for monitoring chemical species. However, identification and quantification of species can be hindered by the complexity of the solutions if bands overlap or show condition-dependent spectral features. Plutonium (IV) is one example ofmore » a species which displays significant spectral variation with changing nitric acid concentration. Single variate analysis (i.e. Beer’s Law) is difficult to apply to the quantification of Pu(IV) unless the nitric acid concentration is known and separate calibration curves have been made for all possible acid strengths. Multivariate, or chemometric, analysis is an approach that allows for the accurate quantification of Pu(IV) without a priori knowledge of nitric acid concentration.« less

Predictive analysis of beer quality by correlating sensory evaluation with higher alcohol and ester production using multivariate statistics methods.

PubMed

Dong, Jian-Jun; Li, Qing-Liang; Yin, Hua; Zhong, Cheng; Hao, Jun-Guang; Yang, Pan-Fei; Tian, Yu-Hong; Jia, Shi-Ru

2014-10-15

Sensory evaluation is regarded as a necessary procedure to ensure a reproducible quality of beer. Meanwhile, high-throughput analytical methods provide a powerful tool to analyse various flavour compounds, such as higher alcohol and ester. In this study, the relationship between flavour compounds and sensory evaluation was established by non-linear models such as partial least squares (PLS), genetic algorithm back-propagation neural network (GA-BP), support vector machine (SVM). It was shown that SVM with a Radial Basis Function (RBF) had a better performance of prediction accuracy for both calibration set (94.3%) and validation set (96.2%) than other models. Relatively lower prediction abilities were observed for GA-BP (52.1%) and PLS (31.7%). In addition, the kernel function of SVM played an essential role of model training when the prediction accuracy of SVM with polynomial kernel function was 32.9%. As a powerful multivariate statistics method, SVM holds great potential to assess beer quality. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multivariate methods on the excitation emission matrix fluorescence spectroscopic data of diesel-kerosene mixtures: a comparative study.

PubMed

Divya, O; Mishra, Ashok K

2007-05-29

Quantitative determination of kerosene fraction present in diesel has been carried out based on excitation emission matrix fluorescence (EEMF) along with parallel factor analysis (PARAFAC) and N-way partial least squares regression (N-PLS). EEMF is a simple, sensitive and nondestructive method suitable for the analysis of multifluorophoric mixtures. Calibration models consisting of varying compositions of diesel and kerosene were constructed and their validation was carried out using leave-one-out cross validation method. The accuracy of the model was evaluated through the root mean square error of prediction (RMSEP) for the PARAFAC, N-PLS and unfold PLS methods. N-PLS was found to be a better method compared to PARAFAC and unfold PLS method because of its low RMSEP values.

Nomogram Prediction of Overall Survival After Curative Irradiation for Uterine Cervical Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seo, YoungSeok; Yoo, Seong Yul; Kim, Mi-Sook

Purpose: The purpose of this study was to develop a nomogram capable of predicting the probability of 5-year survival after radical radiotherapy (RT) without chemotherapy for uterine cervical cancer. Methods and Materials: We retrospectively analyzed 549 patients that underwent radical RT for uterine cervical cancer between March 1994 and April 2002 at our institution. Multivariate analysis using Cox proportional hazards regression was performed and this Cox model was used as the basis for the devised nomogram. The model was internally validated for discrimination and calibration by bootstrap resampling. Results: By multivariate regression analysis, the model showed that age, hemoglobin levelmore » before RT, Federation Internationale de Gynecologie Obstetrique (FIGO) stage, maximal tumor diameter, lymph node status, and RT dose at Point A significantly predicted overall survival. The survival prediction model demonstrated good calibration and discrimination. The bootstrap-corrected concordance index was 0.67. The predictive ability of the nomogram proved to be superior to FIGO stage (p = 0.01). Conclusions: The devised nomogram offers a significantly better level of discrimination than the FIGO staging system. In particular, it improves predictions of survival probability and could be useful for counseling patients, choosing treatment modalities and schedules, and designing clinical trials. However, before this nomogram is used clinically, it should be externally validated.« less

Investigating the discrimination potential of linear and nonlinear spectral multivariate calibrations for analysis of phenolic compounds in their binary and ternary mixtures and calculation pKa values.

PubMed

Rasouli, Zolaikha; Ghavami, Raouf

2016-08-05

Vanillin (VA), vanillic acid (VAI) and syringaldehyde (SIA) are important food additives as flavor enhancers. The current study for the first time is devote to the application of partial least square (PLS-1), partial robust M-regression (PRM) and feed forward neural networks (FFNNs) as linear and nonlinear chemometric methods for the simultaneous detection of binary and ternary mixtures of VA, VAI and SIA using data extracted directly from UV-spectra with overlapped peaks of individual analytes. Under the optimum experimental conditions, for each compound a linear calibration was obtained in the concentration range of 0.61-20.99 [LOD=0.12], 0.67-23.19 [LOD=0.13] and 0.73-25.12 [LOD=0.15] μgmL(-1) for VA, VAI and SIA, respectively. Four calibration sets of standard samples were designed by combination of a full and fractional factorial designs with the use of the seven and three levels for each factor for binary and ternary mixtures, respectively. The results of this study reveal that both the methods of PLS-1 and PRM are similar in terms of predict ability each binary mixtures. The resolution of ternary mixture has been accomplished by FFNNs. Multivariate curve resolution-alternating least squares (MCR-ALS) was applied for the description of spectra from the acid-base titration systems each individual compound, i.e. the resolution of the complex overlapping spectra as well as to interpret the extracted spectral and concentration profiles of any pure chemical species identified. Evolving factor analysis (EFA) and singular value decomposition (SVD) were used to distinguish the number of chemical species. Subsequently, their corresponding dissociation constants were derived. Finally, FFNNs has been used to detection active compounds in real and spiked water samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigating the discrimination potential of linear and nonlinear spectral multivariate calibrations for analysis of phenolic compounds in their binary and ternary mixtures and calculation pKa values

NASA Astrophysics Data System (ADS)

Rasouli, Zolaikha; Ghavami, Raouf

2016-08-01

Vanillin (VA), vanillic acid (VAI) and syringaldehyde (SIA) are important food additives as flavor enhancers. The current study for the first time is devote to the application of partial least square (PLS-1), partial robust M-regression (PRM) and feed forward neural networks (FFNNs) as linear and nonlinear chemometric methods for the simultaneous detection of binary and ternary mixtures of VA, VAI and SIA using data extracted directly from UV-spectra with overlapped peaks of individual analytes. Under the optimum experimental conditions, for each compound a linear calibration was obtained in the concentration range of 0.61-20.99 [LOD = 0.12], 0.67-23.19 [LOD = 0.13] and 0.73-25.12 [LOD = 0.15] μg mL- 1 for VA, VAI and SIA, respectively. Four calibration sets of standard samples were designed by combination of a full and fractional factorial designs with the use of the seven and three levels for each factor for binary and ternary mixtures, respectively. The results of this study reveal that both the methods of PLS-1 and PRM are similar in terms of predict ability each binary mixtures. The resolution of ternary mixture has been accomplished by FFNNs. Multivariate curve resolution-alternating least squares (MCR-ALS) was applied for the description of spectra from the acid-base titration systems each individual compound, i.e. the resolution of the complex overlapping spectra as well as to interpret the extracted spectral and concentration profiles of any pure chemical species identified. Evolving factor analysis (EFA) and singular value decomposition (SVD) were used to distinguish the number of chemical species. Subsequently, their corresponding dissociation constants were derived. Finally, FFNNs has been used to detection active compounds in real and spiked water samples.

Reduction of interferences in graphite furnace atomic absorption spectrometry by multiple linear regression modelling

NASA Astrophysics Data System (ADS)

Grotti, Marco; Abelmoschi, Maria Luisa; Soggia, Francesco; Tiberiade, Christian; Frache, Roberto

2000-12-01

The multivariate effects of Na, K, Mg and Ca as nitrates on the electrothermal atomisation of manganese, cadmium and iron were studied by multiple linear regression modelling. Since the models proved to efficiently predict the effects of the considered matrix elements in a wide range of concentrations, they were applied to correct the interferences occurring in the determination of trace elements in seawater after pre-concentration of the analytes. In order to obtain a statistically significant number of samples, a large volume of the certified seawater reference materials CASS-3 and NASS-3 was treated with Chelex-100 resin; then, the chelating resin was separated from the solution, divided into several sub-samples, each of them was eluted with nitric acid and analysed by electrothermal atomic absorption spectrometry (for trace element determinations) and inductively coupled plasma optical emission spectrometry (for matrix element determinations). To minimise any other systematic error besides that due to matrix effects, accuracy of the pre-concentration step and contamination levels of the procedure were checked by inductively coupled plasma mass spectrometric measurements. Analytical results obtained by applying the multiple linear regression models were compared with those obtained with other calibration methods, such as external calibration using acid-based standards, external calibration using matrix-matched standards and the analyte addition technique. Empirical models proved to efficiently reduce interferences occurring in the analysis of real samples, allowing an improvement of accuracy better than for other calibration methods.

ASTM clustering for improving coal analysis by near-infrared spectroscopy.

PubMed

Andrés, J M; Bona, M T

2006-11-15

Multivariate analysis techniques have been applied to near-infrared (NIR) spectra coals to investigate the relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding predictor variables. In this work, a whole set of coal samples was grouped into six more homogeneous clusters following the ASTM reference method for classification prior to the application of calibration methods to each coal set. The results obtained showed a considerable improvement of the error determination compared with the calibration for the whole sample set. For some groups, the established calibrations approached the quality required by the ASTM/ISO norms for laboratory analysis. To predict property values for a new coal sample it is necessary the assignation of that sample to its respective group. Thus, the discrimination and classification ability of coal samples by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) in the NIR range was also studied by applying Soft Independent Modelling of Class Analogy (SIMCA) and Linear Discriminant Analysis (LDA) techniques. Modelling of the groups by SIMCA led to overlapping models that cannot discriminate for unique classification. On the other hand, the application of Linear Discriminant Analysis improved the classification of the samples but not enough to be satisfactory for every group considered.

Digital filtering and model updating methods for improving the robustness of near-infrared multivariate calibrations.

PubMed

Kramer, Kirsten E; Small, Gary W

2009-02-01

Fourier transform near-infrared (NIR) transmission spectra are used for quantitative analysis of glucose for 17 sets of prediction data sampled as much as six months outside the timeframe of the corresponding calibration data. Aqueous samples containing physiological levels of glucose in a matrix of bovine serum albumin and triacetin are used to simulate clinical samples such as blood plasma. Background spectra of a single analyte-free matrix sample acquired during the instrumental warm-up period on the prediction day are used for calibration updating and for determining the optimal frequency response of a preprocessing infinite impulse response time-domain digital filter. By tuning the filter and the calibration model to the specific instrumental response associated with the prediction day, the calibration model is given enhanced ability to operate over time. This methodology is demonstrated in conjunction with partial least squares calibration models built with a spectral range of 4700-4300 cm(-1). By using a subset of the background spectra to evaluate the prediction performance of the updated model, projections can be made regarding the success of subsequent glucose predictions. If a threshold standard error of prediction (SEP) of 1.5 mM is used to establish successful model performance with the glucose samples, the corresponding threshold for the SEP of the background spectra is found to be 1.3 mM. For calibration updating in conjunction with digital filtering, SEP values of all 17 prediction sets collected over 3-178 days displaced from the calibration data are below 1.5 mM. In addition, the diagnostic based on the background spectra correctly assesses the prediction performance in 16 of the 17 cases.

A comparison of ensemble post-processing approaches that preserve correlation structures

NASA Astrophysics Data System (ADS)

Schefzik, Roman; Van Schaeybroeck, Bert; Vannitsem, Stéphane

2016-04-01

Despite the fact that ensemble forecasts address the major sources of uncertainty, they exhibit biases and dispersion errors and therefore are known to improve by calibration or statistical post-processing. For instance the ensemble model output statistics (EMOS) method, also known as non-homogeneous regression approach (Gneiting et al., 2005) is known to strongly improve forecast skill. EMOS is based on fitting and adjusting a parametric probability density function (PDF). However, EMOS and other common post-processing approaches apply to a single weather quantity at a single location for a single look-ahead time. They are therefore unable of taking into account spatial, inter-variable and temporal dependence structures. Recently many research efforts have been invested in designing post-processing methods that resolve this drawback but also in verification methods that enable the detection of dependence structures. New verification methods are applied on two classes of post-processing methods, both generating physically coherent ensembles. A first class uses the ensemble copula coupling (ECC) that starts from EMOS but adjusts the rank structure (Schefzik et al., 2013). The second class is a member-by-member post-processing (MBM) approach that maps each raw ensemble member to a corrected one (Van Schaeybroeck and Vannitsem, 2015). We compare variants of the EMOS-ECC and MBM classes and highlight a specific theoretical connection between them. All post-processing variants are applied in the context of the ensemble system of the European Centre of Weather Forecasts (ECMWF) and compared using multivariate verification tools including the energy score, the variogram score (Scheuerer and Hamill, 2015) and the band depth rank histogram (Thorarinsdottir et al., 2015). Gneiting, Raftery, Westveld, and Goldman, 2005: Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation. Mon. Wea. Rev., {133}, 1098-1118. Scheuerer and Hamill, 2015. Variogram-based proper scoring rules for probabilistic forecasts of multivariate quantities. Mon. Wea. Rev. {143},1321-1334. Schefzik, Thorarinsdottir, Gneiting. Uncertainty quantification in complex simulation models using ensemble copula coupling. Statistical Science {28},616-640, 2013. Thorarinsdottir, M. Scheuerer, and C. Heinz, 2015. Assessing the calibration of high-dimensional ensemble forecasts using rank histograms, arXiv:1310.0236. Van Schaeybroeck and Vannitsem, 2015: Ensemble post-processing using member-by-member approaches: theoretical aspects. Q.J.R. Meteorol. Soc., 141: 807-818.

A comparison of two adaptive multivariate analysis methods (PLSR and ANN) for winter wheat yield forecasting using Landsat-8 OLI images

NASA Astrophysics Data System (ADS)

Chen, Pengfei; Jing, Qi

2017-02-01

An assumption that the non-linear method is more reasonable than the linear method when canopy reflectance is used to establish the yield prediction model was proposed and tested in this study. For this purpose, partial least squares regression (PLSR) and artificial neural networks (ANN), represented linear and non-linear analysis method, were applied and compared for wheat yield prediction. Multi-period Landsat-8 OLI images were collected at two different wheat growth stages, and a field campaign was conducted to obtain grain yields at selected sampling sites in 2014. The field data were divided into a calibration database and a testing database. Using calibration data, a cross-validation concept was introduced for the PLSR and ANN model construction to prevent over-fitting. All models were tested using the test data. The ANN yield-prediction model produced R2, RMSE and RMSE% values of 0.61, 979 kg ha-1, and 10.38%, respectively, in the testing phase, performing better than the PLSR yield-prediction model, which produced R2, RMSE, and RMSE% values of 0.39, 1211 kg ha-1, and 12.84%, respectively. Non-linear method was suggested as a better method for yield prediction.

Quantitative methods for compensation of matrix effects and self-absorption in Laser Induced Breakdown Spectroscopy signals of solids

NASA Astrophysics Data System (ADS)

Takahashi, Tomoko; Thornton, Blair

2017-12-01

This paper reviews methods to compensate for matrix effects and self-absorption during quantitative analysis of compositions of solids measured using Laser Induced Breakdown Spectroscopy (LIBS) and their applications to in-situ analysis. Methods to reduce matrix and self-absorption effects on calibration curves are first introduced. The conditions where calibration curves are applicable to quantification of compositions of solid samples and their limitations are discussed. While calibration-free LIBS (CF-LIBS), which corrects matrix effects theoretically based on the Boltzmann distribution law and Saha equation, has been applied in a number of studies, requirements need to be satisfied for the calculation of chemical compositions to be valid. Also, peaks of all elements contained in the target need to be detected, which is a bottleneck for in-situ analysis of unknown materials. Multivariate analysis techniques are gaining momentum in LIBS analysis. Among the available techniques, principal component regression (PCR) analysis and partial least squares (PLS) regression analysis, which can extract related information to compositions from all spectral data, are widely established methods and have been applied to various fields including in-situ applications in air and for planetary explorations. Artificial neural networks (ANNs), where non-linear effects can be modelled, have also been investigated as a quantitative method and their applications are introduced. The ability to make quantitative estimates based on LIBS signals is seen as a key element for the technique to gain wider acceptance as an analytical method, especially in in-situ applications. In order to accelerate this process, it is recommended that the accuracy should be described using common figures of merit which express the overall normalised accuracy, such as the normalised root mean square errors (NRMSEs), when comparing the accuracy obtained from different setups and analytical methods.

Wavelet analysis techniques applied to removing varying spectroscopic background in calibration model for pear sugar content

NASA Astrophysics Data System (ADS)

Liu, Yande; Ying, Yibin; Lu, Huishan; Fu, Xiaping

2005-11-01

A new method is proposed to eliminate the varying background and noise simultaneously for multivariate calibration of Fourier transform near infrared (FT-NIR) spectral signals. An ideal spectrum signal prototype was constructed based on the FT-NIR spectrum of fruit sugar content measurement. The performances of wavelet based threshold de-noising approaches via different combinations of wavelet base functions were compared. Three families of wavelet base function (Daubechies, Symlets and Coiflets) were applied to estimate the performance of those wavelet bases and threshold selection rules by a series of experiments. The experimental results show that the best de-noising performance is reached via the combinations of Daubechies 4 or Symlet 4 wavelet base function. Based on the optimization parameter, wavelet regression models for sugar content of pear were also developed and result in a smaller prediction error than a traditional Partial Least Squares Regression (PLSR) mode.

Rapid determination of chemical composition and classification of bamboo fractions using visible-near infrared spectroscopy coupled with multivariate data analysis.

PubMed

Yang, Zhong; Li, Kang; Zhang, Maomao; Xin, Donglin; Zhang, Junhua

2016-01-01

During conversion of bamboo into biofuels and chemicals, it is necessary to efficiently predict the chemical composition and digestibility of biomass. However, traditional methods for determination of lignocellulosic biomass composition are expensive and time consuming. In this work, a novel and fast method for quantitative and qualitative analysis of chemical composition and enzymatic digestibilities of juvenile bamboo and mature bamboo fractions (bamboo green, bamboo timber, bamboo yellow, bamboo node, and bamboo branch) using visible-near infrared spectra was evaluated. The developed partial least squares models yielded coefficients of determination in calibration of 0.88, 0.94, and 0.96, for cellulose, xylan, and lignin of bamboo fractions in raw spectra, respectively. After visible-near infrared spectra being pretreated, the corresponding coefficients of determination in calibration yielded by the developed partial least squares models are 0.994, 0.990, and 0.996, respectively. The score plots of principal component analysis of mature bamboo, juvenile bamboo, and different fractions of mature bamboo were obviously distinguished in raw spectra. Based on partial least squares discriminant analysis, the classification accuracies of mature bamboo, juvenile bamboo, and different fractions of bamboo (bamboo green, bamboo timber, bamboo yellow, and bamboo branch) all reached 100 %. In addition, high accuracies of evaluation of the enzymatic digestibilities of bamboo fractions after pretreatment with aqueous ammonia were also observed. The results showed the potential of visible-near infrared spectroscopy in combination with multivariate analysis in efficiently analyzing the chemical composition and hydrolysabilities of lignocellulosic biomass, such as bamboo fractions.

A multivariate regression model for detection of fumonisins content in maize from near infrared spectra.

PubMed

Giacomo, Della Riccia; Stefania, Del Zotto

2013-12-15

Fumonisins are mycotoxins produced by Fusarium species that commonly live in maize. Whereas fungi damage plants, fumonisins cause disease both to cattle breedings and human beings. Law limits set fumonisins tolerable daily intake with respect to several maize based feed and food. Chemical techniques assure the most reliable and accurate measurements, but they are expensive and time consuming. A method based on Near Infrared spectroscopy and multivariate statistical regression is described as a simpler, cheaper and faster alternative. We apply Partial Least Squares with full cross validation. Two models are described, having high correlation of calibration (0.995, 0.998) and of validation (0.908, 0.909), respectively. Description of observed phenomenon is accurate and overfitting is avoided. Screening of contaminated maize with respect to European legal limit of 4 mg kg(-1) should be assured. Copyright © 2013 Elsevier Ltd. All rights reserved.

Identification and quantification of ciprofloxacin in urine through excitation-emission fluorescence and three-way PARAFAC calibration.

PubMed

Ortiz, M C; Sarabia, L A; Sánchez, M S; Giménez, D

2009-05-29

Due to the second-order advantage, calibration models based on parallel factor analysis (PARAFAC) decomposition of three-way data are becoming important in routine analysis. This work studies the possibility of fitting PARAFAC models with excitation-emission fluorescence data for the determination of ciprofloxacin in human urine. The finally chosen PARAFAC decomposition is built with calibration samples spiked with ciprofloxacin, and with other series of urine samples that were also spiked. One of the series of samples has also another drug because the patient was taking mesalazine. The mesalazine is a fluorescent substance that interferes with the ciprofloxacin. Finally, the procedure is applied to samples of a patient who was being treated with ciprofloxacin. The trueness has been established by the regression "predicted concentration versus added concentration". The recovery factor is 88.3% for ciprofloxacin in urine, and the mean of the absolute value of the relative errors is 4.2% for 46 test samples. The multivariate sensitivity of the fit calibration model is evaluated by a regression between the loadings of PARAFAC linked to ciprofloxacin versus the true concentration in spiked samples. The multivariate capability of discrimination is near 8 microg L(-1) when the probabilities of false non-compliance and false compliance are fixed at 5%.

Predicting microbiologically defined infection in febrile neutropenic episodes in children: global individual participant data multivariable meta-analysis

PubMed Central

Phillips, Robert S; Sung, Lillian; Amman, Roland A; Riley, Richard D; Castagnola, Elio; Haeusler, Gabrielle M; Klaassen, Robert; Tissing, Wim J E; Lehrnbecher, Thomas; Chisholm, Julia; Hakim, Hana; Ranasinghe, Neil; Paesmans, Marianne; Hann, Ian M; Stewart, Lesley A

2016-01-01

Background: Risk-stratified management of fever with neutropenia (FN), allows intensive management of high-risk cases and early discharge of low-risk cases. No single, internationally validated, prediction model of the risk of adverse outcomes exists for children and young people. An individual patient data (IPD) meta-analysis was undertaken to devise one. Methods: The ‘Predicting Infectious Complications in Children with Cancer' (PICNICC) collaboration was formed by parent representatives, international clinical and methodological experts. Univariable and multivariable analyses, using random effects logistic regression, were undertaken to derive and internally validate a risk-prediction model for outcomes of episodes of FN based on clinical and laboratory data at presentation. Results: Data came from 22 different study groups from 15 countries, of 5127 episodes of FN in 3504 patients. There were 1070 episodes in 616 patients from seven studies available for multivariable analysis. Univariable analyses showed associations with microbiologically defined infection (MDI) in many items, including higher temperature, lower white cell counts and acute myeloid leukaemia, but not age. Patients with osteosarcoma/Ewings sarcoma and those with more severe mucositis were associated with a decreased risk of MDI. The predictive model included: malignancy type, temperature, clinically ‘severely unwell', haemoglobin, white cell count and absolute monocyte count. It showed moderate discrimination (AUROC 0.723, 95% confidence interval 0.711–0.759) and good calibration (calibration slope 0.95). The model was robust to bootstrap and cross-validation sensitivity analyses. Conclusions: This new prediction model for risk of MDI appears accurate. It requires prospective studies assessing implementation to assist clinicians and parents/patients in individualised decision making. PMID:26954719

Moisture Influence Reducing Method for Heavy Metals Detection in Plant Materials Using Laser-Induced Breakdown Spectroscopy: A Case Study for Chromium Content Detection in Rice Leaves.

PubMed

Peng, Jiyu; He, Yong; Ye, Lanhan; Shen, Tingting; Liu, Fei; Kong, Wenwen; Liu, Xiaodan; Zhao, Yun

2017-07-18

Fast detection of heavy metals in plant materials is crucial for environmental remediation and ensuring food safety. However, most plant materials contain high moisture content, the influence of which cannot be simply ignored. Hence, we proposed moisture influence reducing method for fast detection of heavy metals using laser-induced breakdown spectroscopy (LIBS). First, we investigated the effect of moisture content on signal intensity, stability, and plasma parameters (temperature and electron density) and determined the main influential factors (experimental parameters F and the change of analyte concentration) on the variations of signal. For chromium content detection, the rice leaves were performed with a quick drying procedure, and two strategies were further used to reduce the effect of moisture content and shot-to-shot fluctuation. An exponential model based on the intensity of background was used to correct the actual element concentration in analyte. Also, the ratio of signal-to-background for univariable calibration and partial least squared regression (PLSR) for multivariable calibration were used to compensate the prediction deviations. The PLSR calibration model obtained the best result, with the correlation coefficient of 0.9669 and root-mean-square error of 4.75 mg/kg in the prediction set. The preliminary results indicated that the proposed method allowed for the detection of heavy metals in plant materials using LIBS, and it could be possibly used for element mapping in future work.

Gaussian Mixture Models of Between-Source Variation for Likelihood Ratio Computation from Multivariate Data

PubMed Central

Franco-Pedroso, Javier; Ramos, Daniel; Gonzalez-Rodriguez, Joaquin

2016-01-01

In forensic science, trace evidence found at a crime scene and on suspect has to be evaluated from the measurements performed on them, usually in the form of multivariate data (for example, several chemical compound or physical characteristics). In order to assess the strength of that evidence, the likelihood ratio framework is being increasingly adopted. Several methods have been derived in order to obtain likelihood ratios directly from univariate or multivariate data by modelling both the variation appearing between observations (or features) coming from the same source (within-source variation) and that appearing between observations coming from different sources (between-source variation). In the widely used multivariate kernel likelihood-ratio, the within-source distribution is assumed to be normally distributed and constant among different sources and the between-source variation is modelled through a kernel density function (KDF). In order to better fit the observed distribution of the between-source variation, this paper presents a different approach in which a Gaussian mixture model (GMM) is used instead of a KDF. As it will be shown, this approach provides better-calibrated likelihood ratios as measured by the log-likelihood ratio cost (Cllr) in experiments performed on freely available forensic datasets involving different trace evidences: inks, glass fragments and car paints. PMID:26901680

Performance of b-jet identification in the ATLAS experiment

DOE PAGES

Aad, G; Abbott, B; Abdallah, J; ...

2016-04-04

The identification of jets containing b hadrons is important for the physics programme of the ATLAS experiment at the Large Hadron Collider. Several algorithms to identify jets containing b hadrons are described, ranging from those based on the reconstruction of an inclusive secondary vertex or the presence of tracks with large impact parameters to combined tagging algorithms making use of multi-variate discriminants. An independent b-tagging algorithm based on the reconstruction of muons inside jets as well as the b-tagging algorithm used in the online trigger are also presented. The b-jet tagging efficiency, the c-jet tagging efficiency and the mistag ratemore » for light flavour jets in data have been measured with a number of complementary methods. The calibration results are presented as scale factors defined as the ratio of the efficiency (or mistag rate) in data to that in simulation. In the case of b jets, where more than one calibration method exists, the results from the various analyses have been combined taking into account the statistical correlation as well as the correlation of the sources of systematic uncertainty.« less

An Improved Weighted Partial Least Squares Method Coupled with Near Infrared Spectroscopy for Rapid Determination of Multiple Components and Anti-Oxidant Activity of Pu-Erh Tea.

PubMed

Liu, Ze; Xie, Hua-Lin; Chen, Lin; Huang, Jian-Hua

2018-05-02

Background: Pu-erh tea is a unique microbially fermented tea, which distinctive chemical constituents and activities are worthy of systematic study. Near infrared spectroscopy (NIR) coupled with suitable chemometrics approaches can rapidly and accurately quantitatively analyze multiple compounds in samples. Methods: In this study, an improved weighted partial least squares (PLS) algorithm combined with near infrared spectroscopy (NIR) was used to construct a fast calibration model for determining four main components, i.e., tea polyphenols, tea polysaccharide, total flavonoids, theanine content, and further determine the total antioxidant capacity of pu-erh tea. Results: The final correlation coefficients R square for tea polyphenols, tea polysaccharide, total flavonoids content, theanine content, and total antioxidant capacity were 0.8288, 0.8403, 0.8415, 0.8537 and 0.8682, respectively. Conclusions : The current study provided a comprehensive study of four main ingredients and activity of pu-erh tea, and demonstrated that NIR spectroscopy technology coupled with multivariate calibration analysis could be successfully applied to pu-erh tea quality assessment.

Application of near-infrared spectroscopy for the rapid quality assessment of Radix Paeoniae Rubra

NASA Astrophysics Data System (ADS)

Zhan, Hao; Fang, Jing; Tang, Liying; Yang, Hongjun; Li, Hua; Wang, Zhuju; Yang, Bin; Wu, Hongwei; Fu, Meihong

2017-08-01

Near-infrared (NIR) spectroscopy with multivariate analysis was used to quantify gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra, and the feasibility to classify the samples originating from different areas was investigated. A new high-performance liquid chromatography method was developed and validated to analyze gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra as the reference. Partial least squares (PLS), principal component regression (PCR), and stepwise multivariate linear regression (SMLR) were performed to calibrate the regression model. Different data pretreatments such as derivatives (1st and 2nd), multiplicative scatter correction, standard normal variate, Savitzky-Golay filter, and Norris derivative filter were applied to remove the systematic errors. The performance of the model was evaluated according to the root mean square of calibration (RMSEC), root mean square error of prediction (RMSEP), root mean square error of cross-validation (RMSECV), and correlation coefficient (r). The results show that compared to PCR and SMLR, PLS had a lower RMSEC, RMSECV, and RMSEP and higher r for all the four analytes. PLS coupled with proper pretreatments showed good performance in both the fitting and predicting results. Furthermore, the original areas of Radix Paeoniae Rubra samples were partly distinguished by principal component analysis. This study shows that NIR with PLS is a reliable, inexpensive, and rapid tool for the quality assessment of Radix Paeoniae Rubra.

Near and mid infrared spectroscopy and multivariate data analysis in studies of oxidation of edible oils.

PubMed

Wójcicki, Krzysztof; Khmelinskii, Igor; Sikorski, Marek; Sikorska, Ewa

2015-11-15

Infrared spectroscopic techniques and chemometric methods were used to study oxidation of olive, sunflower and rapeseed oils. Accelerated oxidative degradation of oils at 60°C was monitored using peroxide values and FT-MIR ATR and FT-NIR transmittance spectroscopy. Principal component analysis (PCA) facilitated visualization and interpretation of spectral changes occurring during oxidation. Multivariate curve resolution (MCR) method found three spectral components in the NIR and MIR spectral matrix, corresponding to the oxidation products, and saturated and unsaturated structures. Good quantitative relation was found between peroxide value and contribution of oxidation products evaluated using MCR--based on NIR (R(2) = 0.890), MIR (R(2) = 0.707) and combined NIR and MIR (R(2) = 0.747) data. Calibration models for prediction peroxide value established using partial least squares (PLS) regression were characterized for MIR (R(2) = 0.701, RPD = 1.7), NIR (R(2) = 0.970, RPD = 5.3), and combined NIR and MIR data (R(2) = 0.954, RPD = 3.1). Copyright © 2015 Elsevier Ltd. All rights reserved.

Luminescence Sensors Applied to Water Analysis of Organic Pollutants—An Update

PubMed Central

Ibañez, Gabriela A.; Escandar, Graciela M.

2011-01-01

The development of chemical sensors for environmental analysis based on fluorescence, phosphorescence and chemiluminescence signals continues to be a dynamic topic within the sensor field. This review covers the fundamentals of this type of sensors, and an update on recent works devoted to quantifying organic pollutants in environmental waters, focusing on advances since about 2005. Among the wide variety of these contaminants, special attention has been paid polycyclic aromatic hydrocarbons, pesticides, explosives and emerging organic pollutants. The potential of coupling optical sensors with multivariate calibration methods in order to improve the selectivity is also discussed. PMID:22247654

Strategies for multivariate modeling of moisture content in freeze-dried mannitol-containing products by near-infrared spectroscopy.

PubMed

Yip, Wai Lam; Gausemel, Ingvil; Sande, Sverre Arne; Dyrstad, Knut

2012-11-01

Accurate determination of residual moisture content of a freeze-dried (FD) pharmaceutical product is critical for prediction of its quality. Near-infrared (NIR) spectroscopy is a fast and non-invasive method routinely used for quantification of moisture. However, several physicochemical properties of the FD product may interfere with absorption bands related to the water content. A commonly used stabilizer and bulking agent in FD known for variation in physicochemical properties, is mannitol. To minimize this physicochemical interference, different approaches for multivariate correlation between NIR spectra of a FD product containing mannitol and the corresponding moisture content measured by Karl Fischer (KF) titration have been investigated. A novel method, MIPCR (Main and Interactions of Individual Principal Components Regression), was found to have significantly increased predictive ability of moisture content compared to a traditional PLS approach. The philosophy behind the MIPCR is that the interference from a variety of particle and morphology attributes has interactive effects on the water related absorption bands. The transformation of original wavelength variables to orthogonal scores gives a new set of variables (scores) without covariance structure, and the possibility of inclusion of interaction terms in the further modeling. The residual moisture content of the FD product investigated is in the range from 0.7% to 2.6%. The mean errors of cross validated prediction of models developed in the investigated NIR regions were reduced from a range of 24.1-27.6% for traditional PLS method to 15.7-20.5% for the MIPCR method. Improved model quality by application of MIPCR, without the need for inclusion of a large number of calibration samples, might increase the use of NIR in early phase product development, where availability of calibration samples is often limited. Copyright © 2012 Elsevier B.V. All rights reserved.

Verification of Non-Invasive Blood Glucose Measurement Method Based on Pulse Wave Signal Detected by FBG Sensor System.

PubMed

Kurasawa, Shintaro; Koyama, Shouhei; Ishizawa, Hiroaki; Fujimoto, Keisaku; Chino, Shun

2017-11-23

This paper describes and verifies a non-invasive blood glucose measurement method using a fiber Bragg grating (FBG) sensor system. The FBG sensor is installed on the radial artery, and the strain (pulse wave) that is propagated from the heartbeat is measured. The measured pulse wave signal was used as a collection of feature vectors for multivariate analysis aiming to determine the blood glucose level. The time axis of the pulse wave signal was normalized by two signal processing methods: the shortest-time-cut process and 1-s-normalization process. The measurement accuracy of the calculated blood glucose level was compared with the accuracy of these signal processing methods. It was impossible to calculate a blood glucose level exceeding 200 mg/dL in the calibration curve that was constructed by the shortest-time-cut process. In the 1-s-normalization process, the measurement accuracy of the blood glucose level was improved, and a blood glucose level exceeding 200 mg/dL could be calculated. By verifying the loading vector of each calibration curve to calculate the blood glucose level with a high measurement accuracy, we found the gradient of the peak of the pulse wave at the acceleration plethysmogram greatly affected.

[Influence of sample surface roughness on mathematical model of NIR quantitative analysis of wood density].

PubMed

Huang, An-Min; Fei, Ben-Hua; Jiang, Ze-Hui; Hse, Chung-Yun

2007-09-01

Near infrared spectroscopy is widely used as a quantitative method, and the main multivariate techniques consist of regression methods used to build prediction models, however, the accuracy of analysis results will be affected by many factors. In the present paper, the influence of different sample roughness on the mathematical model of NIR quantitative analysis of wood density was studied. The result of experiments showed that if the roughness of predicted samples was consistent with that of calibrated samples, the result was good, otherwise the error would be much higher. The roughness-mixed model was more flexible and adaptable to different sample roughness. The prediction ability of the roughness-mixed model was much better than that of the single-roughness model.

Multivariate Formation Pressure Prediction with Seismic-derived Petrophysical Properties from Prestack AVO inversion and Poststack Seismic Motion Inversion

NASA Astrophysics Data System (ADS)

Yu, H.; Gu, H.

2017-12-01

A novel multivariate seismic formation pressure prediction methodology is presented, which incorporates high-resolution seismic velocity data from prestack AVO inversion, and petrophysical data (porosity and shale volume) derived from poststack seismic motion inversion. In contrast to traditional seismic formation prediction methods, the proposed methodology is based on a multivariate pressure prediction model and utilizes a trace-by-trace multivariate regression analysis on seismic-derived petrophysical properties to calibrate model parameters in order to make accurate predictions with higher resolution in both vertical and lateral directions. With prestack time migration velocity as initial velocity model, an AVO inversion was first applied to prestack dataset to obtain high-resolution seismic velocity with higher frequency that is to be used as the velocity input for seismic pressure prediction, and the density dataset to calculate accurate Overburden Pressure (OBP). Seismic Motion Inversion (SMI) is an inversion technique based on Markov Chain Monte Carlo simulation. Both structural variability and similarity of seismic waveform are used to incorporate well log data to characterize the variability of the property to be obtained. In this research, porosity and shale volume are first interpreted on well logs, and then combined with poststack seismic data using SMI to build porosity and shale volume datasets for seismic pressure prediction. A multivariate effective stress model is used to convert velocity, porosity and shale volume datasets to effective stress. After a thorough study of the regional stratigraphic and sedimentary characteristics, a regional normally compacted interval model is built, and then the coefficients in the multivariate prediction model are determined in a trace-by-trace multivariate regression analysis on the petrophysical data. The coefficients are used to convert velocity, porosity and shale volume datasets to effective stress and then to calculate formation pressure with OBP. Application of the proposed methodology to a research area in East China Sea has proved that the method can bridge the gap between seismic and well log pressure prediction and give predicted pressure values close to pressure meassurements from well testing.

Reporting and Methodology of Multivariable Analyses in Prognostic Observational Studies Published in 4 Anesthesiology Journals: A Methodological Descriptive Review.

PubMed

Guglielminotti, Jean; Dechartres, Agnès; Mentré, France; Montravers, Philippe; Longrois, Dan; Laouénan, Cedric

2015-10-01

Prognostic research studies in anesthesiology aim to identify risk factors for an outcome (explanatory studies) or calculate the risk of this outcome on the basis of patients' risk factors (predictive studies). Multivariable models express the relationship between predictors and an outcome and are used in both explanatory and predictive studies. Model development demands a strict methodology and a clear reporting to assess its reliability. In this methodological descriptive review, we critically assessed the reporting and methodology of multivariable analysis used in observational prognostic studies published in anesthesiology journals. A systematic search was conducted on Medline through Web of Knowledge, PubMed, and journal websites to identify observational prognostic studies with multivariable analysis published in Anesthesiology, Anesthesia & Analgesia, British Journal of Anaesthesia, and Anaesthesia in 2010 and 2011. Data were extracted by 2 independent readers. First, studies were analyzed with respect to reporting of outcomes, design, size, methods of analysis, model performance (discrimination and calibration), model validation, clinical usefulness, and STROBE (i.e., Strengthening the Reporting of Observational Studies in Epidemiology) checklist. A reporting rate was calculated on the basis of 21 items of the aforementioned points. Second, they were analyzed with respect to some predefined methodological points. Eighty-six studies were included: 87.2% were explanatory and 80.2% investigated a postoperative event. The reporting was fairly good, with a median reporting rate of 79% (75% in explanatory studies and 100% in predictive studies). Six items had a reporting rate <36% (i.e., the 25th percentile), with some of them not identified in the STROBE checklist: blinded evaluation of the outcome (11.9%), reason for sample size (15.1%), handling of missing data (36.0%), assessment of colinearity (17.4%), assessment of interactions (13.9%), and calibration (34.9%). When reported, a few methodological shortcomings were observed, both in explanatory and predictive studies, such as an insufficient number of events of the outcome (44.6%), exclusion of cases with missing data (93.6%), or categorization of continuous variables (65.1%.). The reporting of multivariable analysis was fairly good and could be further improved by checking reporting guidelines and EQUATOR Network website. Limiting the number of candidate variables, including cases with missing data, and not arbitrarily categorizing continuous variables should be encouraged.

FT-IR-cPAS—New Photoacoustic Measurement Technique for Analysis of Hot Gases: A Case Study on VOCs

PubMed Central

Hirschmann, Christian Bernd; Koivikko, Niina Susanna; Raittila, Jussi; Tenhunen, Jussi; Ojala, Satu; Rahkamaa-Tolonen, Katariina; Marbach, Ralf; Hirschmann, Sarah; Keiski, Riitta Liisa

2011-01-01

This article describes a new photoacoustic FT-IR system capable of operating at elevated temperatures. The key hardware component is an optical-readout cantilever microphone that can work up to 200 °C. All parts in contact with the sample gas were put into a heated oven, incl. the photoacoustic cell. The sensitivity of the built photoacoustic system was tested by measuring 18 different VOCs. At 100 ppm gas concentration, the univariate signal to noise ratios (1σ, measurement time 25.5 min, at highest peak, optical resolution 8 cm−1) of the spectra varied from minimally 19 for o-xylene up to 329 for butyl acetate. The sensitivity can be improved by multivariate analyses over broad wavelength ranges, which effectively co-adds the univariate sensitivities achievable at individual wavelengths. The multivariate limit of detection (3σ, 8.5 min, full useful wavelength range), i.e., the best possible inverse analytical sensitivity achievable at optimum calibration, was calculated using the SBC method and varied from 2.60 ppm for dichloromethane to 0.33 ppm for butyl acetate. Depending on the shape of the spectra, which often only contain a few sharp peaks, the multivariate analysis improved the analytical sensitivity by 2.2 to 9.2 times compared to the univariate case. Selectivity and multi component ability were tested by a SBC calibration including 5 VOCs and water. The average cross selectivities turned out to be less than 2% and the resulting inverse analytical sensitivities of the 5 interfering VOCs was increased by maximum factor of 2.2 compared to the single component sensitivities. Water subtraction using SBC gave the true analyte concentration with a variation coefficient of 3%, although the sample spectra (methyl ethyl ketone, 200 ppm) contained water from 1,400 to 100k ppm and for subtraction only one water spectra (10k ppm) was used. The developed device shows significant improvement to the current state-of-the-art measurement methods used in industrial VOC measurements. PMID:22163900

Near Infrared Spectroscopy Detection and Quantification of Herbal Medicines Adulterated with Sibutramine.

PubMed

da Silva, Neirivaldo Cavalcante; Honorato, Ricardo Saldanha; Pimentel, Maria Fernanda; Garrigues, Salvador; Cervera, Maria Luisa; de la Guardia, Miguel

2015-09-01

There is an increasing demand for herbal medicines in weight loss treatment. Some synthetic chemicals, such as sibutramine (SB), have been detected as adulterants in herbal formulations. In this study, two strategies using near infrared (NIR) spectroscopy have been developed to evaluate potential adulteration of herbal medicines with SB: a qualitative screening approach and a quantitative methodology based on multivariate calibration. Samples were composed by products commercialized as herbal medicines, as well as by laboratory adulterated samples. Spectra were obtained in the range of 14,000-4000 per cm. Using PLS-DA, a correct classification of 100% was achieved for the external validation set. In the quantitative approach, the root mean squares error of prediction (RMSEP), for both PLS and MLR models, was 0.2% w/w. The results prove the potential of NIR spectroscopy and multivariate calibration in quantifying sibutramine in adulterated herbal medicines samples. © 2015 American Academy of Forensic Sciences.

Improving the accuracy of hyaluronic acid molecular weight estimation by conventional size exclusion chromatography.

PubMed

Shanmuga Doss, Sreeja; Bhatt, Nirav Pravinbhai; Jayaraman, Guhan

2017-08-15

There is an unreasonably high variation in the literature reports on molecular weight of hyaluronic acid (HA) estimated using conventional size exclusion chromatography (SEC). This variation is most likely due to errors in estimation. Working with commercially available HA molecular weight standards, this work examines the extent of error in molecular weight estimation due to two factors: use of non-HA based calibration and concentration of sample injected into the SEC column. We develop a multivariate regression correlation to correct for concentration effect. Our analysis showed that, SEC calibration based on non-HA standards like polyethylene oxide and pullulan led to approximately 2 and 10 times overestimation, respectively, when compared to HA-based calibration. Further, we found that injected sample concentration has an effect on molecular weight estimation. Even at 1g/l injected sample concentration, HA molecular weight standards of 0.7 and 1.64MDa showed appreciable underestimation of 11-24%. The multivariate correlation developed was found to reduce error in estimations at 1g/l to <4%. The correlation was also successfully applied to accurately estimate the molecular weight of HA produced by a recombinant Lactococcus lactis fermentation. Copyright © 2017 Elsevier B.V. All rights reserved.

Sample classification for improved performance of PLS models applied to the quality control of deep-frying oils of different botanic origins analyzed using ATR-FTIR spectroscopy.

PubMed

Kuligowski, Julia; Carrión, David; Quintás, Guillermo; Garrigues, Salvador; de la Guardia, Miguel

2011-01-01

The selection of an appropriate calibration set is a critical step in multivariate method development. In this work, the effect of using different calibration sets, based on a previous classification of unknown samples, on the partial least squares (PLS) regression model performance has been discussed. As an example, attenuated total reflection (ATR) mid-infrared spectra of deep-fried vegetable oil samples from three botanical origins (olive, sunflower, and corn oil), with increasing polymerized triacylglyceride (PTG) content induced by a deep-frying process were employed. The use of a one-class-classifier partial least squares-discriminant analysis (PLS-DA) and a rooted binary directed acyclic graph tree provided accurate oil classification. Oil samples fried without foodstuff could be classified correctly, independent of their PTG content. However, class separation of oil samples fried with foodstuff, was less evident. The combined use of double-cross model validation with permutation testing was used to validate the obtained PLS-DA classification models, confirming the results. To discuss the usefulness of the selection of an appropriate PLS calibration set, the PTG content was determined by calculating a PLS model based on the previously selected classes. In comparison to a PLS model calculated using a pooled calibration set containing samples from all classes, the root mean square error of prediction could be improved significantly using PLS models based on the selected calibration sets using PLS-DA, ranging between 1.06 and 2.91% (w/w).

ATR-FTIR membrane-based sensor for the simultaneous determination of surfactant and oil total indices in industrial degreasing baths.

PubMed

Lucena, Rafael; Cárdenas, Soledad; Gallego, Mercedes; Valcárcel, Miguel

2006-03-01

Monitoring the exhaustion of alkaline degreasing baths is one of the main aspects in metal mechanizing industrial process control. The global level of surfactant, and mainly grease, can be used as ageing indicators. In this paper, an attenuated total reflection-Fourier transform infrared (ATR-FTIR) membrane-based sensor is presented for the determination of these parameters. The system is based on a micro-liquid-liquid extraction of the analytes through a polymeric membrane from the aqueous to the organic solvent layer which is in close contact with the internal reflection element and continuously monitored. Samples are automatically processed using a simple, robust sequential injection analysis (SIA) configuration, on-line coupled to the instrument. The global signal obtained for both families of compounds are processed via a multivariate calibration technique (partial least squares, PLS). Excellent correlation was obtained for the values given by the proposed method compared to those of the gravimetric reference one with very low error values for both calibration and validation.

Quantitative analysis of Sudan dye adulteration in paprika powder using FTIR spectroscopy.

PubMed

Lohumi, Santosh; Joshi, Ritu; Kandpal, Lalit Mohan; Lee, Hoonsoo; Kim, Moon S; Cho, Hyunjeong; Mo, Changyeun; Seo, Young-Wook; Rahman, Anisur; Cho, Byoung-Kwan

2017-05-01

As adulteration of foodstuffs with Sudan dye, especially paprika- and chilli-containing products, has been reported with some frequency, this issue has become one focal point for addressing food safety. FTIR spectroscopy has been used extensively as an analytical method for quality control and safety determination for food products. Thus, the use of FTIR spectroscopy for rapid determination of Sudan dye in paprika powder was investigated in this study. A net analyte signal (NAS)-based methodology, named HLA/GO (hybrid linear analysis in the literature), was applied to FTIR spectral data to predict Sudan dye concentration. The calibration and validation sets were designed to evaluate the performance of the multivariate method. The obtained results had a high determination coefficient (R 2 ) of 0.98 and low root mean square error (RMSE) of 0.026% for the calibration set, and an R 2 of 0.97 and RMSE of 0.05% for the validation set. The model was further validated using a second validation set and through the figures of merit, such as sensitivity, selectivity, and limits of detection and quantification. The proposed technique of FTIR combined with HLA/GO is rapid, simple and low cost, making this approach advantageous when compared with the main alternative methods based on liquid chromatography (LC) techniques.

Improved quantification of important beer quality parameters based on nonlinear calibration methods applied to FT-MIR spectra.

PubMed

Cernuda, Carlos; Lughofer, Edwin; Klein, Helmut; Forster, Clemens; Pawliczek, Marcin; Brandstetter, Markus

2017-01-01

During the production process of beer, it is of utmost importance to guarantee a high consistency of the beer quality. For instance, the bitterness is an essential quality parameter which has to be controlled within the specifications at the beginning of the production process in the unfermented beer (wort) as well as in final products such as beer and beer mix beverages. Nowadays, analytical techniques for quality control in beer production are mainly based on manual supervision, i.e., samples are taken from the process and analyzed in the laboratory. This typically requires significant lab technicians efforts for only a small fraction of samples to be analyzed, which leads to significant costs for beer breweries and companies. Fourier transform mid-infrared (FT-MIR) spectroscopy was used in combination with nonlinear multivariate calibration techniques to overcome (i) the time consuming off-line analyses in beer production and (ii) already known limitations of standard linear chemometric methods, like partial least squares (PLS), for important quality parameters Speers et al. (J I Brewing. 2003;109(3):229-235), Zhang et al. (J I Brewing. 2012;118(4):361-367) such as bitterness, citric acid, total acids, free amino nitrogen, final attenuation, or foam stability. The calibration models are established with enhanced nonlinear techniques based (i) on a new piece-wise linear version of PLS by employing fuzzy rules for local partitioning the latent variable space and (ii) on extensions of support vector regression variants (-PLSSVR and ν-PLSSVR), for overcoming high computation times in high-dimensional problems and time-intensive and inappropriate settings of the kernel parameters. Furthermore, we introduce a new model selection scheme based on bagged ensembles in order to improve robustness and thus predictive quality of the final models. The approaches are tested on real-world calibration data sets for wort and beer mix beverages, and successfully compared to linear methods, showing a clear out-performance in most cases and being able to meet the model quality requirements defined by the experts at the beer company. Figure Workflow for calibration of non-Linear model ensembles from FT-MIR spectra in beer production .

Origin Discrimination of Osmanthus fragrans var. thunbergii Flowers using GC-MS and UPLC-PDA Combined with Multivariable Analysis Methods.

PubMed

Zhou, Fei; Zhao, Yajing; Peng, Jiyu; Jiang, Yirong; Li, Maiquan; Jiang, Yuan; Lu, Baiyi

2017-07-01

Osmanthus fragrans flowers are used as folk medicine and additives for teas, beverages and foods. The metabolites of O. fragrans flowers from different geographical origins were inconsistent in some extent. Chromatography and mass spectrometry combined with multivariable analysis methods provides an approach for discriminating the origin of O. fragrans flowers. To discriminate the Osmanthus fragrans var. thunbergii flowers from different origins with the identified metabolites. GC-MS and UPLC-PDA were conducted to analyse the metabolites in O. fragrans var. thunbergii flowers (in total 150 samples). Principal component analysis (PCA), soft independent modelling of class analogy analysis (SIMCA) and random forest (RF) analysis were applied to group the GC-MS and UPLC-PDA data. GC-MS identified 32 compounds common to all samples while UPLC-PDA/QTOF-MS identified 16 common compounds. PCA of the UPLC-PDA data generated a better clustering than PCA of the GC-MS data. Ten metabolites (six from GC-MS and four from UPLC-PDA) were selected as effective compounds for discrimination by PCA loadings. SIMCA and RF analysis were used to build classification models, and the RF model, based on the four effective compounds (caffeic acid derivative, acteoside, ligustroside and compound 15), yielded better results with the classification rate of 100% in the calibration set and 97.8% in the prediction set. GC-MS and UPLC-PDA combined with multivariable analysis methods can discriminate the origin of Osmanthus fragrans var. thunbergii flowers. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Discrimination of Gastrodia elata from Different Geographical Origin for Quality Evaluation Using Newly-Build Near Infrared Spectrum Coupled with Multivariate Analysis.

PubMed

Zuo, Yamin; Deng, Xuehua; Wu, Qing

2018-05-04

Discrimination of Gastrodia elata ( G. elata ) geographical origin is of great importance to pharmaceutical companies and consumers in China. this paper focuses on the feasibility of near infrared spectrum (NIRS) combined multivariate analysis as a rapid and non-destructive method to prove its fit for this purpose. Firstly, 16 batches of G. elata samples from four main-cultivation regions in China were quantified by traditional HPLC method. It showed that samples from different origins could not be efficiently differentiated by the contents of four phenolic compounds in this study. Secondly, the raw near infrared (NIR) spectra of those samples were acquired and two different pattern recognition techniques were used to classify the geographical origins. The results showed that with spectral transformation optimized, discriminant analysis (DA) provided 97% and 99% correct classification for the calibration and validation sets of samples from discriminating of four different main-cultivation regions, and provided 98% and 99% correct classifications for the calibration and validation sets of samples from eight different cities, respectively, which all performed better than the principal component analysis (PCA) method. Thirdly, as phenolic compounds content (PCC) is highly related with the quality of G. elata , synergy interval partial least squares (Si-PLS) was applied to build the PCC prediction model. The coefficient of determination for prediction (R p ²) of the Si-PLS model was 0.9209, and root mean square error for prediction (RMSEP) was 0.338. The two regions (4800 cm −1 ⁻5200 cm −1 , and 5600 cm −1 ⁻6000 cm −1 ) selected by Si-PLS corresponded to the absorptions of aromatic ring in the basic phenolic structure. It can be concluded that NIR spectroscopy combined with PCA, DA and Si-PLS would be a potential tool to provide a reference for the quality control of G. elata.

Strain Gauge Balance Uncertainty Analysis at NASA Langley: A Technical Review

NASA Technical Reports Server (NTRS)

Tripp, John S.

1999-01-01

This paper describes a method to determine the uncertainties of measured forces and moments from multi-component force balances used in wind tunnel tests. A multivariate regression technique is first employed to estimate the uncertainties of the six balance sensitivities and 156 interaction coefficients derived from established balance calibration procedures. These uncertainties are then employed to calculate the uncertainties of force-moment values computed from observed balance output readings obtained during tests. Confidence and prediction intervals are obtained for each computed force and moment as functions of the actual measurands. Techniques are discussed for separate estimation of balance bias and precision uncertainties.

Advanced spectrophotometric chemometric methods for resolving the binary mixture of doxylamine succinate and pyridoxine hydrochloride.

PubMed

Katsarov, Plamen; Gergov, Georgi; Alin, Aylin; Pilicheva, Bissera; Al-Degs, Yahya; Simeonov, Vasil; Kassarova, Margarita

2018-03-01

The prediction power of partial least squares (PLS) and multivariate curve resolution-alternating least squares (MCR-ALS) methods have been studied for simultaneous quantitative analysis of the binary drug combination - doxylamine succinate and pyridoxine hydrochloride. Analysis of first-order UV overlapped spectra was performed using different PLS models - classical PLS1 and PLS2 as well as partial robust M-regression (PRM). These linear models were compared to MCR-ALS with equality and correlation constraints (MCR-ALS-CC). All techniques operated within the full spectral region and extracted maximum information for the drugs analysed. The developed chemometric methods were validated on external sample sets and were applied to the analyses of pharmaceutical formulations. The obtained statistical parameters were satisfactory for calibration and validation sets. All developed methods can be successfully applied for simultaneous spectrophotometric determination of doxylamine and pyridoxine both in laboratory-prepared mixtures and commercial dosage forms.

Fourier transform infrared spectroscopy for Kona coffee authentication.

PubMed

Wang, Jun; Jun, Soojin; Bittenbender, H C; Gautz, Loren; Li, Qing X

2009-06-01

Kona coffee, the variety of "Kona typica" grown in the north and south districts of Kona-Island, carries a unique stamp of the region of Big Island of Hawaii, U.S.A. The excellent quality of Kona coffee makes it among the best coffee products in the world. Fourier transform infrared (FTIR) spectroscopy integrated with an attenuated total reflectance (ATR) accessory and multivariate analysis was used for qualitative and quantitative analysis of ground and brewed Kona coffee and blends made with Kona coffee. The calibration set of Kona coffee consisted of 10 different blends of Kona-grown original coffee mixture from 14 different farms in Hawaii and a non-Kona-grown original coffee mixture from 3 different sampling sites in Hawaii. Derivative transformations (1st and 2nd), mathematical enhancements such as mean centering and variance scaling, multivariate regressions by partial least square (PLS), and principal components regression (PCR) were implemented to develop and enhance the calibration model. The calibration model was successfully validated using 9 synthetic blend sets of 100% Kona coffee mixture and its adulterant, 100% non-Kona coffee mixture. There were distinct peak variations of ground and brewed coffee blends in the spectral "fingerprint" region between 800 and 1900 cm(-1). The PLS-2nd derivative calibration model based on brewed Kona coffee with mean centering data processing showed the highest degree of accuracy with the lowest standard error of calibration value of 0.81 and the highest R(2) value of 0.999. The model was further validated by quantitative analysis of commercial Kona coffee blends. Results demonstrate that FTIR can be a rapid alternative to authenticate Kona coffee, which only needs very quick and simple sample preparations.

An attempt at predicting blood β-hydroxybutyrate from Fourier-transform mid-infrared spectra of milk using multivariate mixed models in Polish dairy cattle.

PubMed

Belay, T K; Dagnachew, B S; Kowalski, Z M; Ådnøy, T

2017-08-01

Fourier transform mid-infrared (FT-MIR) spectra of milk are commonly used for phenotyping of traits of interest through links developed between the traits and milk FT-MIR spectra. Predicted traits are then used in genetic analysis for ultimate phenotypic prediction using a single-trait mixed model that account for cows' circumstances at a given test day. Here, this approach is referred to as indirect prediction (IP). Alternatively, FT-MIR spectral variable can be kept multivariate in the form of factor scores in REML and BLUP analyses. These BLUP predictions, including phenotype (predicted factor scores), were converted to single-trait through calibration outputs; this method is referred to as direct prediction (DP). The main aim of this study was to verify whether mixed modeling of milk spectra in the form of factors scores (DP) gives better prediction of blood β-hydroxybutyrate (BHB) than the univariate approach (IP). Models to predict blood BHB from milk spectra were also developed. Two data sets that contained milk FT-MIR spectra and other information on Polish dairy cattle were used in this study. Data set 1 (n = 826) also contained BHB measured in blood samples, whereas data set 2 (n = 158,028) did not contain measured blood values. Part of data set 1 was used to calibrate a prediction model (n = 496) and the remaining part of data set 1 (n = 330) was used to validate the calibration models, as well as to evaluate the DP and IP approaches. Dimensions of FT-MIR spectra in data set 2 were reduced either into 5 or 10 factor scores (DP) or into a single trait (IP) with calibration outputs. The REML estimates for these factor scores were found using WOMBAT. The BLUP values and predicted BHB for observations in the validation set were computed using the REML estimates. Blood BHB predicted from milk FT-MIR spectra by both approaches were regressed on reference blood BHB that had not been used in the model development. Coefficients of determination in cross-validation for untransformed blood BHB were from 0.21 to 0.32, whereas that for the log-transformed BHB were from 0.31 to 0.38. The corresponding estimates in validation were from 0.29 to 0.37 and 0.21 to 0.43, respectively, for untransformed and logarithmic BHB. Contrary to expectation, slightly better predictions of BHB were found when univariate variance structure was used (IP) than when multivariate covariance structures were used (DP). Conclusive remarks on the importance of keeping spectral data in multivariate form for prediction of phenotypes may be found in data sets where the trait of interest has strong relationships with spectral variables. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

The RAMANITA © method for non-destructive and in situ semi-quantitative chemical analysis of mineral solid-solutions by multidimensional calibration of Raman wavenumber shifts

NASA Astrophysics Data System (ADS)

Smith, David C.

2005-08-01

The "RAMANITA ©" method, for semi-quantitative chemical analysis of mineral solid-solutions by multidimensional calibration of Raman wavenumber shifts and mathematical calculation by simultaneous equations, is published here in detail in English for the first time. It was conceived by the present writer 20 years ago for binary and ternary pyroxene and garnet systems. The mathematical description was set out in 1989, but in an abstract in an obscure French special publication. Detailed "step-by-step" calibration of two garnet ternaries, followed by their linking, by M. Pinet and D.C. Smith in the early 1990s provided a hexary garnet database. Much later, using this garnet database, which forms part of his personal database called RAMANITA ©, the present writer began to develop the method by improving the terminology, automating the calculations, discussing problems and experimenting with different real chemical problems in archaeometry. Although this RAMANITA © method has been very briefly mentioned in two recent books, the necessary full mathematical explanation is given only here. The method will find application in any study which requires obtaining a non-destructive semi-quantitative chemical analysis from mineral solid solutions that cannot be analysed by any destructive analytical method, in particular for archaeological, geological or extraterrestrial research projects, e.g. from gemstones or other crystalline artworks of the cultural heritage (especially by Mobile Raman Microscopy (MRM)) in situ in museums or at archaeological sites, including under water for subaquatic archaeometry; from scientifically precious mineral microinclusions (such as garnet or pyroxene within diamond); from minerals in rocks analysed in situ on planetary bodies by a rover (especially "at distance" by telescopy). Recently some other workers have begun deducing chemical compositions from Raman wavenumber shifts in multivariate chemical space, but the philosophical approach is quite different.

Linking multimetric and multivariate approaches to assess the ecological condition of streams.

PubMed

Collier, Kevin J

2009-10-01

Few attempts have been made to combine multimetric and multivariate analyses for bioassessment despite recognition that an integrated method could yield powerful tools for bioassessment. An approach is described that integrates eight macroinvertebrate community metrics into a Principal Components Analysis to develop a Multivariate Condition Score (MCS) from a calibration dataset of 511 samples. The MCS is compared to an Index of Biotic Integrity (IBI) derived using the same metrics based on the ratio to the reference site mean. Both approaches were highly correlated although the MCS appeared to offer greater potential for discriminating a wider range of impaired conditions. Both the MCS and IBI displayed low temporal variability within reference sites, and were able to distinguish between reference conditions and low levels of catchment modification and local habitat degradation, although neither discriminated among three levels of low impact. Pseudosamples developed to test the response of the metric aggregation approaches to organic enrichment, urban, mining, pastoral and logging stressor scenarios ranked pressures in the same order, but the MCS provided a lower score for the urban scenario and a higher score for the pastoral scenario. The MCS was calculated for an independent test dataset of urban and reference sites, and yielded similar results to the IBI. Although both methods performed comparably, the MCS approach may have some advantages because it removes the subjectivity of assigning thresholds for scoring biological condition, and it appears to discriminate a wider range of degraded conditions.

Quality control for quantitative PCR based on amplification compatibility test.

PubMed

Tichopad, Ales; Bar, Tzachi; Pecen, Ladislav; Kitchen, Robert R; Kubista, Mikael; Pfaffl, Michael W

2010-04-01

Quantitative qPCR is a routinely used method for the accurate quantification of nucleic acids. Yet it may generate erroneous results if the amplification process is obscured by inhibition or generation of aberrant side-products such as primer dimers. Several methods have been established to control for pre-processing performance that rely on the introduction of a co-amplified reference sequence, however there is currently no method to allow for reliable control of the amplification process without directly modifying the sample mix. Herein we present a statistical approach based on multivariate analysis of the amplification response data generated in real-time. The amplification trajectory in its most resolved and dynamic phase is fitted with a suitable model. Two parameters of this model, related to amplification efficiency, are then used for calculation of the Z-score statistics. Each studied sample is compared to a predefined reference set of reactions, typically calibration reactions. A probabilistic decision for each individual Z-score is then used to identify the majority of inhibited reactions in our experiments. We compare this approach to univariate methods using only the sample specific amplification efficiency as reporter of the compatibility. We demonstrate improved identification performance using the multivariate approach compared to the univariate approach. Finally we stress that the performance of the amplification compatibility test as a quality control procedure depends on the quality of the reference set. Copyright 2010 Elsevier Inc. All rights reserved.

Simultaneous calibration of ensemble river flow predictions over an entire range of lead times

NASA Astrophysics Data System (ADS)

Hemri, S.; Fundel, F.; Zappa, M.

2013-10-01

Probabilistic estimates of future water levels and river discharge are usually simulated with hydrologic models using ensemble weather forecasts as main inputs. As hydrologic models are imperfect and the meteorological ensembles tend to be biased and underdispersed, the ensemble forecasts for river runoff typically are biased and underdispersed, too. Thus, in order to achieve both reliable and sharp predictions statistical postprocessing is required. In this work Bayesian model averaging (BMA) is applied to statistically postprocess ensemble runoff raw forecasts for a catchment in Switzerland, at lead times ranging from 1 to 240 h. The raw forecasts have been obtained using deterministic and ensemble forcing meteorological models with different forecast lead time ranges. First, BMA is applied based on mixtures of univariate normal distributions, subject to the assumption of independence between distinct lead times. Then, the independence assumption is relaxed in order to estimate multivariate runoff forecasts over the entire range of lead times simultaneously, based on a BMA version that uses multivariate normal distributions. Since river runoff is a highly skewed variable, Box-Cox transformations are applied in order to achieve approximate normality. Both univariate and multivariate BMA approaches are able to generate well calibrated probabilistic forecasts that are considerably sharper than climatological forecasts. Additionally, multivariate BMA provides a promising approach for incorporating temporal dependencies into the postprocessed forecasts. Its major advantage against univariate BMA is an increase in reliability when the forecast system is changing due to model availability.

Noninvasive and fast measurement of blood glucose in vivo by near infrared (NIR) spectroscopy

NASA Astrophysics Data System (ADS)

Jintao, Xue; Liming, Ye; Yufei, Liu; Chunyan, Li; Han, Chen

2017-05-01

This research was to develop a method for noninvasive and fast blood glucose assay in vivo. Near-infrared (NIR) spectroscopy, a more promising technique compared to other methods, was investigated in rats with diabetes and normal rats. Calibration models are generated by two different multivariate strategies: partial least squares (PLS) as linear regression method and artificial neural networks (ANN) as non-linear regression method. The PLS model was optimized individually by considering spectral range, spectral pretreatment methods and number of model factors, while the ANN model was studied individually by selecting spectral pretreatment methods, parameters of network topology, number of hidden neurons, and times of epoch. The results of the validation showed the two models were robust, accurate and repeatable. Compared to the ANN model, the performance of the PLS model was much better, with lower root mean square error of validation (RMSEP) of 0.419 and higher correlation coefficients (R) of 96.22%.

A rapid field test for the measurement of bovine serum immunoglobulin G using attenuated total reflectance infrared spectroscopy.

PubMed

Elsohaby, Ibrahim; Hou, Siyuan; McClure, J Trenton; Riley, Christopher B; Shaw, R Anthony; Keefe, Gregory P

2015-08-20

Following the recent development of a new approach to quantitative analysis of IgG concentrations in bovine serum using transmission infrared spectroscopy, the potential to measure IgG levels using technology and a device better designed for field use was investigated. A method using attenuated total reflectance infrared (ATR) spectroscopy in combination with partial least squares (PLS) regression was developed to measure bovine serum IgG concentrations. ATR spectroscopy has a distinct ease-of-use advantage that may open the door to routine point-of-care testing. Serum samples were collected from calves and adult cows, tested by a reference RID method, and ATR spectra acquired. The spectra were linked to the RID-IgG concentrations and then randomly split into two sets: calibration and prediction. The calibration set was used to build a calibration model, while the prediction set was used to assess the predictive performance and accuracy of the final model. The procedure was repeated for various spectral data preprocessing approaches. For the prediction set, the Pearson's and concordance correlation coefficients between the IgG measured by RID and predicted by ATR spectroscopy were both 0.93. The Bland Altman plot revealed no obvious systematic bias between the two methods. ATR spectroscopy showed a sensitivity for detection of failure of transfer of passive immunity (FTPI) of 88 %, specificity of 100 % and accuracy of 94 % (with IgG <1000 mg/dL as the FTPI cut-off value). ATR spectroscopy in combination with multivariate data analysis shows potential as an alternative approach for rapid quantification of IgG concentrations in bovine serum and the diagnosis of FTPI in calves.

New NIR Calibration Models Speed Biomass Composition and Reactivity Characterization

DOE Office of Scientific and Technical Information (OSTI.GOV)

2015-09-01

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. This highlight describes NREL's work to use near-infrared (NIR) spectroscopy and partial least squares multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. This highlight is being developed for the September 2015 Alliance S&T Board meeting.

Analysis of Multivariate Experimental Data Using A Simplified Regression Model Search Algorithm

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert M.

2013-01-01

A new regression model search algorithm was developed that may be applied to both general multivariate experimental data sets and wind tunnel strain-gage balance calibration data. The algorithm is a simplified version of a more complex algorithm that was originally developed for the NASA Ames Balance Calibration Laboratory. The new algorithm performs regression model term reduction to prevent overfitting of data. It has the advantage that it needs only about one tenth of the original algorithm's CPU time for the completion of a regression model search. In addition, extensive testing showed that the prediction accuracy of math models obtained from the simplified algorithm is similar to the prediction accuracy of math models obtained from the original algorithm. The simplified algorithm, however, cannot guarantee that search constraints related to a set of statistical quality requirements are always satisfied in the optimized regression model. Therefore, the simplified algorithm is not intended to replace the original algorithm. Instead, it may be used to generate an alternate optimized regression model of experimental data whenever the application of the original search algorithm fails or requires too much CPU time. Data from a machine calibration of NASA's MK40 force balance is used to illustrate the application of the new search algorithm.

Analysis of Multivariate Experimental Data Using A Simplified Regression Model Search Algorithm

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred

2013-01-01

A new regression model search algorithm was developed in 2011 that may be used to analyze both general multivariate experimental data sets and wind tunnel strain-gage balance calibration data. The new algorithm is a simplified version of a more complex search algorithm that was originally developed at the NASA Ames Balance Calibration Laboratory. The new algorithm has the advantage that it needs only about one tenth of the original algorithm's CPU time for the completion of a search. In addition, extensive testing showed that the prediction accuracy of math models obtained from the simplified algorithm is similar to the prediction accuracy of math models obtained from the original algorithm. The simplified algorithm, however, cannot guarantee that search constraints related to a set of statistical quality requirements are always satisfied in the optimized regression models. Therefore, the simplified search algorithm is not intended to replace the original search algorithm. Instead, it may be used to generate an alternate optimized regression model of experimental data whenever the application of the original search algorithm either fails or requires too much CPU time. Data from a machine calibration of NASA's MK40 force balance is used to illustrate the application of the new regression model search algorithm.

The critical role of NIR spectroscopy and statistical process control (SPC) strategy towards captopril tablets (25 mg) manufacturing process understanding: a case study.

PubMed

Curtivo, Cátia Panizzon Dal; Funghi, Nathália Bitencourt; Tavares, Guilherme Diniz; Barbosa, Sávio Fujita; Löbenberg, Raimar; Bou-Chacra, Nádia Araci

2015-05-01

In this work, near-infrared spectroscopy (NIRS) method was used to evaluate the uniformity of dosage units of three captopril 25 mg tablets commercial batches. The performance of the calibration method was assessed by determination of Q value (0.9986), standard error of estimation (C-set SEE = 1.956), standard error of prediction (V-set SEP = 2.076) as well as the consistency (106.1%). These results indicated the adequacy of the selected model. The method validation revealed the agreement of the reference high pressure liquid chromatography (HPLC) and NIRS methods. The process evaluation using the NIRS method showed that the variability was due to common causes and delivered predictable results consistently. Cp and Cpk values were, respectively, 2.05 and 1.80. These results revealed a non-centered process in relation to the average target (100% w/w), in the specified range (85-115%). The probability of failure was 21:100 million tablets of captopril. The NIRS in combination with the method of multivariate calibration, partial least squares (PLS) regression, allowed the development of methodology for the uniformity of dosage units evaluation of captopril tablets 25 mg. The statistical process control strategy associated with NIRS method as PAT played a critical role in understanding of the sources and degree of variation and its impact on the process. This approach led towards a better process understanding and provided the sound scientific basis for its continuous improvement.

Quantitative nuclear magnetic resonance for additives determination in an electrolytic nickel bath.

PubMed

Ostra, Miren; Ubide, Carlos; Vidal, Maider

2011-02-01

The use of proton nuclear magnetic resonance (¹H-NMR) for the quantitation of additives in a commercial electrolytic nickel bath (Supreme Plus Brilliant, Atotech formulation) is reported. A simple and quick method is described that needs only the separation of nickel ions by precipitation with NaOH. The four additives in the bath (A-5(2X), leveler; Supreme Plus Brightener (SPB); SA-1, leveler; NPA, wetting agent; all of them are commercial names from Atotech) can be quantified, whereas no other analytical methods have been found in the literature for SA-1 and NPA. Two calibration methods have been tried: integration of NMR signals with the use of a proper internal standard and partial least squares regression applied to the characteristic NMR peaks. The multivariate method was preferred because of accuracy and precision. Multivariate limits of detection of about 4 mL L⁻¹ A-5(2X), 0.4 mL L⁻¹ SPB, 0.2 mL L⁻¹ SA-1 and 0.6 mL L⁻¹ NPA were found. The dynamic ranges are suitable to follow the concentration of additives in the bath along electrodeposition. ¹H-NMR spectra provide evidence for SPB and SA-1 consumption (A-5(2X) and NPA keep unchanged along the process) and the growth of some products from SA-1 degradation can be followed. The method can, probably, be extended to other electrolytic nickel baths.

Development of a multivariate calibration model for the determination of dry extract content in Brazilian commercial bee propolis extracts through UV-Vis spectroscopy

NASA Astrophysics Data System (ADS)

Barbeira, Paulo J. S.; Paganotti, Rosilene S. N.; Ássimos, Ariane A.

2013-10-01

This study had the objective of determining the content of dry extract of commercial alcoholic extracts of bee propolis through Partial Least Squares (PLS) multivariate calibration and electronic spectroscopy. The PLS model provided a good prediction of dry extract content in commercial alcoholic extracts of bee propolis in the range of 2.7 a 16.8% (m/v), presenting the advantage of being less laborious and faster than the traditional gravimetric methodology. The PLS model was optimized with outlier detection tests according to the ASTM E 1655-05. In this study it was possible to verify that a centrifugation stage is extremely important in order to avoid the presence of waxes, resulting in a more accurate model. Around 50% of the analyzed samples presented content of dry extract lower than the value established by Brazilian legislation, in most cases, the values found were different from the values claimed in the product's label.

Methodological challenges to multivariate syndromic surveillance: a case study using Swiss animal health data.

PubMed

Vial, Flavie; Wei, Wei; Held, Leonhard

2016-12-20

In an era of ubiquitous electronic collection of animal health data, multivariate surveillance systems (which concurrently monitor several data streams) should have a greater probability of detecting disease events than univariate systems. However, despite their limitations, univariate aberration detection algorithms are used in most active syndromic surveillance (SyS) systems because of their ease of application and interpretation. On the other hand, a stochastic modelling-based approach to multivariate surveillance offers more flexibility, allowing for the retention of historical outbreaks, for overdispersion and for non-stationarity. While such methods are not new, they are yet to be applied to animal health surveillance data. We applied an example of such stochastic model, Held and colleagues' two-component model, to two multivariate animal health datasets from Switzerland. In our first application, multivariate time series of the number of laboratories test requests were derived from Swiss animal diagnostic laboratories. We compare the performance of the two-component model to parallel monitoring using an improved Farrington algorithm and found both methods yield a satisfactorily low false alarm rate. However, the calibration test of the two-component model on the one-step ahead predictions proved satisfactory, making such an approach suitable for outbreak prediction. In our second application, the two-component model was applied to the multivariate time series of the number of cattle abortions and the number of test requests for bovine viral diarrhea (a disease that often results in abortions). We found that there is a two days lagged effect from the number of abortions to the number of test requests. We further compared the joint modelling and univariate modelling of the number of laboratory test requests time series. The joint modelling approach showed evidence of superiority in terms of forecasting abilities. Stochastic modelling approaches offer the potential to address more realistic surveillance scenarios through, for example, the inclusion of times series specific parameters, or of covariates known to have an impact on syndrome counts. Nevertheless, many methodological challenges to multivariate surveillance of animal SyS data still remain. Deciding on the amount of corroboration among data streams that is required to escalate into an alert is not a trivial task given the sparse data on the events under consideration (e.g. disease outbreaks).

Novel pure component contribution, mean centering of ratio spectra and factor based algorithms for simultaneous resolution and quantification of overlapped spectral signals: An application to recently co-formulated tablets of chlorzoxazone, aceclofenac and paracetamol

NASA Astrophysics Data System (ADS)

Toubar, Safaa S.; Hegazy, Maha A.; Elshahed, Mona S.; Helmy, Marwa I.

2016-06-01

In this work, resolution and quantitation of spectral signals are achieved by several univariate and multivariate techniques. The novel pure component contribution algorithm (PCCA) along with mean centering of ratio spectra (MCR) and the factor based partial least squares (PLS) algorithms were developed for simultaneous determination of chlorzoxazone (CXZ), aceclofenac (ACF) and paracetamol (PAR) in their pure form and recently co-formulated tablets. The PCCA method allows the determination of each drug at its λmax. While, the mean centered values at 230, 302 and 253 nm, were used for quantification of CXZ, ACF and PAR, respectively, by MCR method. Partial least-squares (PLS) algorithm was applied as a multivariate calibration method. The three methods were successfully applied for determination of CXZ, ACF and PAR in pure form and tablets. Good linear relationships were obtained in the ranges of 2-50, 2-40 and 2-30 μg mL- 1 for CXZ, ACF and PAR, in order, by both PCCA and MCR, while the PLS model was built for the three compounds each in the range of 2-10 μg mL- 1. The results obtained from the proposed methods were statistically compared with a reported one. PCCA and MCR methods were validated according to ICH guidelines, while PLS method was validated by both cross validation and an independent data set. They are found suitable for the determination of the studied drugs in bulk powder and tablets.

Optical and laser spectroscopic diagnostics for energy applications

NASA Astrophysics Data System (ADS)

Tripathi, Markandey Mani

The continuing need for greater energy security and energy independence has motivated researchers to develop new energy technologies for better energy resource management and efficient energy usage. The focus of this dissertation is the development of optical (spectroscopic) sensing methodologies for various fuels, and energy applications. A fiber-optic NIR sensing methodology was developed for predicting water content in bio-oil. The feasibility of using the designed near infrared (NIR) system for estimating water content in bio-oil was tested by applying multivariate analysis to NIR spectral data. The calibration results demonstrated that the spectral information can successfully predict the bio-oil water content (from 16% to 36%). The effect of ultraviolet (UV) light on the chemical stability of bio-oil was studied by employing laser-induced fluorescence (LIF) spectroscopy. To simulate the UV light exposure, a laser in the UV region (325 nm) was employed for bio-oil excitation. The LIF, as a signature of chemical change, was recorded from bio-oil. From this study, it was concluded that phenols present in the bio-oil show chemical instability, when exposed to UV light. A laser-induced breakdown spectroscopy (LIBS)-based optical sensor was designed, developed, and tested for detection of four important trace impurities in rocket fuel (hydrogen). The sensor can simultaneously measure the concentrations of nitrogen, argon, oxygen, and helium in hydrogen from storage tanks and supply lines. The sensor had estimated lower detection limits of 80 ppm for nitrogen, 97 ppm for argon, 10 ppm for oxygen, and 25 ppm for helium. A chemiluminescence-based spectroscopic diagnostics were performed to measure equivalence ratios in methane-air premixed flames. A partial least-squares regression (PLS-R)-based multivariate sensing methodology was investigated. It was found that the equivalence ratios predicted with the PLS-R-based multivariate calibration model matched with the experimentally measured equivalence ratios within 7 %. A comparative study was performed for equivalence ratios measurement in atmospheric premixed methane-air flames with ungated LIBS and chemiluminescence spectroscopy. It was reported that LIBS-based calibration, which carries spectroscopic information from a "point-like-volume," provides better predictions of equivalence ratios compared to chemiluminescence-based calibration, which is essentially a "line-of-sight" measurement.

[Measurement of Water COD Based on UV-Vis Spectroscopy Technology].

PubMed

Wang, Xiao-ming; Zhang, Hai-liang; Luo, Wei; Liu, Xue-mei

2016-01-01

Ultraviolet/visible (UV/Vis) spectroscopy technology was used to measure water COD. A total of 135 water samples were collected from Zhejiang province. Raw spectra with 3 different pretreatment methods (Multiplicative Scatter Correction (MSC), Standard Normal Variate (SNV) and 1st Derivatives were compared to determine the optimal pretreatment method for analysis. Spectral variable selection is an important strategy in spectrum modeling analysis, because it tends to parsimonious data representation and can lead to multivariate models with better performance. In order to simply calibration models, the preprocessed spectra were then used to select sensitive wavelengths by competitive adaptive reweighted sampling (CARS), Random frog and Successive Genetic Algorithm (GA) methods. Different numbers of sensitive wavelengths were selected by different variable selection methods with SNV preprocessing method. Partial least squares (PLS) was used to build models with the full spectra, and Extreme Learning Machine (ELM) was applied to build models with the selected wavelength variables. The overall results showed that ELM model performed better than PLS model, and the ELM model with the selected wavelengths based on CARS obtained the best results with the determination coefficient (R2), RMSEP and RPD were 0.82, 14.48 and 2.34 for prediction set. The results indicated that it was feasible to use UV/Vis with characteristic wavelengths which were obtained by CARS variable selection method, combined with ELM calibration could apply for the rapid and accurate determination of COD in aquaculture water. Moreover, this study laid the foundation for further implementation of online analysis of aquaculture water and rapid determination of other water quality parameters.

Interference modelling, experimental design and pre-concentration steps in validation of the Fenton's reagent for pesticides determination.

PubMed

Ostra, Miren; Ubide, Carlos; Zuriarrain, Juan

2007-02-12

The determination of atrazine in real samples (commercial pesticide preparations and water matrices) shows how the Fenton's reagent can be used with analytical purposes when kinetic methodology and multivariate calibration methods are applied. Also, binary mixtures of atrazine-alachlor and atrazine-bentazone in pesticide preparations have been resolved. The work shows the way in which interferences and the matrix effect can be modelled. Experimental design has been used to optimize experimental conditions, including the effect of solvent (methanol) used for extraction of atrazine from the sample. The determination of pesticides in commercial preparations was accomplished without any pre-treatment of sample apart from evaporation of solvent; the calibration model was developed for concentration ranges between 0.46 and 11.6 x 10(-5) mol L(-1) with mean relative errors under 4%. Solid-phase extraction is used for pre-concentration of atrazine in water samples through C(18) disks, and the concentration range for determination was established between 4 and 115 microg L(-1) approximately. Satisfactory results for recuperation of atrazine were always obtained.

Detection and quantification of adulteration in sandalwood oil through near infrared spectroscopy.

PubMed

Kuriakose, Saji; Thankappan, Xavier; Joe, Hubert; Venkataraman, Venkateswaran

2010-10-01

The confirmation of authenticity of essential oils and the detection of adulteration are problems of increasing importance in the perfumes, pharmaceutical, flavor and fragrance industries. This is especially true for 'value added' products like sandalwood oil. A methodical study is conducted here to demonstrate the potential use of Near Infrared (NIR) spectroscopy along with multivariate calibration models like principal component regression (PCR) and partial least square regression (PLSR) as rapid analytical techniques for the qualitative and quantitative determination of adulterants in sandalwood oil. After suitable pre-processing of the NIR raw spectral data, the models are built-up by cross-validation. The lowest Root Mean Square Error of Cross-Validation and Calibration (RMSECV and RMSEC % v/v) are used as a decision supporting system to fix the optimal number of factors. The coefficient of determination (R(2)) and the Root Mean Square Error of Prediction (RMSEP % v/v) in the prediction sets are used as the evaluation parameters (R(2) = 0.9999 and RMSEP = 0.01355). The overall result leads to the conclusion that NIR spectroscopy with chemometric techniques could be successfully used as a rapid, simple, instant and non-destructive method for the detection of adulterants, even 1% of the low-grade oils, in the high quality form of sandalwood oil.

Objective calibration of numerical weather prediction models

NASA Astrophysics Data System (ADS)

Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P.

2017-07-01

Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas.

A calibration method for fringe reflection technique based on the analytical phase-slope description

NASA Astrophysics Data System (ADS)

Wu, Yuxiang; Yue, Huimin; Pan, Zhipeng; Liu, Yong

2018-05-01

The fringe reflection technique (FRT) has been one of the most popular methods to measure the shape of specular surface these years. The existing system calibration methods of FRT usually contain two parts, which are camera calibration and geometric calibration. In geometric calibration, the liquid crystal display (LCD) screen position calibration is one of the most difficult steps among all the calibration procedures, and its accuracy is affected by the factors such as the imaging aberration, the plane mirror flatness, and LCD screen pixel size accuracy. In this paper, based on the deduction of FRT analytical phase-slope description, we present a novel calibration method with no requirement to calibrate the position of LCD screen. On the other hand, the system can be arbitrarily arranged, and the imaging system can either be telecentric or non-telecentric. In our experiment of measuring the 5000mm radius sphere mirror, the proposed calibration method achieves 2.5 times smaller measurement error than the geometric calibration method. In the wafer surface measuring experiment, the measurement result with the proposed calibration method is closer to the interferometer result than the geometric calibration method.

Comparative study on ATR-FTIR calibration models for monitoring solution concentration in cooling crystallization

NASA Astrophysics Data System (ADS)

Zhang, Fangkun; Liu, Tao; Wang, Xue Z.; Liu, Jingxiang; Jiang, Xiaobin

2017-02-01

In this paper calibration model building based on using an ATR-FTIR spectroscopy is investigated for in-situ measurement of the solution concentration during a cooling crystallization process. The cooling crystallization of L-glutamic Acid (LGA) as a case is studied here. It was found that using the metastable zone (MSZ) data for model calibration can guarantee the prediction accuracy for monitoring the operating window of cooling crystallization, compared to the usage of undersaturated zone (USZ) spectra for model building as traditionally practiced. Calibration experiments were made for LGA solution under different concentrations. Four candidate calibration models were established using different zone data for comparison, by using a multivariate partial least-squares (PLS) regression algorithm for the collected spectra together with the corresponding temperature values. Experiments under different process conditions including the changes of solution concentration and operating temperature were conducted. The results indicate that using the MSZ spectra for model calibration can give more accurate prediction of the solution concentration during the crystallization process, while maintaining accuracy in changing the operating temperature. The primary reason of prediction error was clarified as spectral nonlinearity for in-situ measurement between USZ and MSZ. In addition, an LGA cooling crystallization experiment was performed to verify the sensitivity of these calibration models for monitoring the crystal growth process.

Estuarine Sediment Deposition during Wetland Restoration: A GIS and Remote Sensing Modeling Approach

NASA Technical Reports Server (NTRS)

Newcomer, Michelle; Kuss, Amber; Kentron, Tyler; Remar, Alex; Choksi, Vivek; Skiles, J. W.

2011-01-01

Restoration of the industrial salt flats in the San Francisco Bay, California is an ongoing wetland rehabilitation project. Remote sensing maps of suspended sediment concentration, and other GIS predictor variables were used to model sediment deposition within these recently restored ponds. Suspended sediment concentrations were calibrated to reflectance values from Landsat TM 5 and ASTER using three statistical techniques -- linear regression, multivariate regression, and an Artificial Neural Network (ANN), to map suspended sediment concentrations. Multivariate and ANN regressions using ASTER proved to be the most accurate methods, yielding r2 values of 0.88 and 0.87, respectively. Predictor variables such as sediment grain size and tidal frequency were used in the Marsh Sedimentation (MARSED) model for predicting deposition rates for three years. MARSED results for a fully restored pond show a root mean square deviation (RMSD) of 66.8 mm (<1) between modeled and field observations. This model was further applied to a pond breached in November 2010 and indicated that the recently breached pond will reach equilibrium levels after 60 months of tidal inundation.

Support vector regression and artificial neural network models for stability indicating analysis of mebeverine hydrochloride and sulpiride mixtures in pharmaceutical preparation: A comparative study

NASA Astrophysics Data System (ADS)

Naguib, Ibrahim A.; Darwish, Hany W.

2012-02-01

A comparison between support vector regression (SVR) and Artificial Neural Networks (ANNs) multivariate regression methods is established showing the underlying algorithm for each and making a comparison between them to indicate the inherent advantages and limitations. In this paper we compare SVR to ANN with and without variable selection procedure (genetic algorithm (GA)). To project the comparison in a sensible way, the methods are used for the stability indicating quantitative analysis of mixtures of mebeverine hydrochloride and sulpiride in binary mixtures as a case study in presence of their reported impurities and degradation products (summing up to 6 components) in raw materials and pharmaceutical dosage form via handling the UV spectral data. For proper analysis, a 6 factor 5 level experimental design was established resulting in a training set of 25 mixtures containing different ratios of the interfering species. An independent test set consisting of 5 mixtures was used to validate the prediction ability of the suggested models. The proposed methods (linear SVR (without GA) and linear GA-ANN) were successfully applied to the analysis of pharmaceutical tablets containing mebeverine hydrochloride and sulpiride mixtures. The results manifest the problem of nonlinearity and how models like the SVR and ANN can handle it. The methods indicate the ability of the mentioned multivariate calibration models to deconvolute the highly overlapped UV spectra of the 6 components' mixtures, yet using cheap and easy to handle instruments like the UV spectrophotometer.

Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods.

PubMed

Durakli Velioglu, Serap; Ercioglu, Elif; Boyaci, Ismail Hakki

2017-05-01

This research paper describes the potential of synchronous fluorescence (SF) spectroscopy for authentication of buffalo milk, a favourable raw material in the production of some premium dairy products. Buffalo milk is subjected to fraudulent activities like many other high priced foodstuffs. The current methods widely used for the detection of adulteration of buffalo milk have various disadvantages making them unattractive for routine analysis. Thus, the aim of the present study was to assess the potential of SF spectroscopy in combination with multivariate methods for rapid discrimination between buffalo and cow milk and detection of the adulteration of buffalo milk with cow milk. SF spectra of cow and buffalo milk samples were recorded between 400-550 nm excitation range with Δλ of 10-100 nm, in steps of 10 nm. The data obtained for ∆λ = 10 nm were utilised to classify the samples using principal component analysis (PCA), and detect the adulteration level of buffalo milk with cow milk using partial least square (PLS) methods. Successful discrimination of samples and detection of adulteration of buffalo milk with limit of detection value (LOD) of 6% are achieved with the models having root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) values of 2, 7, and 4%, respectively. The results reveal the potential of SF spectroscopy for rapid authentication of buffalo milk.

Discrimination of edible oils and fats by combination of multivariate pattern recognition and FT-IR spectroscopy: A comparative study between different modeling methods

NASA Astrophysics Data System (ADS)

Javidnia, Katayoun; Parish, Maryam; Karimi, Sadegh; Hemmateenejad, Bahram

2013-03-01

By using FT-IR spectroscopy, many researchers from different disciplines enrich the experimental complexity of their research for obtaining more precise information. Moreover chemometrics techniques have boosted the use of IR instruments. In the present study we aimed to emphasize on the power of FT-IR spectroscopy for discrimination between different oil samples (especially fat from vegetable oils). Also our data were used to compare the performance of different classification methods. FT-IR transmittance spectra of oil samples (Corn, Colona, Sunflower, Soya, Olive, and Butter) were measured in the wave-number interval of 450-4000 cm-1. Classification analysis was performed utilizing PLS-DA, interval PLS-DA, extended canonical variate analysis (ECVA) and interval ECVA methods. The effect of data preprocessing by extended multiplicative signal correction was investigated. Whilst all employed method could distinguish butter from vegetable oils, iECVA resulted in the best performances for calibration and external test set with 100% sensitivity and specificity.

Advancements in IR spectroscopic approaches for the determination of fungal derived contaminations in food crops.

PubMed

McMullin, David; Mizaikoff, Boris; Krska, Rudolf

2015-01-01

Infrared spectroscopy is a rapid, nondestructive analytical technique that can be applied to the authentication and characterization of food samples in high throughput. In particular, near infrared spectroscopy is commonly utilized in the food quality control industry to monitor the physical attributes of numerous cereal grains for protein, carbohydrate, and lipid content. IR-based methods require little sample preparation, labor, or technical competence if multivariate data mining techniques are implemented; however, they do require extensive calibration. Economically important crops are infected by fungi that can severely reduce crop yields and quality and, in addition, produce mycotoxins. Owing to the health risks associated with mycotoxins in the food chain, regulatory limits have been set by both national and international institutions for specific mycotoxins and mycotoxin classes. This article discusses the progress and potential of IR-based methods as an alternative to existing chemical methods for the determination of fungal contamination in crops, as well as emerging spectroscopic methods.

A quantitative study for determination of sugar concentration using attenuated total reflectance terahertz (ATR-THz) spectroscopy

NASA Astrophysics Data System (ADS)

Suhandy, Diding; Suzuki, Tetsuhito; Ogawa, Yuichi; Kondo, Naoshi; Ishihara, Takeshi; Takemoto, Yuichiro

2011-06-01

The objective of our research was to use ATR-THz spectroscopy together with chemometric for quantitative study in food analysis. Glucose, fructose and sucrose are main component of sugar both in fresh and processed fruits. The use of spectroscopic-based method for sugar determination is well reported especially using visible, near infrared (NIR) and middle infrared (MIR) spectroscopy. However, the use of terahertz spectroscopy for sugar determination in fruits has not yet been reported. In this work, a quantitative study for sugars determination using attenuated total reflectance terahertz (ATR-THz) spectroscopy was conducted. Each samples of glucose, fructose and sucrose solution with different concentrations were prepared respectively and their absorbance spectra between wavenumber 20 and 450 cm-1 (between 0.6 THz and 13.5 THz) were acquired using a terahertz-based Fourier Transform spectrometer (FARIS-1S, JASCO Co., Japan). This spectrometer was equipped with a high pressure of mercury lamp as light source and a pyroelectric sensor made from deuterated L-alanine triglycine sulfate (DLTGS) as detector. Each spectrum was acquired using 16 cm-1 of resolution and 200 scans for averaging. The spectra of water and sugar solutions were compared and discussed. The results showed that increasing sugar concentration caused decreasing absorbance. The correlation between sugar concentration and its spectra was investigated using multivariate analysis. Calibration models for glucose, fructose and sucrose determination were developed using partial least squares (PLS) regression. The calibration model was evaluated using some parameters such as coefficient of determination (R2), standard error of calibration (SEC), standard error of prediction (SEP), bias between actual and predicted sugar concentration value and ratio prediction to deviation (RPD) parameter. The cross validation method was used to validate each calibration model. It is showed that the use of ATR-THz spectroscopy combined with appropriate chemometric can be a potential for a rapid determination of sugar concentrations.

Enhanced ID Pit Sizing Using Multivariate Regression Algorithm

NASA Astrophysics Data System (ADS)

Krzywosz, Kenji

2007-03-01

EPRI is funding a program to enhance and improve the reliability of inside diameter (ID) pit sizing for balance-of plant heat exchangers, such as condensers and component cooling water heat exchangers. More traditional approaches to ID pit sizing involve the use of frequency-specific amplitude or phase angles. The enhanced multivariate regression algorithm for ID pit depth sizing incorporates three simultaneous input parameters of frequency, amplitude, and phase angle. A set of calibration data sets consisting of machined pits of various rounded and elongated shapes and depths was acquired in the frequency range of 100 kHz to 1 MHz for stainless steel tubing having nominal wall thickness of 0.028 inch. To add noise to the acquired data set, each test sample was rotated and test data acquired at 3, 6, 9, and 12 o'clock positions. The ID pit depths were estimated using a second order and fourth order regression functions by relying on normalized amplitude and phase angle information from multiple frequencies. Due to unique damage morphology associated with the microbiologically-influenced ID pits, it was necessary to modify the elongated calibration standard-based algorithms by relying on the algorithm developed solely from the destructive sectioning results. This paper presents the use of transformed multivariate regression algorithm to estimate ID pit depths and compare the results with the traditional univariate phase angle analysis. Both estimates were then compared with the destructive sectioning results.

Calibration method for a large-scale structured light measurement system.

PubMed

Wang, Peng; Wang, Jianmei; Xu, Jing; Guan, Yong; Zhang, Guanglie; Chen, Ken

2017-05-10

The structured light method is an effective non-contact measurement approach. The calibration greatly affects the measurement precision of structured light systems. To construct a large-scale structured light system with high accuracy, a large-scale and precise calibration gauge is always required, which leads to an increased cost. To this end, in this paper, a calibration method with a planar mirror is proposed to reduce the calibration gauge size and cost. An out-of-focus camera calibration method is also proposed to overcome the defocusing problem caused by the shortened distance during the calibration procedure. The experimental results verify the accuracy of the proposed calibration method.

Application of correlation constrained multivariate curve resolution alternating least-squares methods for determination of compounds of interest in biodiesel blends using NIR and UV-visible spectroscopic data.

PubMed

de Oliveira, Rodrigo Rocha; de Lima, Kássio Michell Gomes; Tauler, Romà; de Juan, Anna

2014-07-01

This study describes two applications of a variant of the multivariate curve resolution alternating least squares (MCR-ALS) method with a correlation constraint. The first application describes the use of MCR-ALS for the determination of biodiesel concentrations in biodiesel blends using near infrared (NIR) spectroscopic data. In the second application, the proposed method allowed the determination of the synthetic antioxidant N,N'-Di-sec-butyl-p-phenylenediamine (PDA) present in biodiesel mixtures from different vegetable sources using UV-visible spectroscopy. Well established multivariate regression algorithm, partial least squares (PLS), were calculated for comparison of the quantification performance in the models developed in both applications. The correlation constraint has been adapted to handle the presence of batch-to-batch matrix effects due to ageing effects, which might occur when different groups of samples were used to build a calibration model in the first application. Different data set configurations and diverse modes of application of the correlation constraint are explored and guidelines are given to cope with different type of analytical problems, such as the correction of matrix effects among biodiesel samples, where MCR-ALS outperformed PLS reducing the relative error of prediction RE (%) from 9.82% to 4.85% in the first application, or the determination of minor compound with overlapped weak spectroscopic signals, where MCR-ALS gave higher (RE (%)=3.16%) for prediction of PDA compared to PLS (RE (%)=1.99%), but with the advantage of recovering the related pure spectral profile of analytes and interferences. The obtained results show the potential of the MCR-ALS method with correlation constraint to be adapted to diverse data set configurations and analytical problems related to the determination of biodiesel mixtures and added compounds therein. Copyright © 2014 Elsevier B.V. All rights reserved.

A LiDAR data-based camera self-calibration method

NASA Astrophysics Data System (ADS)

Xu, Lijun; Feng, Jing; Li, Xiaolu; Chen, Jianjun

2018-07-01

To find the intrinsic parameters of a camera, a LiDAR data-based camera self-calibration method is presented here. Parameters have been estimated using particle swarm optimization (PSO), enhancing the optimal solution of a multivariate cost function. The main procedure of camera intrinsic parameter estimation has three parts, which include extraction and fine matching of interest points in the images, establishment of cost function, based on Kruppa equations and optimization of PSO using LiDAR data as the initialization input. To improve the precision of matching pairs, a new method of maximal information coefficient (MIC) and maximum asymmetry score (MAS) was used to remove false matching pairs based on the RANSAC algorithm. Highly precise matching pairs were used to calculate the fundamental matrix so that the new cost function (deduced from Kruppa equations in terms of the fundamental matrix) was more accurate. The cost function involving four intrinsic parameters was minimized by PSO for the optimal solution. To overcome the issue of optimization pushed to a local optimum, LiDAR data was used to determine the scope of initialization, based on the solution to the P4P problem for camera focal length. To verify the accuracy and robustness of the proposed method, simulations and experiments were implemented and compared with two typical methods. Simulation results indicated that the intrinsic parameters estimated by the proposed method had absolute errors less than 1.0 pixel and relative errors smaller than 0.01%. Based on ground truth obtained from a meter ruler, the distance inversion accuracy in the experiments was smaller than 1.0 cm. Experimental and simulated results demonstrated that the proposed method was highly accurate and robust.

Calibration of an electronic nose for poultry farm

NASA Astrophysics Data System (ADS)

Abdullah, A. H.; Shukor, S. A.; Kamis, M. S.; Shakaff, A. Y. M.; Zakaria, A.; Rahim, N. A.; Mamduh, S. M.; Kamarudin, K.; Saad, F. S. A.; Masnan, M. J.; Mustafa, H.

2017-03-01

Malodour from the poultry farms could cause air pollution and therefore potentially dangerous to humans' and animals' health. This issue also poses sustainability risk to the poultry industries due to objections from local community. The aim of this paper is to develop and calibrate a cost effective and efficient electronic nose for poultry farm air monitoring. The instrument main components include sensor chamber, array of specific sensors, microcontroller, signal conditioning circuits and wireless sensor networks. The instrument was calibrated to allow classification of different concentrations of main volatile compounds in the poultry farm malodour. The outcome of the process will also confirm the device's reliability prior to being used for poultry farm malodour assessment. The Multivariate Analysis (HCA and KNN) and Artificial Neural Network (ANN) pattern recognition technique was used to process the acquired data. The results show that the instrument is able to calibrate the samples using ANN classification model with high accuracy. The finding verifies the instrument's performance to be used as an effective poultry farm malodour monitoring.

Quantitation of active pharmaceutical ingredients and excipients in powder blends using designed multivariate calibration models by near-infrared spectroscopy.

PubMed

Li, Weiyong; Worosila, Gregory D

2005-05-13

This research note demonstrates the simultaneous quantitation of a pharmaceutical active ingredient and three excipients in a simulated powder blend containing acetaminophen, Prosolv and Crospovidone. An experimental design approach was used in generating a 5-level (%, w/w) calibration sample set that included 125 samples. The samples were prepared by weighing suitable amount of powders into separate 20-mL scintillation vials and were mixed manually. Partial least squares (PLS) regression was used in calibration model development. The models generated accurate results for quantitation of Crospovidone (at 5%, w/w) and magnesium stearate (at 0.5%, w/w). Further testing of the models demonstrated that the 2-level models were as effective as the 5-level ones, which reduced the calibration sample number to 50. The models had a small bias for quantitation of acetaminophen (at 30%, w/w) and Prosolv (at 64.5%, w/w) in the blend. The implication of the bias is discussed.

Quantitative analysis of virgin coconut oil in cream cosmetics preparations using fourier transform infrared (FTIR) spectroscopy.

PubMed

Rohman, A; Man, Yb Che; Sismindari

2009-10-01

Today, virgin coconut oil (VCO) is becoming valuable oil and is receiving an attractive topic for researchers because of its several biological activities. In cosmetics industry, VCO is excellent material which functions as a skin moisturizer and softener. Therefore, it is important to develop a quantitative analytical method offering a fast and reliable technique. Fourier transform infrared (FTIR) spectroscopy with sample handling technique of attenuated total reflectance (ATR) can be successfully used to analyze VCO quantitatively in cream cosmetic preparations. A multivariate analysis using calibration of partial least square (PLS) model revealed the good relationship between actual value and FTIR-predicted value of VCO with coefficient of determination (R2) of 0.998.

A projector calibration method for monocular structured light system based on digital image correlation

NASA Astrophysics Data System (ADS)

Feng, Zhixin

2018-02-01

Projector calibration is crucial for a camera-projector three-dimensional (3-D) structured light measurement system, which has one camera and one projector. In this paper, a novel projector calibration method is proposed based on digital image correlation. In the method, the projector is viewed as an inverse camera, and a plane calibration board with feature points is used to calibrate the projector. During the calibration processing, a random speckle pattern is projected onto the calibration board with different orientations to establish the correspondences between projector images and camera images. Thereby, dataset for projector calibration are generated. Then the projector can be calibrated using a well-established camera calibration algorithm. The experiment results confirm that the proposed method is accurate and reliable for projector calibration.

Multi-Variable and Multi-Site Calibration and Validation of SWAT for Water Quality in the Kaskaskia River Watershed

EPA Science Inventory

The Future Midwest Landscape (FML) project is part of the U.S. Environmental Protection Agency’s new Ecosystem Services Research Program, undertaken to examine the variety of ways in which landscapes that include crop lands, conservation areas, wetlands, lakes and streams affect ...

ASCAL: A Microcomputer Program for Estimating Logistic IRT Item Parameters.

ERIC Educational Resources Information Center

Vale, C. David; Gialluca, Kathleen A.

ASCAL is a microcomputer-based program for calibrating items according to the three-parameter logistic model of item response theory. It uses a modified multivariate Newton-Raphson procedure for estimating item parameters. This study evaluated this procedure using Monte Carlo Simulation Techniques. The current version of ASCAL was then compared to…

Detection of Butter Adulteration with Lard by Employing (1)H-NMR Spectroscopy and Multivariate Data Analysis.

PubMed

Fadzillah, Nurrulhidayah Ahmad; Man, Yaakob bin Che; Rohman, Abdul; Rosman, Arieff Salleh; Ismail, Amin; Mustafa, Shuhaimi; Khatib, Alfi

2015-01-01

The authentication of food products from the presence of non-allowed components for certain religion like lard is very important. In this study, we used proton Nuclear Magnetic Resonance ((1)H-NMR) spectroscopy for the analysis of butter adulterated with lard by simultaneously quantification of all proton bearing compounds, and consequently all relevant sample classes. Since the spectra obtained were too complex to be analyzed visually by the naked eyes, the classification of spectra was carried out.The multivariate calibration of partial least square (PLS) regression was used for modelling the relationship between actual value of lard and predicted value. The model yielded a highest regression coefficient (R(2)) of 0.998 and the lowest root mean square error calibration (RMSEC) of 0.0091% and root mean square error prediction (RMSEP) of 0.0090, respectively. Cross validation testing evaluates the predictive power of the model. PLS model was shown as good models as the intercept of R(2)Y and Q(2)Y were 0.0853 and -0.309, respectively.

Boiling points of halogenated aliphatic compounds: a quantitative structure-property relationship for prediction and validation.

PubMed

Oberg, Tomas

2004-01-01

Halogenated aliphatic compounds have many technical uses, but substances within this group are also ubiquitous environmental pollutants that can affect the ozone layer and contribute to global warming. The establishment of quantitative structure-property relationships is of interest not only to fill in gaps in the available database but also to validate experimental data already acquired. The three-dimensional structures of 240 compounds were modeled with molecular mechanics prior to the generation of empirical descriptors. Two bilinear projection methods, principal component analysis (PCA) and partial-least-squares regression (PLSR), were used to identify outliers. PLSR was subsequently used to build a multivariate calibration model by extracting the latent variables that describe most of the covariation between the molecular structure and the boiling point. Boiling points were also estimated with an extension of the group contribution method of Stein and Brown.

Diffuse Reflectance Spectroscopy of Hidden Objects. Part II: Recovery of a Target Spectrum.

PubMed

Pomerantsev, Alexey L; Rodionova, Oxana Ye; Skvortsov, Alexej N

2017-08-01

In this study, we consider the reconstruction of a diffuse reflectance near-infrared spectrum of an object (target spectrum) in case the object is covered by an interfering absorbing and scattering layer. Recovery is performed using a new empirical method, which was developed in our previous study. We focus on a system, which consists of several layers of polyethylene (PE) film and underlayer objects with different spectral features. The spectral contribution of the interfering layer is modeled by a three-component two-parameter multivariate curve resolution (MCR) model, which was built and calibrated using spectrally flat objects. We show that this model is applicable to real objects with non-uniform spectra. Ultimately, the target spectrum can be reconstructed from a single spectrum of the covered target. With calculation methods, we are able to recover quite accurately the spectrum of a target even when the object is covered by 0.7 mm of PE.

Rapid evaluation and quantitative analysis of thyme, origano and chamomile essential oils by ATR-IR and NIR spectroscopy

NASA Astrophysics Data System (ADS)

Schulz, Hartwig; Quilitzsch, Rolf; Krüger, Hans

2003-12-01

The essential oils obtained from various chemotypes of thyme, origano and chamomile species were studied by ATR/FT-IR as well as NIR spectroscopy. Application of multivariate statistics (PCA, PLS) in conjunction with analytical reference data leads to very good IR and NIR calibration results. For the main essential oil components (e.g. carvacrol, thymol, γ-terpinene, α-bisabolol and β-farnesene) standard errors are in the range of the applied GC reference method. In most cases the multiple coefficients of determination ( R2) are >0.97. Using the IR fingerprint region (900-1400 cm -1) a qualitative discrimination of the individual chemotypes is possible already by visual judgement without to apply any chemometric algorithms.The described rapid and non-destructive methods can be applied in industry to control very easily purifying, blending and redistillation processes of the mentioned essential oils.

Real-time absorption and scattering characterization of slab-shaped turbid samples obtained by a combination of angular and spatially resolved measurements.

PubMed

Dam, Jan S; Yavari, Nazila; Sørensen, Søren; Andersson-Engels, Stefan

2005-07-10

We present a fast and accurate method for real-time determination of the absorption coefficient, the scattering coefficient, and the anisotropy factor of thin turbid samples by using simple continuous-wave noncoherent light sources. The three optical properties are extracted from recordings of angularly resolved transmittance in addition to spatially resolved diffuse reflectance and transmittance. The applied multivariate calibration and prediction techniques are based on multiple polynomial regression in combination with a Newton--Raphson algorithm. The numerical test results based on Monte Carlo simulations showed mean prediction errors of approximately 0.5% for all three optical properties within ranges typical for biological media. Preliminary experimental results are also presented yielding errors of approximately 5%. Thus the presented methods show a substantial potential for simultaneous absorption and scattering characterization of turbid media.

Pretreatment Nomogram to Predict the Risk of Acute Urinary Retention After I-125 Prostate Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roeloffzen, Ellen M., E-mail: e.m.a.roeloffzen@umcutrecht.nl; Vulpen, Marco van; Battermann, Jan J.

Purpose: Acute urinary retention (AUR) after iodine-125 (I-125) prostate brachytherapy negatively influences long-term quality of life and therefore should be prevented. We aimed to develop a nomogram to preoperatively predict the risk of AUR. Methods: Using the preoperative data of 714 consecutive patients who underwent I-125 prostate brachytherapy between 2005 and 2008 at our department, we modeled the probability of AUR. Multivariate logistic regression analysis was used to assess the predictive ability of a set of pretreatment predictors and the additional value of a new risk factor (the extent of prostate protrusion into the bladder). The performance of the finalmore » model was assessed with calibration and discrimination measures. Results: Of the 714 patients, 57 patients (8.0%) developed AUR after implantation. Multivariate analysis showed that the combination of prostate volume, IPSS score, neoadjuvant hormonal treatment and the extent of prostate protrusion contribute to the prediction of AUR. The discriminative value (receiver operator characteristic area, ROC) of the basic model (including prostate volume, International Prostate Symptom Score, and neoadjuvant hormonal treatment) to predict the development of AUR was 0.70. The addition of prostate protrusion significantly increased the discriminative power of the model (ROC 0.82). Calibration of this final model was good. The nomogram showed that among patients with a low sum score (<18 points), the risk of AUR was only 0%-5%. However, in patients with a high sum score (>35 points), the risk of AUR was more than 20%. Conclusion: This nomogram is a useful tool for physicians to predict the risk of AUR after I-125 prostate brachytherapy. The nomogram can aid in individualized treatment decision-making and patient counseling.« less

Calibration transfer of a Raman spectroscopic quantification method from at-line to in-line assessment of liquid detergent compositions.

PubMed

Brouckaert, D; Uyttersprot, J-S; Broeckx, W; De Beer, T

2017-06-08

The industrial production of liquid detergent compositions entails delicate balance of ingredients and process steps. In order to assure high quality and productivity in the manufacturing line, process analytical technology tools such as Raman spectroscopy are to be implemented. Marked chemical specificity, negligible water interference and high robustness are ascribed to this process analytical technique. Previously, at-line calibration models have been developed for determining the concentration levels of the being studied liquid detergents main ingredients from Raman spectra. A strategy is now proposed to transfer such at-line developed regression models to an in-line set-up, allowing real-time dosing control of the liquid detergent composition under production. To mimic in-line manufacturing conditions, liquid detergent compositions are created in a five-liter vessel with an overhead mixer. Raman spectra are continuously acquired by pumping the detergent under production via plastic tubing towards a Raman superhead probe, which is incorporated into a metal frame with a sapphire window facing the detergent fluid. Two at-line developed partial least squares (PLS) models are aimed at transferring, predicting the concentration of surfactant 1 and polymer 2 in the examined liquid detergent composition. A univariate slope/bias correction (SBC) is investigated, next to three well-acknowledged multivariate transformation methods: direct, piecewise and double-window piecewise direct standardization. Transfer is considered successful when the magnitude of the validation sets root mean square error of prediction (RMSEP) is similar to or smaller than the corresponding at-line prediction error. The transferred model offering the most promising outcome is further subjected to an exhaustive statistical evaluation, in order to appraise the applicability of the suggested calibration transfer method. Interval hypothesis tests are thereby performed for method comparison. It is illustrated that the investigated transfer approach yields satisfactory results, provided that the original at-line calibration model is thoroughly validated. Both SBC transfer models return lower RMSEP values than their corresponding original models. The surfactant 1 assay met all relevant evaluation criteria, demonstrating successful transfer to the in-line set-up. The in-line quantification of polymer 2 levels in the liquid detergent composition could not be statistically validated, due to the poorer performance of the at-line model. Copyright © 2017 Elsevier B.V. All rights reserved.

Simultaneous quantification of Aroclor mixtures in soil samples by gas chromatography/mass spectrometry with solid phase microextraction using partial least-squares regression.

PubMed

Zhang, Mengliang; Harrington, Peter de B

2015-01-01

Multivariate partial least-squares (PLS) method was applied to the quantification of two complex polychlorinated biphenyls (PCBs) commercial mixtures, Aroclor 1254 and 1260, in a soil matrix. PCBs in soil samples were extracted by headspace solid phase microextraction (SPME) and determined by gas chromatography/mass spectrometry (GC/MS). Decachlorinated biphenyl (deca-CB) was used as internal standard. After the baseline correction was applied, four data representations including extracted ion chromatograms (EIC) for Aroclor 1254, EIC for Aroclor 1260, EIC for both Aroclors and two-way data sets were constructed for PLS-1 and PLS-2 calibrations and evaluated with respect to quantitative prediction accuracy. The PLS model was optimized with respect to the number of latent variables using cross validation of the calibration data set. The validation of the method was performed with certified soil samples and real field soil samples and the predicted concentrations for both Aroclors using EIC data sets agreed with the certified values. The linear range of the method was from 10μgkg(-1) to 1000μgkg(-1) for both Aroclor 1254 and 1260 in soil matrices and the detection limit was 4μgkg(-1) for Aroclor 1254 and 6μgkg(-1) for Aroclor 1260. This holistic approach for the determination of mixtures of complex samples has broad application to environmental forensics and modeling. Copyright © 2014 Elsevier Ltd. All rights reserved.

Second-order data obtained by beta-cyclodextrin complexes: a novel approach for multicomponent analysis with three-way multivariate calibration methods.

PubMed

Khani, Rouhollah; Ghasemi, Jahan B; Shemirani, Farzaneh

2014-10-01

This research reports the first application of β-cyclodextrin (β-CD) complexes as a new method for generation of three way data, combined with second-order calibration methods for quantification of a binary mixture of caffeic (CA) and vanillic (VA) acids, as model compounds in fruit juices samples. At first, the basic experimental parameters affecting the formation of inclusion complexes between target analytes and β-CD were investigated and optimized. Then under the optimum conditions, parallel factor analysis (PARAFAC) and bilinear least squares/residual bilinearization (BLLS/RBL) were applied for deconvolution of trilinear data to get spectral and concentration profiles of CA and VA as a function of β-CD concentrations. Due to severe concentration profile overlapping between CA and VA in β-CD concentration dimension, PARAFAC could not be successfully applied to the studied samples. So, BLLS/RBL performed better than PARAFAC. The resolution of the model compounds was possible due to differences in the spectral absorbance changes of the β-CD complexes signals of the investigated analytes, opening a new approach for second-order data generation. The proposed method was validated by comparison with a reference method based on high-performance liquid chromatography photodiode array detection (HPLC-PDA), and no significant differences were found between the reference values and the ones obtained with the proposed method. Such a chemometrics-based protocol may be a very promising tool for more analytical applications in real samples monitoring, due to its advantages of simplicity, rapidity, accuracy, sufficient spectral resolution and concentration prediction even in the presence of unknown interferents. Copyright © 2014 Elsevier B.V. All rights reserved.

Calibration of a distributed hydrologic model for six European catchments using remote sensing data

NASA Astrophysics Data System (ADS)

Stisen, S.; Demirel, M. C.; Mendiguren González, G.; Kumar, R.; Rakovec, O.; Samaniego, L. E.

2017-12-01

While observed streamflow has been the single reference for most conventional hydrologic model calibration exercises, the availability of spatially distributed remote sensing observations provide new possibilities for multi-variable calibration assessing both spatial and temporal variability of different hydrologic processes. In this study, we first identify the key transfer parameters of the mesoscale Hydrologic Model (mHM) controlling both the discharge and the spatial distribution of actual evapotranspiration (AET) across six central European catchments (Elbe, Main, Meuse, Moselle, Neckar and Vienne). These catchments are selected based on their limited topographical and climatic variability which enables to evaluate the effect of spatial parameterization on the simulated evapotranspiration patterns. We develop a European scale remote sensing based actual evapotranspiration dataset at a 1 km grid scale driven primarily by land surface temperature observations from MODIS using the TSEB approach. Using the observed AET maps we analyze the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mHM model. This model allows calibrating one-basin-at-a-time or all-basins-together using its unique structure and multi-parameter regionalization approach. Results will indicate any tradeoffs between spatial pattern and discharge simulation during model calibration and through validation against independent internal discharge locations. Moreover, added value on internal water balances will be analyzed.

Automatic multi-camera calibration for deployable positioning systems

NASA Astrophysics Data System (ADS)

Axelsson, Maria; Karlsson, Mikael; Rudner, Staffan

2012-06-01

Surveillance with automated positioning and tracking of subjects and vehicles in 3D is desired in many defence and security applications. Camera systems with stereo or multiple cameras are often used for 3D positioning. In such systems, accurate camera calibration is needed to obtain a reliable 3D position estimate. There is also a need for automated camera calibration to facilitate fast deployment of semi-mobile multi-camera 3D positioning systems. In this paper we investigate a method for automatic calibration of the extrinsic camera parameters (relative camera pose and orientation) of a multi-camera positioning system. It is based on estimation of the essential matrix between each camera pair using the 5-point method for intrinsically calibrated cameras. The method is compared to a manual calibration method using real HD video data from a field trial with a multicamera positioning system. The method is also evaluated on simulated data from a stereo camera model. The results show that the reprojection error of the automated camera calibration method is close to or smaller than the error for the manual calibration method and that the automated calibration method can replace the manual calibration.

Combined analysis of whole human blood parameters by Raman spectroscopy and spectral-domain low-coherence interferometry

NASA Astrophysics Data System (ADS)

Gnyba, M.; Wróbel, M. S.; Karpienko, K.; Milewska, D.; Jedrzejewska-Szczerska, M.

2015-07-01

In this article the simultaneous investigation of blood parameters by complementary optical methods, Raman spectroscopy and spectral-domain low-coherence interferometry, is presented. Thus, the mutual relationship between chemical and physical properties may be investigated, because low-coherence interferometry measures optical properties of the investigated object, while Raman spectroscopy gives information about its molecular composition. A series of in-vitro measurements were carried out to assess sufficient accuracy for monitoring of blood parameters. A vast number of blood samples with various hematological parameters, collected from different donors, were measured in order to achieve a statistical significance of results and validation of the methods. Preliminary results indicate the benefits in combination of presented complementary methods and form the basis for development of a multimodal system for rapid and accurate optical determination of selected parameters in whole human blood. Future development of optical systems and multivariate calibration models are planned to extend the number of detected blood parameters and provide a robust quantitative multi-component analysis.

A new technique for spectrophotometric determination of pseudoephedrine and guaifenesin in syrup and synthetic mixture.

PubMed

Riahi, Siavash; Hadiloo, Farshad; Milani, Seyed Mohammad R; Davarkhah, Nazila; Ganjali, Mohammad R; Norouzi, Parviz; Seyfi, Payam

2011-05-01

The accuracy in predicting different chemometric methods was compared when applied on ordinary UV spectra and first order derivative spectra. Principal component regression (PCR) and partial least squares with one dependent variable (PLS1) and two dependent variables (PLS2) were applied on spectral data of pharmaceutical formula containing pseudoephedrine (PDP) and guaifenesin (GFN). The ability to derivative in resolved overlapping spectra chloropheniramine maleate was evaluated when multivariate methods are adopted for analysis of two component mixtures without using any chemical pretreatment. The chemometrics models were tested on an external validation dataset and finally applied to the analysis of pharmaceuticals. Significant advantages were found in analysis of the real samples when the calibration models from derivative spectra were used. It should also be mentioned that the proposed method is a simple and rapid way requiring no preliminary separation steps and can be used easily for the analysis of these compounds, especially in quality control laboratories. Copyright © 2011 John Wiley & Sons, Ltd.

Sustained modelling ability of artificial neural networks in the analysis of two pharmaceuticals (dextropropoxyphene and dipyrone) present in unequal concentrations.

PubMed

Cámara, María S; Ferroni, Félix M; De Zan, Mercedes; Goicoechea, Héctor C

2003-07-01

An improvement is presented on the simultaneous determination of two active ingredients present in unequal concentrations in injections. The analysis was carried out with spectrophotometric data and non-linear multivariate calibration methods, in particular artificial neural networks (ANNs). The presence of non-linearities caused by the major analyte concentrations which deviate from Beer's law was confirmed by plotting actual vs. predicted concentrations, and observing curvatures in the residuals for the estimated concentrations with linear methods. Mixtures of dextropropoxyphene and dipyrone have been analysed by using linear and non-linear partial least-squares (PLS and NPLSs) and ANNs. Notwithstanding the high degree of spectral overlap and the occurrence of non-linearities, rapid and simultaneous analysis has been achieved, with reasonably good accuracy and precision. A commercial sample was analysed by using the present methodology, and the obtained results show reasonably good agreement with those obtained by using high-performance liquid chromatography (HPLC) and a UV-spectrophotometric comparative methods.

Cole-Cole, linear and multivariate modeling of capacitance data for on-line monitoring of biomass.

PubMed

Dabros, Michal; Dennewald, Danielle; Currie, David J; Lee, Mark H; Todd, Robert W; Marison, Ian W; von Stockar, Urs

2009-02-01

This work evaluates three techniques of calibrating capacitance (dielectric) spectrometers used for on-line monitoring of biomass: modeling of cell properties using the theoretical Cole-Cole equation, linear regression of dual-frequency capacitance measurements on biomass concentration, and multivariate (PLS) modeling of scanning dielectric spectra. The performance and robustness of each technique is assessed during a sequence of validation batches in two experimental settings of differing signal noise. In more noisy conditions, the Cole-Cole model had significantly higher biomass concentration prediction errors than the linear and multivariate models. The PLS model was the most robust in handling signal noise. In less noisy conditions, the three models performed similarly. Estimates of the mean cell size were done additionally using the Cole-Cole and PLS models, the latter technique giving more satisfactory results.

A Novel Multi-Camera Calibration Method based on Flat Refractive Geometry

NASA Astrophysics Data System (ADS)

Huang, S.; Feng, M. C.; Zheng, T. X.; Li, F.; Wang, J. Q.; Xiao, L. F.

2018-03-01

Multi-camera calibration plays an important role in many field. In the paper, we present a novel multi-camera calibration method based on flat refractive geometry. All cameras can acquire calibration images of transparent glass calibration board (TGCB) at the same time. The application of TGCB leads to refractive phenomenon which can generate calibration error. The theory of flat refractive geometry is employed to eliminate the error. The new method can solve the refractive phenomenon of TGCB. Moreover, the bundle adjustment method is used to minimize the reprojection error and obtain optimized calibration results. Finally, the four-cameras calibration results of real data show that the mean value and standard deviation of the reprojection error of our method are 4.3411e-05 and 0.4553 pixel, respectively. The experimental results show that the proposed method is accurate and reliable.

Biodiesel content determination in diesel fuel blends using near infrared (NIR) spectroscopy and support vector machines (SVM).

PubMed

Alves, Julio Cesar L; Poppi, Ronei J

2013-01-30

This work verifies the potential of support vector machine (SVM) algorithm applied to near infrared (NIR) spectroscopy data to develop multivariate calibration models for determination of biodiesel content in diesel fuel blends that are more effective and appropriate for analytical determinations of this type of fuel nowadays, providing the usual extended analytical range with required accuracy. Considering the difficulty to develop suitable models for this type of determination in an extended analytical range and that, in practice, biodiesel/diesel fuel blends are nowadays most often used between 0 and 30% (v/v) of biodiesel content, a calibration model is suggested for the range 0-35% (v/v) of biodiesel in diesel blends. The possibility of using a calibration model for the range 0-100% (v/v) of biodiesel in diesel fuel blends was also investigated and the difficulty in obtaining adequate results for this full analytical range is discussed. The SVM models are compared with those obtained with PLS models. The best result was obtained by the SVM model using the spectral region 4400-4600 cm(-1) providing the RMSEP value of 0.11% in 0-35% biodiesel content calibration model. This model provides the determination of biodiesel content in agreement with the accuracy required by ABNT NBR and ASTM reference methods and without interference due to the presence of vegetable oil in the mixture. The best SVM model fit performance for the relationship studied is also verified by providing similar prediction results with the use of 4400-6200 cm(-1) spectral range while the PLS results are much worse over this spectral region. Copyright © 2012 Elsevier B.V. All rights reserved.

Application of Monte Carlo Method for Evaluation of Uncertainties of ITS-90 by Standard Platinum Resistance Thermometer

NASA Astrophysics Data System (ADS)

Palenčár, Rudolf; Sopkuliak, Peter; Palenčár, Jakub; Ďuriš, Stanislav; Suroviak, Emil; Halaj, Martin

2017-06-01

Evaluation of uncertainties of the temperature measurement by standard platinum resistance thermometer calibrated at the defining fixed points according to ITS-90 is a problem that can be solved in different ways. The paper presents a procedure based on the propagation of distributions using the Monte Carlo method. The procedure employs generation of pseudo-random numbers for the input variables of resistances at the defining fixed points, supposing the multivariate Gaussian distribution for input quantities. This allows taking into account the correlations among resistances at the defining fixed points. Assumption of Gaussian probability density function is acceptable, with respect to the several sources of uncertainties of resistances. In the case of uncorrelated resistances at the defining fixed points, the method is applicable to any probability density function. Validation of the law of propagation of uncertainty using the Monte Carlo method is presented on the example of specific data for 25 Ω standard platinum resistance thermometer in the temperature range from 0 to 660 °C. Using this example, we demonstrate suitability of the method by validation of its results.

Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures

NASA Astrophysics Data System (ADS)

Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany

2016-07-01

Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.

A calibration method of infrared LVF based spectroradiometer

NASA Astrophysics Data System (ADS)

Liu, Jiaqing; Han, Shunli; Liu, Lei; Hu, Dexin

2017-10-01

In this paper, a calibration method of LVF-based spectroradiometer is summarize, including spectral calibration and radiometric calibration. The spectral calibration process as follow: first, the relationship between stepping motor's step number and transmission wavelength is derivative by theoretical calculation, including a non-linearity correction of LVF;second, a line-to-line method was used to corrected the theoretical wavelength; Finally, the 3.39 μm and 10.69 μm laser is used for spectral calibration validation, show the sought 0.1% accuracy or better is achieved.A new sub-region multi-point calibration method is used for radiometric calibration to improving accuracy, results show the sought 1% accuracy or better is achieved.

Feasibility of field portable near infrared (NIR) spectroscopy to determine cyanide concentrations in soil

NASA Astrophysics Data System (ADS)

Sut, Magdalena; Fischer, Thomas; Repmann, Frank; Raab, Thomas

2013-04-01

In Germany, at more than 1000 sites, soil is polluted with an anthropogenic contaminant in form of iron-cyanide complexes. These contaminations are caused by former Manufactured Gas Plants (MGPs), where electricity for lighting was produced in the process of coal gasification. The production of manufactured gas was restrained in 1950, which caused cessation of MGPs. Our study describes the application of Polychromix Handheld Field Portable Near-Infrared (NIR) Analyzer to predict the cyanide concentrations in soil. In recent times, when the soil remediation is of major importance, there is a need to develop rapid and non-destructive methods for contaminant determination in the field. In situ analysis enables determination of 'hot spots', is cheap and time saving in comparison to laboratory methods. This paper presents a novel usage of NIR spectroscopy, where a calibration model was developed, using multivariate calibration algorithms, in order to determine NIR spectral response to the cyanide concentration in soil samples. As a control, the contaminant concentration was determined using conventional Flow Injection Analysis (FIA). The experiments revealed that portable near-infrared spectrometers could be a reliable device for identification of contamination 'hot spots', where cyanide concentration are higher than 2400 mg kg-1 in the field and >1750 mg kg-1 after sample preparation in the laboratory, but cannot replace traditional laboratory analyses due to high limits of detection.

Optics-Only Calibration of a Neural-Net Based Optical NDE Method for Structural Health Monitoring

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2004-01-01

A calibration process is presented that uses optical measurements alone to calibrate a neural-net based NDE method. The method itself detects small changes in the vibration mode shapes of structures. The optics-only calibration process confirms previous work that the sensitivity to vibration-amplitude changes can be as small as 10 nanometers. A more practical value in an NDE service laboratory is shown to be 50 nanometers. Both model-generated and experimental calibrations are demonstrated using two implementations of the calibration technique. The implementations are based on previously published demonstrations of the NDE method and an alternative calibration procedure that depends on comparing neural-net and point sensor measurements. The optics-only calibration method, unlike the alternative method, does not require modifications of the structure being tested or the creation of calibration objects. The calibration process can be used to test improvements in the NDE process and to develop a vibration-mode-independence of damagedetection sensitivity. The calibration effort was intended to support NASA s objective to promote safety in the operations of ground test facilities or aviation safety, in general, by allowing the detection of the gradual onset of structural changes and damage.

Wavelength calibration of dispersive near-infrared spectrometer using relative k-space distribution with low coherence interferometer

NASA Astrophysics Data System (ADS)

Kim, Ji-hyun; Han, Jae-Ho; Jeong, Jichai

2016-05-01

The commonly employed calibration methods for laboratory-made spectrometers have several disadvantages, including poor calibration when the number of characteristic spectral peaks is low. Therefore, we present a wavelength calibration method using relative k-space distribution with low coherence interferometer. The proposed method utilizes an interferogram with a perfect sinusoidal pattern in k-space for calibration. Zero-crossing detection extracts the k-space distribution of a spectrometer from the interferogram in the wavelength domain, and a calibration lamp provides information about absolute wavenumbers. To assign wavenumbers, wavelength-to-k-space conversion is required for the characteristic spectrum of the calibration lamp with the extracted k-space distribution. Then, the wavelength calibration is completed by inverse conversion of the k-space into wavelength domain. The calibration performance of the proposed method was demonstrated with two experimental conditions of four and eight characteristic spectral peaks. The proposed method elicited reliable calibration results in both cases, whereas the conventional method of third-order polynomial curve fitting failed to determine wavelengths in the case of four characteristic peaks. Moreover, for optical coherence tomography imaging, the proposed method could improve axial resolution due to higher suppression of sidelobes in point spread function than the conventional method. We believe that our findings can improve not only wavelength calibration accuracy but also resolution for optical coherence tomography.

Verification of the ISO calibration method for field pyranometers under tropical sky conditions

NASA Astrophysics Data System (ADS)

Janjai, Serm; Tohsing, Korntip; Pattarapanitchai, Somjet; Detkhon, Pasakorn

2017-02-01

Field pyranomters need to be annually calibrated and the International Organization for Standardization (ISO) has defined a standard method (ISO 9847) for calibrating these pyranometers. According to this standard method for outdoor calibration, the field pyranometers have to be compared to a reference pyranometer for the period of 2 to 14 days, depending on sky conditions. In this work, the ISO 9847 standard method was verified under tropical sky conditions. To verify the standard method, calibration of field pyranometers was conducted at a tropical site located in Nakhon Pathom (13.82o N, 100.04o E), Thailand under various sky conditions. The conditions of the sky were monitored by using a sky camera. The calibration results for different time periods used for the calibration under various sky conditions were analyzed. It was found that the calibration periods given by this standard method could be reduced without significant change in the final calibration result. In addition, recommendation and discussion on the use of this standard method in the tropics were also presented.

FT-IR spectroscopy and multivariate analysis as an auxiliary tool for diagnosis of mental disorders: Bipolar and schizophrenia cases

NASA Astrophysics Data System (ADS)

Ogruc Ildiz, G.; Arslan, M.; Unsalan, O.; Araujo-Andrade, C.; Kurt, E.; Karatepe, H. T.; Yilmaz, A.; Yalcinkaya, O. B.; Herken, H.

2016-01-01

In this study, a methodology based on Fourier-transform infrared spectroscopy and principal component analysis and partial least square methods is proposed for the analysis of blood plasma samples in order to identify spectral changes correlated with some biomarkers associated with schizophrenia and bipolarity. Our main goal was to use the spectral information for the calibration of statistical models to discriminate and classify blood plasma samples belonging to bipolar and schizophrenic patients. IR spectra of 30 samples of blood plasma obtained from each, bipolar and schizophrenic patients and healthy control group were collected. The results obtained from principal component analysis (PCA) show a clear discrimination between the bipolar (BP), schizophrenic (SZ) and control group' (CG) blood samples that also give possibility to identify three main regions that show the major differences correlated with both mental disorders (biomarkers). Furthermore, a model for the classification of the blood samples was calibrated using partial least square discriminant analysis (PLS-DA), allowing the correct classification of BP, SZ and CG samples. The results obtained applying this methodology suggest that it can be used as a complimentary diagnostic tool for the detection and discrimination of these mental diseases.

Headspace-mass spectrometry determination of benzene, toluene and the mixture of ethylbenzene and xylene isomers in soil samples using chemometrics.

PubMed

Esteve-Turrillas, F A; Armenta, S; Garrigues, S; Pastor, A; de la Guardia, M

2007-03-21

A simple and fast method has been developed for the determination of benzene, toluene and the mixture of ethylbenzene and xylene isomers (BTEX) in soils. Samples were introduced in 10 mL standard glass vials of a headspace (HS) autosampler together with 150 microL of 2,6,10,14-tetramethylpentadecane, heated at 90 degrees C for 10 min and introduced in the mass spectrometer by using a transfer line heated at 250 degrees C as interface. The volatile fraction of samples was directly introduced into the source of the mass spectrometer which was scanned from m/z 75 to 110. A partial least squares (PLS) multivariate calibration approach based on a classical 3(3) calibration model was build with mixtures of benzene, toluene and o-xylene in 2,6,10,14-tetramethylpentadecane for BTEX determination. Results obtained for BTEX analysis by HS-MS in different types of soil samples were comparables to those obtained by the reference HS-GC-MS procedure. So, the developed procedure allowed a fast identification and prediction of BTEX present in the samples without a prior chromatographic separation.

Generic Raman-based calibration models enabling real-time monitoring of cell culture bioreactors.

PubMed

Mehdizadeh, Hamidreza; Lauri, David; Karry, Krizia M; Moshgbar, Mojgan; Procopio-Melino, Renee; Drapeau, Denis

2015-01-01

Raman-based multivariate calibration models have been developed for real-time in situ monitoring of multiple process parameters within cell culture bioreactors. Developed models are generic, in the sense that they are applicable to various products, media, and cell lines based on Chinese Hamster Ovarian (CHO) host cells, and are scalable to large pilot and manufacturing scales. Several batches using different CHO-based cell lines and corresponding proprietary media and process conditions have been used to generate calibration datasets, and models have been validated using independent datasets from separate batch runs. All models have been validated to be generic and capable of predicting process parameters with acceptable accuracy. The developed models allow monitoring multiple key bioprocess metabolic variables, and hence can be utilized as an important enabling tool for Quality by Design approaches which are strongly supported by the U.S. Food and Drug Administration. © 2015 American Institute of Chemical Engineers.

Research on camera on orbit radial calibration based on black body and infrared calibration stars

NASA Astrophysics Data System (ADS)

Wang, YuDu; Su, XiaoFeng; Zhang, WanYing; Chen, FanSheng

2018-05-01

Affected by launching process and space environment, the response capability of a space camera must be attenuated. So it is necessary for a space camera to have a spaceborne radiant calibration. In this paper, we propose a method of calibration based on accurate Infrared standard stars was proposed for increasing infrared radiation measurement precision. As stars can be considered as a point target, we use them as the radiometric calibration source and establish the Taylor expansion method and the energy extrapolation model based on WISE catalog and 2MASS catalog. Then we update the calibration results from black body. Finally, calibration mechanism is designed and the technology of design is verified by on orbit test. The experimental calibration result shows the irradiance extrapolation error is about 3% and the accuracy of calibration methods is about 10%, the results show that the methods could satisfy requirements of on orbit calibration.

A Comparison of Two Balance Calibration Model Building Methods

NASA Technical Reports Server (NTRS)

DeLoach, Richard; Ulbrich, Norbert

2007-01-01

Simulated strain-gage balance calibration data is used to compare the accuracy of two balance calibration model building methods for different noise environments and calibration experiment designs. The first building method obtains a math model for the analysis of balance calibration data after applying a candidate math model search algorithm to the calibration data set. The second building method uses stepwise regression analysis in order to construct a model for the analysis. Four balance calibration data sets were simulated in order to compare the accuracy of the two math model building methods. The simulated data sets were prepared using the traditional One Factor At a Time (OFAT) technique and the Modern Design of Experiments (MDOE) approach. Random and systematic errors were introduced in the simulated calibration data sets in order to study their influence on the math model building methods. Residuals of the fitted calibration responses and other statistical metrics were compared in order to evaluate the calibration models developed with different combinations of noise environment, experiment design, and model building method. Overall, predicted math models and residuals of both math model building methods show very good agreement. Significant differences in model quality were attributable to noise environment, experiment design, and their interaction. Generally, the addition of systematic error significantly degraded the quality of calibration models developed from OFAT data by either method, but MDOE experiment designs were more robust with respect to the introduction of a systematic component of the unexplained variance.

Post-processing of multi-hydrologic model simulations for improved streamflow projections

NASA Astrophysics Data System (ADS)

khajehei, sepideh; Ahmadalipour, Ali; Moradkhani, Hamid

2016-04-01

Hydrologic model outputs are prone to bias and uncertainty due to knowledge deficiency in model and data. Uncertainty in hydroclimatic projections arises due to uncertainty in hydrologic model as well as the epistemic or aleatory uncertainties in GCM parameterization and development. This study is conducted to: 1) evaluate the recently developed multi-variate post-processing method for historical simulations and 2) assess the effect of post-processing on uncertainty and reliability of future streamflow projections in both high-flow and low-flow conditions. The first objective is performed for historical period of 1970-1999. Future streamflow projections are generated for 10 statistically downscaled GCMs from two widely used downscaling methods: Bias Corrected Statistically Downscaled (BCSD) and Multivariate Adaptive Constructed Analogs (MACA), over the period of 2010-2099 for two representative concentration pathways of RCP4.5 and RCP8.5. Three semi-distributed hydrologic models were employed and calibrated at 1/16 degree latitude-longitude resolution for over 100 points across the Columbia River Basin (CRB) in the pacific northwest USA. Streamflow outputs are post-processed through a Bayesian framework based on copula functions. The post-processing approach is relying on a transfer function developed based on bivariate joint distribution between the observation and simulation in historical period. Results show that application of post-processing technique leads to considerably higher accuracy in historical simulations and also reducing model uncertainty in future streamflow projections.

Geometric calibration of Colour and Stereo Surface Imaging System of ESA's Trace Gas Orbiter

NASA Astrophysics Data System (ADS)

Tulyakov, Stepan; Ivanov, Anton; Thomas, Nicolas; Roloff, Victoria; Pommerol, Antoine; Cremonese, Gabriele; Weigel, Thomas; Fleuret, Francois

2018-01-01

There are many geometric calibration methods for "standard" cameras. These methods, however, cannot be used for the calibration of telescopes with large focal lengths and complex off-axis optics. Moreover, specialized calibration methods for the telescopes are scarce in literature. We describe the calibration method that we developed for the Colour and Stereo Surface Imaging System (CaSSIS) telescope, on board of the ExoMars Trace Gas Orbiter (TGO). Although our method is described in the context of CaSSIS, with camera-specific experiments, it is general and can be applied to other telescopes. We further encourage re-use of the proposed method by making our calibration code and data available on-line.

Regional vertical total electron content (VTEC) modeling together with satellite and receiver differential code biases (DCBs) using semi-parametric multivariate adaptive regression B-splines (SP-BMARS)

NASA Astrophysics Data System (ADS)

Durmaz, Murat; Karslioglu, Mahmut Onur

2015-04-01

There are various global and regional methods that have been proposed for the modeling of ionospheric vertical total electron content (VTEC). Global distribution of VTEC is usually modeled by spherical harmonic expansions, while tensor products of compactly supported univariate B-splines can be used for regional modeling. In these empirical parametric models, the coefficients of the basis functions as well as differential code biases (DCBs) of satellites and receivers can be treated as unknown parameters which can be estimated from geometry-free linear combinations of global positioning system observables. In this work we propose a new semi-parametric multivariate adaptive regression B-splines (SP-BMARS) method for the regional modeling of VTEC together with satellite and receiver DCBs, where the parametric part of the model is related to the DCBs as fixed parameters and the non-parametric part adaptively models the spatio-temporal distribution of VTEC. The latter is based on multivariate adaptive regression B-splines which is a non-parametric modeling technique making use of compactly supported B-spline basis functions that are generated from the observations automatically. This algorithm takes advantage of an adaptive scale-by-scale model building strategy that searches for best-fitting B-splines to the data at each scale. The VTEC maps generated from the proposed method are compared numerically and visually with the global ionosphere maps (GIMs) which are provided by the Center for Orbit Determination in Europe (CODE). The VTEC values from SP-BMARS and CODE GIMs are also compared with VTEC values obtained through calibration using local ionospheric model. The estimated satellite and receiver DCBs from the SP-BMARS model are compared with the CODE distributed DCBs. The results show that the SP-BMARS algorithm can be used to estimate satellite and receiver DCBs while adaptively and flexibly modeling the daily regional VTEC.

Calibration of mass spectrometric peptide mass fingerprint data without specific external or internal calibrants

PubMed Central

Wolski, Witold E; Lalowski, Maciej; Jungblut, Peter; Reinert, Knut

2005-01-01

Background Peptide Mass Fingerprinting (PMF) is a widely used mass spectrometry (MS) method of analysis of proteins and peptides. It relies on the comparison between experimentally determined and theoretical mass spectra. The PMF process requires calibration, usually performed with external or internal calibrants of known molecular masses. Results We have introduced two novel MS calibration methods. The first method utilises the local similarity of peptide maps generated after separation of complex protein samples by two-dimensional gel electrophoresis. It computes a multiple peak-list alignment of the data set using a modified Minimum Spanning Tree (MST) algorithm. The second method exploits the idea that hundreds of MS samples are measured in parallel on one sample support. It improves the calibration coefficients by applying a two-dimensional Thin Plate Splines (TPS) smoothing algorithm. We studied the novel calibration methods utilising data generated by three different MALDI-TOF-MS instruments. We demonstrate that a PMF data set can be calibrated without resorting to external or relying on widely occurring internal calibrants. The methods developed here were implemented in R and are part of the BioConductor package mscalib available from . Conclusion The MST calibration algorithm is well suited to calibrate MS spectra of protein samples resulting from two-dimensional gel electrophoretic separation. The TPS based calibration algorithm might be used to correct systematic mass measurement errors observed for large MS sample supports. As compared to other methods, our combined MS spectra calibration strategy increases the peptide/protein identification rate by an additional 5 – 15%. PMID:16102175

Vis-NIR spectrometric determination of Brix and sucrose in sugar production samples using kernel partial least squares with interval selection based on the successive projections algorithm.

PubMed

de Almeida, Valber Elias; de Araújo Gomes, Adriano; de Sousa Fernandes, David Douglas; Goicoechea, Héctor Casimiro; Galvão, Roberto Kawakami Harrop; Araújo, Mario Cesar Ugulino

2018-05-01

This paper proposes a new variable selection method for nonlinear multivariate calibration, combining the Successive Projections Algorithm for interval selection (iSPA) with the Kernel Partial Least Squares (Kernel-PLS) modelling technique. The proposed iSPA-Kernel-PLS algorithm is employed in a case study involving a Vis-NIR spectrometric dataset with complex nonlinear features. The analytical problem consists of determining Brix and sucrose content in samples from a sugar production system, on the basis of transflectance spectra. As compared to full-spectrum Kernel-PLS, the iSPA-Kernel-PLS models involve a smaller number of variables and display statistically significant superiority in terms of accuracy and/or bias in the predictions. Published by Elsevier B.V.

An investigation into force-moment calibration techniques applicable to a magnetic suspension and balance system. M.S. Thesis

NASA Technical Reports Server (NTRS)

Eskins, Jonathan

1988-01-01

The problem of determining the forces and moments acting on a wind tunnel model suspended in a Magnetic Suspension and Balance System is addressed. Two calibration methods were investigated for three types of model cores, i.e., Alnico, Samarium-Cobalt, and a superconducting solenoid. Both methods involve calibrating the currents in the electromagnetic array against known forces and moments. The first is a static calibration method using calibration weights and a system of pulleys. The other method, dynamic calibration, involves oscillating the model and using its inertia to provide calibration forces and moments. Static calibration data, found to produce the most reliable results, is presented for three degrees of freedom at 0, 15, and -10 deg angle of attack. Theoretical calculations are hampered by the inability to represent iron-cored electromagnets. Dynamic calibrations, despite being quicker and easier to perform, are not as accurate as static calibrations. Data for dynamic calibrations at 0 and 15 deg is compared with the relevant static data acquired. Distortion of oscillation traces is cited as a major source of error in dynamic calibrations.

The calibration methods for Multi-Filter Rotating Shadowband Radiometer: a review

NASA Astrophysics Data System (ADS)

Chen, Maosi; Davis, John; Tang, Hongzhao; Ownby, Carolyn; Gao, Wei

2013-09-01

The continuous, over two-decade data record from the Multi-Filter Rotating Shadowband Radiometer (MFRSR) is ideal for climate research which requires timely and accurate information of important atmospheric components such as gases, aerosols, and clouds. Except for parameters derived from MFRSR measurement ratios, which are not impacted by calibration error, most applications require accurate calibration factor(s), angular correction, and spectral response function(s) from calibration. Although a laboratory lamp (or reference) calibration can provide all the information needed to convert the instrument readings to actual radiation, in situ calibration methods are implemented routinely (daily) to fill the gaps between lamp calibrations. In this paper, the basic structure and the data collection and pretreatment of the MFRSR are described. The laboratory lamp calibration and its limitations are summarized. The cloud screening algorithms for MFRSR data are presented. The in situ calibration methods, the standard Langley method and its variants, the ratio-Langley method, the general method, Alexandrov's comprehensive method, and Chen's multi-channel method, are outlined. The reason that all these methods do not fit for all situations is that they assume some properties, such as aerosol optical depth (AOD), total optical depth (TOD), precipitable water vapor (PWV), effective size of aerosol particles, or angstrom coefficient, are invariant over time. These properties are not universal and some of them rarely happen. In practice, daily calibration factors derived from these methods should be smoothed to restrain error.

Simple transfer calibration method for a Cimel Sun-Moon photometer: calculating lunar calibration coefficients from Sun calibration constants.

PubMed

Li, Zhengqiang; Li, Kaitao; Li, Donghui; Yang, Jiuchun; Xu, Hua; Goloub, Philippe; Victori, Stephane

2016-09-20

The Cimel new technologies allow both daytime and nighttime aerosol optical depth (AOD) measurements. Although the daytime AOD calibration protocols are well established, accurate and simple nighttime calibration is still a challenging task. Standard lunar-Langley and intercomparison calibration methods both require specific conditions in terms of atmospheric stability and site condition. Additionally, the lunar irradiance model also has some known limits on its uncertainty. This paper presents a simple calibration method that transfers the direct-Sun calibration constant, V_0,Sun, to the lunar irradiance calibration coefficient, C_Moon. Our approach is a pure calculation method, independent of site limits, e.g., Moon phase. The method is also not affected by the lunar irradiance model limitations, which is the largest error source of traditional calibration methods. Besides, this new transfer calibration approach is easy to use in the field since C_Moon can be obtained directly once V_0,Sun is known. Error analysis suggests that the average uncertainty of C_Moon over the 440-1640 nm bands obtained with the transfer method is 2.4%-2.8%, depending on the V_0,Sun approach (Langley or intercomparison), which is comparable with that of lunar-Langley approach, theoretically. In this paper, the Sun-Moon transfer and the Langley methods are compared based on site measurements in Beijing, and the day-night measurement continuity and performance are analyzed.

Optimized star sensors laboratory calibration method using a regularization neural network.

PubMed

Zhang, Chengfen; Niu, Yanxiong; Zhang, Hao; Lu, Jiazhen

2018-02-10

High-precision ground calibration is essential to ensure the performance of star sensors. However, the complex distortion and multi-error coupling have brought great difficulties to traditional calibration methods, especially for large field of view (FOV) star sensors. Although increasing the complexity of models is an effective way to improve the calibration accuracy, it significantly increases the demand for calibration data. In order to achieve high-precision calibration of star sensors with large FOV, a novel laboratory calibration method based on a regularization neural network is proposed. A multi-layer structure neural network is designed to represent the mapping of the star vector and the corresponding star point coordinate directly. To ensure the generalization performance of the network, regularization strategies are incorporated into the net structure and the training algorithm. Simulation and experiment results demonstrate that the proposed method can achieve high precision with less calibration data and without any other priori information. Compared with traditional methods, the calibration error of the star sensor decreased by about 30%. The proposed method can satisfy the precision requirement for large FOV star sensors.

Features calibration of the dynamic force transducers

NASA Astrophysics Data System (ADS)

Sc., M. Yu Prilepko D.; Lysenko, V. G.

2018-04-01

The article discusses calibration methods of dynamic forces measuring instruments. The relevance of work is dictated by need to valid definition of the dynamic forces transducers metrological characteristics taking into account their intended application. The aim of this work is choice justification of calibration method, which provides the definition dynamic forces transducers metrological characteristics under simulation operating conditions for determining suitability for using in accordance with its purpose. The following tasks are solved: the mathematical model and the main measurements equation of calibration dynamic forces transducers by load weight, the main budget uncertainty components of calibration are defined. The new method of dynamic forces transducers calibration with use the reference converter “force-deformation” based on the calibrated elastic element and measurement of his deformation by a laser interferometer is offered. The mathematical model and the main measurements equation of the offered method is constructed. It is shown that use of calibration method based on measurements by the laser interferometer of calibrated elastic element deformations allows to exclude or to considerably reduce the uncertainty budget components inherent to method of load weight.

Radiometer calibration methods and resulting irradiance differences: Radiometer calibration methods and resulting irradiance differences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habte, Aron; Sengupta, Manajit; Andreas, Afshin

Accurate solar radiation measured by radiometers depends on instrument performance specifications, installation method, calibration procedure, measurement conditions, maintenance practices, location, and environmental conditions. This study addresses the effect of different calibration methodologies and resulting differences provided by radiometric calibration service providers such as the National Renewable Energy Laboratory (NREL) and manufacturers of radiometers. Some of these methods calibrate radiometers indoors and some outdoors. To establish or understand the differences in calibration methodologies, we processed and analyzed field-measured data from radiometers deployed for 10 months at NREL's Solar Radiation Research Laboratory. These different methods of calibration resulted in a difference ofmore » +/-1% to +/-2% in solar irradiance measurements. Analyzing these differences will ultimately assist in determining the uncertainties of the field radiometer data and will help develop a consensus on a standard for calibration. Further advancing procedures for precisely calibrating radiometers to world reference standards that reduce measurement uncertainties will help the accurate prediction of the output of planned solar conversion projects and improve the bankability of financing solar projects.« less

Quantitative laser-induced breakdown spectroscopy data using peak area step-wise regression analysis: an alternative method for interpretation of Mars science laboratory results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clegg, Samuel M; Barefield, James E; Wiens, Roger C

2008-01-01

The ChemCam instrument on the Mars Science Laboratory (MSL) will include a laser-induced breakdown spectrometer (LIBS) to quantify major and minor elemental compositions. The traditional analytical chemistry approach to calibration curves for these data regresses a single diagnostic peak area against concentration for each element. This approach contrasts with a new multivariate method in which elemental concentrations are predicted by step-wise multiple regression analysis based on areas of a specific set of diagnostic peaks for each element. The method is tested on LIBS data from igneous and metamorphosed rocks. Between 4 and 13 partial regression coefficients are needed to describemore » each elemental abundance accurately (i.e., with a regression line of R{sup 2} > 0.9995 for the relationship between predicted and measured elemental concentration) for all major and minor elements studied. Validation plots suggest that the method is limited at present by the small data set, and will work best for prediction of concentration when a wide variety of compositions and rock types has been analyzed.« less

Discrimination of edible oils and fats by combination of multivariate pattern recognition and FT-IR spectroscopy: a comparative study between different modeling methods.

PubMed

Javidnia, Katayoun; Parish, Maryam; Karimi, Sadegh; Hemmateenejad, Bahram

2013-03-01

By using FT-IR spectroscopy, many researchers from different disciplines enrich the experimental complexity of their research for obtaining more precise information. Moreover chemometrics techniques have boosted the use of IR instruments. In the present study we aimed to emphasize on the power of FT-IR spectroscopy for discrimination between different oil samples (especially fat from vegetable oils). Also our data were used to compare the performance of different classification methods. FT-IR transmittance spectra of oil samples (Corn, Colona, Sunflower, Soya, Olive, and Butter) were measured in the wave-number interval of 450-4000 cm(-1). Classification analysis was performed utilizing PLS-DA, interval PLS-DA, extended canonical variate analysis (ECVA) and interval ECVA methods. The effect of data preprocessing by extended multiplicative signal correction was investigated. Whilst all employed method could distinguish butter from vegetable oils, iECVA resulted in the best performances for calibration and external test set with 100% sensitivity and specificity. Copyright © 2012 Elsevier B.V. All rights reserved.

Evaluating the role of evapotranspiration remote sensing data in improving hydrological modeling predictability

NASA Astrophysics Data System (ADS)

Herman, Matthew R.; Nejadhashemi, A. Pouyan; Abouali, Mohammad; Hernandez-Suarez, Juan Sebastian; Daneshvar, Fariborz; Zhang, Zhen; Anderson, Martha C.; Sadeghi, Ali M.; Hain, Christopher R.; Sharifi, Amirreza

2018-01-01

As the global demands for the use of freshwater resources continues to rise, it has become increasingly important to insure the sustainability of this resources. This is accomplished through the use of management strategies that often utilize monitoring and the use of hydrological models. However, monitoring at large scales is not feasible and therefore model applications are becoming challenging, especially when spatially distributed datasets, such as evapotranspiration, are needed to understand the model performances. Due to these limitations, most of the hydrological models are only calibrated for data obtained from site/point observations, such as streamflow. Therefore, the main focus of this paper is to examine whether the incorporation of remotely sensed and spatially distributed datasets can improve the overall performance of the model. In this study, actual evapotranspiration (ETa) data was obtained from the two different sets of satellite based remote sensing data. One dataset estimates ETa based on the Simplified Surface Energy Balance (SSEBop) model while the other one estimates ETa based on the Atmosphere-Land Exchange Inverse (ALEXI) model. The hydrological model used in this study is the Soil and Water Assessment Tool (SWAT), which was calibrated against spatially distributed ETa and single point streamflow records for the Honeyoey Creek-Pine Creek Watershed, located in Michigan, USA. Two different techniques, multi-variable and genetic algorithm, were used to calibrate the SWAT model. Using the aforementioned datasets, the performance of the hydrological model in estimating ETa was improved using both calibration techniques by achieving Nash-Sutcliffe efficiency (NSE) values >0.5 (0.73-0.85), percent bias (PBIAS) values within ±25% (±21.73%), and root mean squared error - observations standard deviation ratio (RSR) values <0.7 (0.39-0.52). However, the genetic algorithm technique was more effective with the ETa calibration while significantly reducing the model performance for estimating the streamflow (NSE: 0.32-0.52, PBIAS: ±32.73%, and RSR: 0.63-0.82). Meanwhile, using the multi-variable technique, the model performance for estimating the streamflow was maintained with a high level of accuracy (NSE: 0.59-0.61, PBIAS: ±13.70%, and RSR: 0.63-0.64) while the evapotranspiration estimations were improved. Results from this assessment shows that incorporation of remotely sensed and spatially distributed data can improve the hydrological model performance if it is coupled with a right calibration technique.

Research on the calibration methods of the luminance parameter of radiation luminance meters

NASA Astrophysics Data System (ADS)

Cheng, Weihai; Huang, Biyong; Lin, Fangsheng; Li, Tiecheng; Yin, Dejin; Lai, Lei

2017-10-01

This paper introduces standard diffusion reflection white plate method and integrating sphere standard luminance source method to calibrate the luminance parameter. The paper compares the effects of calibration results by using these two methods through principle analysis and experimental verification. After using two methods to calibrate the same radiation luminance meter, the data obtained verifies the testing results of the two methods are both reliable. The results show that the display value using standard white plate method has fewer errors and better reproducibility. However, standard luminance source method is more convenient and suitable for on-site calibration. Moreover, standard luminance source method has wider range and can test the linear performance of the instruments.

Measurement of pH in whole blood by near-infrared spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alam, M. Kathleen; Maynard, John D.; Robinson, M. Ries

1999-03-01

Whole blood pH has been determined {ital in vitro} by using near-infrared spectroscopy over the wavelength range of 1500 to 1785 nm with multivariate calibration modeling of the spectral data obtained from two different sample sets. In the first sample set, the pH of whole blood was varied without controlling cell size and oxygen saturation (O{sub 2} Sat) variation. The result was that the red blood cell (RBC) size and O{sub 2} Sat correlated with pH. Although the partial least-squares (PLS) multivariate calibration of these data produced a good pH prediction cross-validation standard error of prediction (CVSEP)=0.046, R{sup 2}=0.982, themore » spectral data were dominated by scattering changes due to changing RBC size that correlated with the pH changes. A second experiment was carried out where the RBC size and O{sub 2} Sat were varied orthogonally to the pH variation. A PLS calibration of the spectral data obtained from these samples produced a pH prediction with an R{sup 2} of 0.954 and a cross-validated standard error of prediction of 0.064 pH units. The robustness of the PLS calibration models was tested by predicting the data obtained from the other sets. The predicted pH values obtained from both data sets yielded R{sup 2} values greater than 0.9 once the data were corrected for differences in hemoglobin concentration. For example, with the use of the calibration produced from the second sample set, the pH values from the first sample set were predicted with an R{sup 2} of 0.92 after the predictions were corrected for bias and slope. It is shown that spectral information specific to pH-induced chemical changes in the hemoglobin molecule is contained within the PLS loading vectors developed for both the first and second data sets. It is this pH specific information that allows the spectra dominated by pH-correlated scattering changes to provide robust pH predictive ability in the uncorrelated data, and visa versa. {copyright} {ital 1999} {ital Society for Applied Spectroscopy}« less

A novel dual-camera calibration method for 3D optical measurement

NASA Astrophysics Data System (ADS)

Gai, Shaoyan; Da, Feipeng; Dai, Xianqiang

2018-05-01

A novel dual-camera calibration method is presented. In the classic methods, the camera parameters are usually calculated and optimized by the reprojection error. However, for a system designed for 3D optical measurement, this error does not denote the result of 3D reconstruction. In the presented method, a planar calibration plate is used. In the beginning, images of calibration plate are snapped from several orientations in the measurement range. The initial parameters of the two cameras are obtained by the images. Then, the rotation and translation matrix that link the frames of two cameras are calculated by using method of Centroid Distance Increment Matrix. The degree of coupling between the parameters is reduced. Then, 3D coordinates of the calibration points are reconstructed by space intersection method. At last, the reconstruction error is calculated. It is minimized to optimize the calibration parameters. This error directly indicates the efficiency of 3D reconstruction, thus it is more suitable for assessing the quality of dual-camera calibration. In the experiments, it can be seen that the proposed method is convenient and accurate. There is no strict requirement on the calibration plate position in the calibration process. The accuracy is improved significantly by the proposed method.

Finding trap stiffness of optical tweezers using digital filters.

PubMed

Almendarez-Rangel, Pedro; Morales-Cruzado, Beatriz; Sarmiento-Gómez, Erick; Pérez-Gutiérrez, Francisco G

2018-02-01

Obtaining trap stiffness and calibration of the position detection system is the basis of a force measurement using optical tweezers. Both calibration quantities can be calculated using several experimental methods available in the literature. In most cases, stiffness determination and detection system calibration are performed separately, often requiring procedures in very different conditions, and thus confidence of calibration methods is not assured due to possible changes in the environment. In this work, a new method to simultaneously obtain both the detection system calibration and trap stiffness is presented. The method is based on the calculation of the power spectral density of positions through digital filters to obtain the harmonic contributions of the position signal. This method has the advantage of calculating both trap stiffness and photodetector calibration factor from the same dataset in situ. It also provides a direct method to avoid unwanted frequencies that could greatly affect calibration procedure, such as electric noise, for example.

Improvement of Gaofen-3 Absolute Positioning Accuracy Based on Cross-Calibration

PubMed Central

Deng, Mingjun; Li, Jiansong

2017-01-01

The Chinese Gaofen-3 (GF-3) mission was launched in August 2016, equipped with a full polarimetric synthetic aperture radar (SAR) sensor in the C-band, with a resolution of up to 1 m. The absolute positioning accuracy of GF-3 is of great importance, and in-orbit geometric calibration is a key technology for improving absolute positioning accuracy. Conventional geometric calibration is used to accurately calibrate the geometric calibration parameters of the image (internal delay and azimuth shifts) using high-precision ground control data, which are highly dependent on the control data of the calibration field, but it remains costly and labor-intensive to monitor changes in GF-3’s geometric calibration parameters. Based on the positioning consistency constraint of the conjugate points, this study presents a geometric cross-calibration method for the rapid and accurate calibration of GF-3. The proposed method can accurately calibrate geometric calibration parameters without using corner reflectors and high-precision digital elevation models, thus improving absolute positioning accuracy of the GF-3 image. GF-3 images from multiple regions were collected to verify the absolute positioning accuracy after cross-calibration. The results show that this method can achieve a calibration accuracy as high as that achieved by the conventional field calibration method. PMID:29240675

Radiometric calibration of the Earth observing system's imaging sensors

NASA Technical Reports Server (NTRS)

Slater, P. N.

1987-01-01

Philosophy, requirements, and methods of calibration of multispectral space sensor systems as applicable to the Earth Observing System (EOS) are discussed. Vicarious methods for calibration of low spatial resolution systems, with respect to the Advanced Very High Resolution Radiometer (AVHRR), are then summarized. Finally, a theoretical introduction is given to a new vicarious method of calibration using the ratio of diffuse-to-global irradiance at the Earth's surfaces as the key input. This may provide an additional independent method for in-flight calibration.

Configurations and calibration methods for passive sampling techniques.

PubMed

Ouyang, Gangfeng; Pawliszyn, Janusz

2007-10-19

Passive sampling technology has developed very quickly in the past 15 years, and is widely used for the monitoring of pollutants in different environments. The design and quantification of passive sampling devices require an appropriate calibration method. Current calibration methods that exist for passive sampling, including equilibrium extraction, linear uptake, and kinetic calibration, are presented in this review. A number of state-of-the-art passive sampling devices that can be used for aqueous and air monitoring are introduced according to their calibration methods.

Experimental Design, Near-Infrared Spectroscopy, and Multivariate Calibration: An Advanced Project in a Chemometrics Course

ERIC Educational Resources Information Center

de Oliveira, Rodrigo R.; das Neves, Luiz S.; de Lima, Kassio M. G.

2012-01-01

A chemometrics course is offered to students in their fifth semester of the chemistry undergraduate program that includes an in-depth project. Students carry out the project over five weeks (three 8-h sessions per week) and conduct it in parallel to other courses or other practical work. The students conduct a literature search, carry out…

Application of composite small calibration objects in traffic accident scene photogrammetry.

PubMed

Chen, Qiang; Xu, Hongguo; Tan, Lidong

2015-01-01

In order to address the difficulty of arranging large calibration objects and the low measurement accuracy of small calibration objects in traffic accident scene photogrammetry, a photogrammetric method based on a composite of small calibration objects is proposed. Several small calibration objects are placed around the traffic accident scene, and the coordinate system of the composite calibration object is given based on one of them. By maintaining the relative position and coplanar relationship of the small calibration objects, the local coordinate system of each small calibration object is transformed into the coordinate system of the composite calibration object. The two-dimensional direct linear transformation method is improved based on minimizing the reprojection error of the calibration points of all objects. A rectified image is obtained using the nonlinear optimization method. The increased accuracy of traffic accident scene photogrammetry using a composite small calibration object is demonstrated through the analysis of field experiments and case studies.

Multivariate analysis applied to the study of spatial distributions found in drug-eluting stent coatings by confocal Raman microscopy.

PubMed

Balss, Karin M; Long, Frederick H; Veselov, Vladimir; Orana, Argjenta; Akerman-Revis, Eugena; Papandreou, George; Maryanoff, Cynthia A

2008-07-01

Multivariate data analysis was applied to confocal Raman measurements on stents coated with the polymers and drug used in the CYPHER Sirolimus-eluting Coronary Stents. Partial least-squares (PLS) regression was used to establish three independent calibration curves for the coating constituents: sirolimus, poly(n-butyl methacrylate) [PBMA], and poly(ethylene-co-vinyl acetate) [PEVA]. The PLS calibrations were based on average spectra generated from each spatial location profiled. The PLS models were tested on six unknown stent samples to assess accuracy and precision. The wt % difference between PLS predictions and laboratory assay values for sirolimus was less than 1 wt % for the composite of the six unknowns, while the polymer models were estimated to be less than 0.5 wt % difference for the combined samples. The linearity and specificity of the three PLS models were also demonstrated with the three PLS models. In contrast to earlier univariate models, the PLS models achieved mass balance with better accuracy. This analysis was extended to evaluate the spatial distribution of the three constituents. Quantitative bitmap images of drug-eluting stent coatings are presented for the first time to assess the local distribution of components.

Signal inference with unknown response: calibration-uncertainty renormalized estimator.

PubMed

Dorn, Sebastian; Enßlin, Torsten A; Greiner, Maksim; Selig, Marco; Boehm, Vanessa

2015-01-01

The calibration of a measurement device is crucial for every scientific experiment, where a signal has to be inferred from data. We present CURE, the calibration-uncertainty renormalized estimator, to reconstruct a signal and simultaneously the instrument's calibration from the same data without knowing the exact calibration, but its covariance structure. The idea of the CURE method, developed in the framework of information field theory, is to start with an assumed calibration to successively include more and more portions of calibration uncertainty into the signal inference equations and to absorb the resulting corrections into renormalized signal (and calibration) solutions. Thereby, the signal inference and calibration problem turns into a problem of solving a single system of ordinary differential equations and can be identified with common resummation techniques used in field theories. We verify the CURE method by applying it to a simplistic toy example and compare it against existent self-calibration schemes, Wiener filter solutions, and Markov chain Monte Carlo sampling. We conclude that the method is able to keep up in accuracy with the best self-calibration methods and serves as a noniterative alternative to them.

Structured light system calibration method with optimal fringe angle.

PubMed

Li, Beiwen; Zhang, Song

2014-11-20

For structured light system calibration, one popular approach is to treat the projector as an inverse camera. This is usually performed by projecting horizontal and vertical sequences of patterns to establish one-to-one mapping between camera points and projector points. However, for a well-designed system, either horizontal or vertical fringe images are not sensitive to depth variation and thus yield inaccurate mapping. As a result, the calibration accuracy is jeopardized if a conventional calibration method is used. To address this limitation, this paper proposes a novel calibration method based on optimal fringe angle determination. Experiments demonstrate that our calibration approach can increase the measurement accuracy up to 38% compared to the conventional calibration method with a calibration volume of 300(H)  mm×250(W)  mm×500(D)  mm.

[Hyperspectral Estimation of Apple Tree Canopy LAI Based on SVM and RF Regression].

PubMed

Han, Zhao-ying; Zhu, Xi-cun; Fang, Xian-yi; Wang, Zhuo-yuan; Wang, Ling; Zhao, Geng-Xing; Jiang, Yuan-mao

2016-03-01

Leaf area index (LAI) is the dynamic index of crop population size. Hyperspectral technology can be used to estimate apple canopy LAI rapidly and nondestructively. It can be provide a reference for monitoring the tree growing and yield estimation. The Red Fuji apple trees of full bearing fruit are the researching objects. Ninety apple trees canopies spectral reflectance and LAI values were measured by the ASD Fieldspec3 spectrometer and LAI-2200 in thirty orchards in constant two years in Qixia research area of Shandong Province. The optimal vegetation indices were selected by the method of correlation analysis of the original spectral reflectance and vegetation indices. The models of predicting the LAI were built with the multivariate regression analysis method of support vector machine (SVM) and random forest (RF). The new vegetation indices, GNDVI527, ND-VI676, RVI682, FD-NVI656 and GRVI517 and the previous two main vegetation indices, NDVI670 and NDVI705, are in accordance with LAI. In the RF regression model, the calibration set decision coefficient C-R2 of 0.920 and validation set decision coefficient V-R2 of 0.889 are higher than the SVM regression model by 0.045 and 0.033 respectively. The root mean square error of calibration set C-RMSE of 0.249, the root mean square error validation set V-RMSE of 0.236 are lower than that of the SVM regression model by 0.054 and 0.058 respectively. Relative analysis of calibrating error C-RPD and relative analysis of validation set V-RPD reached 3.363 and 2.520, 0.598 and 0.262, respectively, which were higher than the SVM regression model. The measured and predicted the scatterplot trend line slope of the calibration set and validation set C-S and V-S are close to 1. The estimation result of RF regression model is better than that of the SVM. RF regression model can be used to estimate the LAI of red Fuji apple trees in full fruit period.

Simultaneous calibration phantom commission and geometry calibration in cone beam CT

NASA Astrophysics Data System (ADS)

Xu, Yuan; Yang, Shuai; Ma, Jianhui; Li, Bin; Wu, Shuyu; Qi, Hongliang; Zhou, Linghong

2017-09-01

Geometry calibration is a vital step for describing the geometry of a cone beam computed tomography (CBCT) system and is a prerequisite for CBCT reconstruction. In current methods, calibration phantom commission and geometry calibration are divided into two independent tasks. Small errors in ball-bearing (BB) positioning in the phantom-making step will severely degrade the quality of phantom calibration. To solve this problem, we propose an integrated method to simultaneously realize geometry phantom commission and geometry calibration. Instead of assuming the accuracy of the geometry phantom, the integrated method considers BB centers in the phantom as an optimized parameter in the workflow. Specifically, an evaluation phantom and the corresponding evaluation contrast index are used to evaluate geometry artifacts for optimizing the BB coordinates in the geometry phantom. After utilizing particle swarm optimization, the CBCT geometry and BB coordinates in the geometry phantom are calibrated accurately and are then directly used for the next geometry calibration task in other CBCT systems. To evaluate the proposed method, both qualitative and quantitative studies were performed on simulated and realistic CBCT data. The spatial resolution of reconstructed images using dental CBCT can reach up to 15 line pair cm-1. The proposed method is also superior to the Wiesent method in experiments. This paper shows that the proposed method is attractive for simultaneous and accurate geometry phantom commission and geometry calibration.

Simplified method for creating a density-absorbed dose calibration curve for the low dose range from Gafchromic EBT3 film.

PubMed

Gotanda, Tatsuhiro; Katsuda, Toshizo; Gotanda, Rumi; Kuwano, Tadao; Akagawa, Takuya; Tanki, Nobuyoshi; Tabuchi, Akihiko; Shimono, Tetsunori; Kawaji, Yasuyuki

2016-01-01

Radiochromic film dosimeters have a disadvantage in comparison with an ionization chamber in that the dosimetry process is time-consuming for creating a density-absorbed dose calibration curve. The purpose of this study was the development of a simplified method of creating a density-absorbed dose calibration curve from radiochromic film within a short time. This simplified method was performed using Gafchromic EBT3 film with a low energy dependence and step-shaped Al filter. The simplified method was compared with the standard method. The density-absorbed dose calibration curves created using the simplified and standard methods exhibited approximately similar straight lines, and the gradients of the density-absorbed dose calibration curves were -32.336 and -33.746, respectively. The simplified method can obtain calibration curves within a much shorter time compared to the standard method. It is considered that the simplified method for EBT3 film offers a more time-efficient means of determining the density-absorbed dose calibration curve within a low absorbed dose range such as the diagnostic range.

Simplified method for creating a density-absorbed dose calibration curve for the low dose range from Gafchromic EBT3 film

PubMed Central

Gotanda, Tatsuhiro; Katsuda, Toshizo; Gotanda, Rumi; Kuwano, Tadao; Akagawa, Takuya; Tanki, Nobuyoshi; Tabuchi, Akihiko; Shimono, Tetsunori; Kawaji, Yasuyuki

2016-01-01

Radiochromic film dosimeters have a disadvantage in comparison with an ionization chamber in that the dosimetry process is time-consuming for creating a density-absorbed dose calibration curve. The purpose of this study was the development of a simplified method of creating a density-absorbed dose calibration curve from radiochromic film within a short time. This simplified method was performed using Gafchromic EBT3 film with a low energy dependence and step-shaped Al filter. The simplified method was compared with the standard method. The density-absorbed dose calibration curves created using the simplified and standard methods exhibited approximately similar straight lines, and the gradients of the density-absorbed dose calibration curves were −32.336 and −33.746, respectively. The simplified method can obtain calibration curves within a much shorter time compared to the standard method. It is considered that the simplified method for EBT3 film offers a more time-efficient means of determining the density-absorbed dose calibration curve within a low absorbed dose range such as the diagnostic range. PMID:28144120

Chemometric quality inspection control of pyrantel pamoate, febantel and praziquantel in veterinary tablets by mid infrared spectroscopy

NASA Astrophysics Data System (ADS)

Piantavini, Mário S.; Pontes, Flávia L. D.; Uber, Caroline P.; Stremel, Dile P.; Sena, Marcelo M.; Pontarolo, Roberto

This paper describes the development and validation of a new multivariate calibration method based on diffuse reflectance mid infrared spectroscopy for direct and simultaneous determination of three veterinary pharmaceutical drugs, pyrantel pamoate, praziquantel and febantel, in commercial tablets. The best synergy interval partial least squares (siPLS) model was obtained by selecting three spectral regions, 3715-3150, 2865-2583, and 2298-1733 cm-1, preprocessed by first derivative and Savitzky-Golay smoothing followed by mean centering. This model was built with five latent variables and provided root mean square errors of prediction (RMSEP) equal or lower than 0.69 mg per 100 mg of powder for the three analytes. The method was validated according the appropriate regulations through the estimate of figures of merit, such as trueness, precision, linearity, analytical sensitivity, bias and residual prediction deviation (RPD). Then, it was applied to three different veterinary pharmaceutical formulations found in the Brazilian market, in a situation of multi-product calibration, since the excipient composition of these commercial products, which was not known a priori, was modeled by an experimental design that scanned the likely content range of the possible constituents. The results were verified with high performance liquid chromatography with diode array detection (HPLC-DAD) and high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) and were in agreement with the predicted values at 95% confidence level. The developed method presented the advantages of being simple, rapid, solvent free, and about ten times faster than the HPLC ones.

Real-time determination of critical quality attributes using near-infrared spectroscopy: a contribution for Process Analytical Technology (PAT).

PubMed

Rosas, Juan G; Blanco, Marcel; González, Josep M; Alcalà, Manel

2012-08-15

Process Analytical Technology (PAT) is playing a central role in current regulations on pharmaceutical production processes. Proper understanding of all operations and variables connecting the raw materials to end products is one of the keys to ensuring quality of the products and continuous improvement in their production. Near infrared spectroscopy (NIRS) has been successfully used to develop faster and non-invasive quantitative methods for real-time predicting critical quality attributes (CQA) of pharmaceutical granulates (API content, pH, moisture, flowability, angle of repose and particle size). NIR spectra have been acquired from the bin blender after granulation process in a non-classified area without the need of sample withdrawal. The methodology used for data acquisition, calibration modelling and method application in this context is relatively inexpensive and can be easily implemented by most pharmaceutical laboratories. For this purpose, Partial Least-Squares (PLS) algorithm was used to calculate multivariate calibration models, that provided acceptable Root Mean Square Error of Predictions (RMSEP) values (RMSEP(API)=1.0 mg/g; RMSEP(pH)=0.1; RMSEP(Moisture)=0.1%; RMSEP(Flowability)=0.6 g/s; RMSEP(Angle of repose)=1.7° and RMSEP(Particle size)=2.5%) that allowed the application for routine analyses of production batches. The proposed method affords quality assessment of end products and the determination of important parameters with a view to understanding production processes used by the pharmaceutical industry. As shown here, the NIRS technique is a highly suitable tool for Process Analytical Technologies. Copyright © 2012 Elsevier B.V. All rights reserved.

Chemometric quality inspection control of pyrantel pamoate, febantel and praziquantel in veterinary tablets by mid infrared spectroscopy.

PubMed

Piantavini, Mário S; Pontes, Flávia L D; Uber, Caroline P; Stremel, Dile P; Sena, Marcelo M; Pontarolo, Roberto

2014-05-05

This paper describes the development and validation of a new multivariate calibration method based on diffuse reflectance mid infrared spectroscopy for direct and simultaneous determination of three veterinary pharmaceutical drugs, pyrantel pamoate, praziquantel and febantel, in commercial tablets. The best synergy interval partial least squares (siPLS) model was obtained by selecting three spectral regions, 3715-3150, 2865-2583, and 2298-1733 cm(-1), preprocessed by first derivative and Savitzky-Golay smoothing followed by mean centering. This model was built with five latent variables and provided root mean square errors of prediction (RMSEP) equal or lower than 0.69 mg per 100 mg of powder for the three analytes. The method was validated according the appropriate regulations through the estimate of figures of merit, such as trueness, precision, linearity, analytical sensitivity, bias and residual prediction deviation (RPD). Then, it was applied to three different veterinary pharmaceutical formulations found in the Brazilian market, in a situation of multi-product calibration, since the excipient composition of these commercial products, which was not known a priori, was modeled by an experimental design that scanned the likely content range of the possible constituents. The results were verified with high performance liquid chromatography with diode array detection (HPLC-DAD) and high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) and were in agreement with the predicted values at 95% confidence level. The developed method presented the advantages of being simple, rapid, solvent free, and about ten times faster than the HPLC ones. Copyright © 2014 Elsevier B.V. All rights reserved.

Post-processing of multi-model ensemble river discharge forecasts using censored EMOS

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Lisniak, Dmytro; Klein, Bastian

2014-05-01

When forecasting water levels and river discharge, ensemble weather forecasts are used as meteorological input to hydrologic process models. As hydrologic models are imperfect and the input ensembles tend to be biased and underdispersed, the output ensemble forecasts for river runoff typically are biased and underdispersed, too. Thus, statistical post-processing is required in order to achieve calibrated and sharp predictions. Standard post-processing methods such as Ensemble Model Output Statistics (EMOS) that have their origins in meteorological forecasting are now increasingly being used in hydrologic applications. Here we consider two sub-catchments of River Rhine, for which the forecasting system of the Federal Institute of Hydrology (BfG) uses runoff data that are censored below predefined thresholds. To address this methodological challenge, we develop a censored EMOS method that is tailored to such data. The censored EMOS forecast distribution can be understood as a mixture of a point mass at the censoring threshold and a continuous part based on a truncated normal distribution. Parameter estimates of the censored EMOS model are obtained by minimizing the Continuous Ranked Probability Score (CRPS) over the training dataset. Model fitting on Box-Cox transformed data allows us to take account of the positive skewness of river discharge distributions. In order to achieve realistic forecast scenarios over an entire range of lead-times, there is a need for multivariate extensions. To this end, we smooth the marginal parameter estimates over lead-times. In order to obtain realistic scenarios of discharge evolution over time, the marginal distributions have to be linked with each other. To this end, the multivariate dependence structure can either be adopted from the raw ensemble like in Ensemble Copula Coupling (ECC), or be estimated from observations in a training period. The censored EMOS model has been applied to multi-model ensemble forecasts issued on a daily basis over a period of three years. For the two catchments considered, this resulted in well calibrated and sharp forecast distributions over all lead-times from 1 to 114 h. Training observations tended to be better indicators for the dependence structure than the raw ensemble.

Unlocking interpretation in near infrared multivariate calibrations by orthogonal partial least squares.

PubMed

Stenlund, Hans; Johansson, Erik; Gottfries, Johan; Trygg, Johan

2009-01-01

Near infrared spectroscopy (NIR) was developed primarily for applications such as the quantitative determination of nutrients in the agricultural and food industries. Examples include the determination of water, protein, and fat within complex samples such as grain and milk. Because of its useful properties, NIR analysis has spread to other areas such as chemistry and pharmaceutical production. NIR spectra consist of infrared overtones and combinations thereof, making interpretation of the results complicated. It can be very difficult to assign peaks to known constituents in the sample. Thus, multivariate analysis (MVA) has been crucial in translating spectral data into information, mainly for predictive purposes. Orthogonal partial least squares (OPLS), a new MVA method, has prediction and modeling properties similar to those of other MVA techniques, e.g., partial least squares (PLS), a method with a long history of use for the analysis of NIR data. OPLS provides an intrinsic algorithmic improvement for the interpretation of NIR data. In this report, four sets of NIR data were analyzed to demonstrate the improved interpretation provided by OPLS. The first two sets included simulated data to demonstrate the overall principles; the third set comprised a statistically replicated design of experiments (DoE), to demonstrate how instrumental difference could be accurately visualized and correctly attributed to Wood's anomaly phenomena; the fourth set was chosen to challenge the MVA by using data relating to powder mixing, a crucial step in the pharmaceutical industry prior to tabletting. Improved interpretation by OPLS was demonstrated for all four examples, as compared to alternative MVA approaches. It is expected that OPLS will be used mostly in applications where improved interpretation is crucial; one such area is process analytical technology (PAT). PAT involves fewer independent samples, i.e., batches, than would be associated with agricultural applications; in addition, the Food and Drug Administration (FDA) demands "process understanding" in PAT. Both these issues make OPLS the ideal tool for a multitude of NIR calibrations. In conclusion, OPLS leads to better interpretation of spectrometry data (e.g., NIR) and improved understanding facilitates cross-scientific communication. Such improved knowledge will decrease risk, with respect to both accuracy and precision, when using NIR for PAT applications.

A new systematic calibration method of ring laser gyroscope inertial navigation system

NASA Astrophysics Data System (ADS)

Wei, Guo; Gao, Chunfeng; Wang, Qi; Wang, Qun; Xiong, Zhenyu; Long, Xingwu

2016-10-01

Inertial navigation system has been the core component of both military and civil navigation systems. Before the INS is put into application, it is supposed to be calibrated in the laboratory in order to compensate repeatability error caused by manufacturing. Discrete calibration method cannot fulfill requirements of high-accurate calibration of the mechanically dithered ring laser gyroscope navigation system with shock absorbers. This paper has analyzed theories of error inspiration and separation in detail and presented a new systematic calibration method for ring laser gyroscope inertial navigation system. Error models and equations of calibrated Inertial Measurement Unit are given. Then proper rotation arrangement orders are depicted in order to establish the linear relationships between the change of velocity errors and calibrated parameter errors. Experiments have been set up to compare the systematic errors calculated by filtering calibration result with those obtained by discrete calibration result. The largest position error and velocity error of filtering calibration result are only 0.18 miles and 0.26m/s compared with 2 miles and 1.46m/s of discrete calibration result. These results have validated the new systematic calibration method and proved its importance for optimal design and accuracy improvement of calibration of mechanically dithered ring laser gyroscope inertial navigation system.

Calibrating the stress-time curve of a combined finite-discrete element method to a Split Hopkinson Pressure Bar experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Osthus, Dave; Godinez, Humberto C.; Rougier, Esteban

We presenmore » t a generic method for automatically calibrating a computer code to an experiment, with uncertainty, for a given “training” set of computer code runs. The calibration technique is general and probabilistic, meaning the calibration uncertainty is represented in the form of a probability distribution. We demonstrate the calibration method by calibrating a combined Finite-Discrete Element Method (FDEM) to a Split Hopkinson Pressure Bar (SHPB) experiment with a granite sample. The probabilistic calibration method combines runs of a FDEM computer simulation for a range of “training” settings and experimental uncertainty to develop a statistical emulator. The process allows for calibration of input parameters and produces output quantities with uncertainty estimates for settings where simulation results are desired. Input calibration and FDEM fitted results are presented. We find that the maximum shear strength σ t max and to a lesser extent maximum tensile strength σ n max govern the behavior of the stress-time curve before and around the peak, while the specific energy in Mode II (shear) E t largely governs the post-peak behavior of the stress-time curve. Good agreement is found between the calibrated FDEM and the SHPB experiment. Interestingly, we find the SHPB experiment to be rather uninformative for calibrating the softening-curve shape parameters (a, b, and c). This work stands as a successful demonstration of how a general probabilistic calibration framework can automatically calibrate FDEM parameters to an experiment.« less

Calibrating the stress-time curve of a combined finite-discrete element method to a Split Hopkinson Pressure Bar experiment

DOE PAGES

Osthus, Dave; Godinez, Humberto C.; Rougier, Esteban; ...

2018-05-01

We presenmore » t a generic method for automatically calibrating a computer code to an experiment, with uncertainty, for a given “training” set of computer code runs. The calibration technique is general and probabilistic, meaning the calibration uncertainty is represented in the form of a probability distribution. We demonstrate the calibration method by calibrating a combined Finite-Discrete Element Method (FDEM) to a Split Hopkinson Pressure Bar (SHPB) experiment with a granite sample. The probabilistic calibration method combines runs of a FDEM computer simulation for a range of “training” settings and experimental uncertainty to develop a statistical emulator. The process allows for calibration of input parameters and produces output quantities with uncertainty estimates for settings where simulation results are desired. Input calibration and FDEM fitted results are presented. We find that the maximum shear strength σ t max and to a lesser extent maximum tensile strength σ n max govern the behavior of the stress-time curve before and around the peak, while the specific energy in Mode II (shear) E t largely governs the post-peak behavior of the stress-time curve. Good agreement is found between the calibrated FDEM and the SHPB experiment. Interestingly, we find the SHPB experiment to be rather uninformative for calibrating the softening-curve shape parameters (a, b, and c). This work stands as a successful demonstration of how a general probabilistic calibration framework can automatically calibrate FDEM parameters to an experiment.« less

Shortwave Radiometer Calibration Methods Comparison and Resulting Solar Irradiance Measurement Differences: A User Perspective

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habte, Aron; Sengupta, Manajit; Andreas, Afshin

Banks financing solar energy projects require assurance that these systems will produce the energy predicted. Furthermore, utility planners and grid system operators need to understand the impact of the variable solar resource on solar energy conversion system performance. Accurate solar radiation data sets reduce the expense associated with mitigating performance risk and assist in understanding the impacts of solar resource variability. The accuracy of solar radiation measured by radiometers depends on the instrument performance specification, installation method, calibration procedure, measurement conditions, maintenance practices, location, and environmental conditions. This study addresses the effect of different calibration methods provided by radiometric calibrationmore » service providers, such as NREL and manufacturers of radiometers, on the resulting calibration responsivity. Some of these radiometers are calibrated indoors and some outdoors. To establish or understand the differences in calibration methodology, we processed and analyzed field-measured data from these radiometers. This study investigates calibration responsivities provided by NREL's broadband outdoor radiometer calibration (BORCAL) and a few prominent manufacturers. The BORCAL method provides the outdoor calibration responsivity of pyranometers and pyrheliometers at 45 degree solar zenith angle, and as a function of solar zenith angle determined by clear-sky comparisons with reference irradiance. The BORCAL method also employs a thermal offset correction to the calibration responsivity of single-black thermopile detectors used in pyranometers. Indoor calibrations of radiometers by their manufacturers are performed using a stable artificial light source in a side-by-side comparison between the test radiometer under calibration and a reference radiometer of the same type. In both methods, the reference radiometer calibrations are traceable to the World Radiometric Reference (WRR). These different methods of calibration demonstrated +1% to +2% differences in solar irradiance measurement. Analyzing these differences will ultimately help determine the uncertainty of the field radiometer data and guide the development of a consensus standard for calibration. Further advancing procedures for precisely calibrating radiometers to world reference standards that reduce measurement uncertainty will allow more accurate prediction of solar output and improve the bankability of solar projects.« less

Calibration Method to Eliminate Zeroth Order Effect in Lateral Shearing Interferometry

NASA Astrophysics Data System (ADS)

Fang, Chao; Xiang, Yang; Qi, Keqi; Chen, Dawei

2018-04-01

In this paper, a calibration method is proposed which eliminates the zeroth order effect in lateral shearing interferometry. An analytical expression of the calibration error function is deduced, and the relationship between the phase-restoration error and calibration error is established. The analytical results show that the phase-restoration error introduced by the calibration error is proportional to the phase shifting error and zeroth order effect. The calibration method is verified using simulations and experiments. The simulation results show that the phase-restoration error is approximately proportional to the phase shift error and zeroth order effect, when the phase shifting error is less than 2° and the zeroth order effect is less than 0.2. The experimental result shows that compared with the conventional method with 9-frame interferograms, the calibration method with 5-frame interferograms achieves nearly the same restoration accuracy.

Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures.

PubMed

Hegazy, Maha A; Lotfy, Hayam M; Mowaka, Shereen; Mohamed, Ekram Hany

2016-07-05

Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations. Copyright © 2016 Elsevier B.V. All rights reserved.

Why Multivariate Methods Are Usually Vital in Research: Some Basic Concepts.

ERIC Educational Resources Information Center

Thompson, Bruce

The present paper suggests that multivariate methods ought to be used more frequently in behavioral research and explores the potential consequences of failing to use multivariate methods when these methods are appropriate. The paper explores in detail two reasons why multivariate methods are usually vital. The first is that they limit the…

Theoretical foundation, methods, and criteria for calibrating human vibration models using frequency response functions

PubMed Central

Dong, Ren G.; Welcome, Daniel E.; McDowell, Thomas W.; Wu, John Z.

2015-01-01

While simulations of the measured biodynamic responses of the whole human body or body segments to vibration are conventionally interpreted as summaries of biodynamic measurements, and the resulting models are considered quantitative, this study looked at these simulations from a different angle: model calibration. The specific aims of this study are to review and clarify the theoretical basis for model calibration, to help formulate the criteria for calibration validation, and to help appropriately select and apply calibration methods. In addition to established vibration theory, a novel theorem of mechanical vibration is also used to enhance the understanding of the mathematical and physical principles of the calibration. Based on this enhanced understanding, a set of criteria was proposed and used to systematically examine the calibration methods. Besides theoretical analyses, a numerical testing method is also used in the examination. This study identified the basic requirements for each calibration method to obtain a unique calibration solution. This study also confirmed that the solution becomes more robust if more than sufficient calibration references are provided. Practically, however, as more references are used, more inconsistencies can arise among the measured data for representing the biodynamic properties. To help account for the relative reliabilities of the references, a baseline weighting scheme is proposed. The analyses suggest that the best choice of calibration method depends on the modeling purpose, the model structure, and the availability and reliability of representative reference data. PMID:26740726

Application of Composite Small Calibration Objects in Traffic Accident Scene Photogrammetry

PubMed Central

Chen, Qiang; Xu, Hongguo; Tan, Lidong

2015-01-01

In order to address the difficulty of arranging large calibration objects and the low measurement accuracy of small calibration objects in traffic accident scene photogrammetry, a photogrammetric method based on a composite of small calibration objects is proposed. Several small calibration objects are placed around the traffic accident scene, and the coordinate system of the composite calibration object is given based on one of them. By maintaining the relative position and coplanar relationship of the small calibration objects, the local coordinate system of each small calibration object is transformed into the coordinate system of the composite calibration object. The two-dimensional direct linear transformation method is improved based on minimizing the reprojection error of the calibration points of all objects. A rectified image is obtained using the nonlinear optimization method. The increased accuracy of traffic accident scene photogrammetry using a composite small calibration object is demonstrated through the analysis of field experiments and case studies. PMID:26011052

Second-order standard addition for deconvolution and quantification of fatty acids of fish oil using GC-MS.

PubMed

Vosough, Maryam; Salemi, Amir

2007-08-15

In the present work two second-order calibration methods, generalized rank annihilation method (GRAM) and multivariate curve resolution-alternating least square (MCR-ALS) have been applied on standard addition data matrices obtained by gas chromatography-mass spectrometry (GC-MS) to characterize and quantify four unsaturated fatty acids cis-9-hexadecenoic acid (C16:1omega7c), cis-9-octadecenoic acid (C18:1omega9c), cis-11-eicosenoic acid (C20:1omega9) and cis-13-docosenoic acid (C22:1omega9) in fish oil considering matrix interferences. With these methods, the area does not need to be directly measured and predictions are more accurate. Because of non-trilinear conditions of GC-MS data matrices, at first MCR-ALS and GRAM have been used on uncorrected data matrices. In comparison to MCR-ALS, biased and imprecise concentrations (%R.S.D.=27.3) were obtained using GRAM without correcting the retention time-shift. As trilinearity is the essential requirement for implementing GRAM, the data need to be corrected. Multivariate rank alignment objectively corrects the run-to-run retention time variations between sample GC-MS data matrix and a standard addition GC-MS data matrix. Then, two second-order algorithms have been compared with each other. The above algorithms provided similar mean predictions, pure concentrations and spectral profiles. The results validated using standard mass spectra of target compounds. In addition, some of the quantification results were compared with the concentration values obtained using the selected mass chromatograms. As in the case of strong peak-overlap and the matrix effect, the classical univariate method of determination of the area of the peaks of the analytes will fail, the "second-order advantage" has solved this problem successfully.

Calibration and accuracy analysis of a focused plenoptic camera

NASA Astrophysics Data System (ADS)

Zeller, N.; Quint, F.; Stilla, U.

2014-08-01

In this article we introduce new methods for the calibration of depth images from focused plenoptic cameras and validate the results. We start with a brief description of the concept of a focused plenoptic camera and how from the recorded raw image a depth map can be estimated. For this camera, an analytical expression of the depth accuracy is derived for the first time. In the main part of the paper, methods to calibrate a focused plenoptic camera are developed and evaluated. The optical imaging process is calibrated by using a method which is already known from the calibration of traditional cameras. For the calibration of the depth map two new model based methods, which make use of the projection concept of the camera are developed. These new methods are compared to a common curve fitting approach, which is based on Taylor-series-approximation. Both model based methods show significant advantages compared to the curve fitting method. They need less reference points for calibration than the curve fitting method and moreover, supply a function which is valid in excess of the range of calibration. In addition the depth map accuracy of the plenoptic camera was experimentally investigated for different focal lengths of the main lens and is compared to the analytical evaluation.

Deconvolution of mixing time series on a graph

PubMed Central

Blocker, Alexander W.; Airoldi, Edoardo M.

2013-01-01

In many applications we are interested in making inference on latent time series from indirect measurements, which are often low-dimensional projections resulting from mixing or aggregation. Positron emission tomography, super-resolution, and network traffic monitoring are some examples. Inference in such settings requires solving a sequence of ill-posed inverse problems, yt = Axt, where the projection mechanism provides information on A. We consider problems in which A specifies mixing on a graph of times series that are bursty and sparse. We develop a multilevel state-space model for mixing times series and an efficient approach to inference. A simple model is used to calibrate regularization parameters that lead to efficient inference in the multilevel state-space model. We apply this method to the problem of estimating point-to-point traffic flows on a network from aggregate measurements. Our solution outperforms existing methods for this problem, and our two-stage approach suggests an efficient inference strategy for multilevel models of multivariate time series. PMID:25309135

Near-infrared noninvasive spectroscopic determination of pH

DOEpatents

Alam, Mary K.; Robinson, Mark R.

1998-08-11

Methods and apparatus for, preferably, determining noninvasively and in vitro pH in a human. The non-invasive method includes the steps of: generating light at three or more different wavelengths in the range of 1000 nm to 2500 nm; irradiating blood containing tissue; measuring the intensities of the wavelengths emerging from the blood containing tissue to obtain a set of at least three spectral intensities v. wavelengths; and determining the unknown values of pH. The determination of pH is made by using measured intensities at wavelengths that exhibit change in absorbance due to histidine titration. Histidine absorbance changes are due to titration by hydrogen ions. The determination of the unknown pH values is performed by at least one multivariate algorithm using two or more variables and at least one calibration model. The determined pH values are within the physiological ranges observed in blood containing tissue. The apparatus includes a tissue positioning device, a source, at least one detector, electronics, a microprocessor, memory, and apparatus for indicating the determined values.

PyDREAM: high-dimensional parameter inference for biological models in python.

PubMed

Shockley, Erin M; Vrugt, Jasper A; Lopez, Carlos F; Valencia, Alfonso

2018-02-15

Biological models contain many parameters whose values are difficult to measure directly via experimentation and therefore require calibration against experimental data. Markov chain Monte Carlo (MCMC) methods are suitable to estimate multivariate posterior model parameter distributions, but these methods may exhibit slow or premature convergence in high-dimensional search spaces. Here, we present PyDREAM, a Python implementation of the (Multiple-Try) Differential Evolution Adaptive Metropolis [DREAM(ZS)] algorithm developed by Vrugt and ter Braak (2008) and Laloy and Vrugt (2012). PyDREAM achieves excellent performance for complex, parameter-rich models and takes full advantage of distributed computing resources, facilitating parameter inference and uncertainty estimation of CPU-intensive biological models. PyDREAM is freely available under the GNU GPLv3 license from the Lopez lab GitHub repository at http://github.com/LoLab-VU/PyDREAM. c.lopez@vanderbilt.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Short wavelength Raman spectroscopy applied to the discrimination and characterization of three cultivars of extra virgin olive oils in different maturation stages.

PubMed

Gouvinhas, Irene; Machado, Nelson; Carvalho, Teresa; de Almeida, José M M M; Barros, Ana I R N A

2015-01-01

Extra virgin olive oils produced from three cultivars on different maturation stages were characterized using Raman spectroscopy. Chemometric methods (principal component analysis, discriminant analysis, principal component regression and partial least squares regression) applied to Raman spectral data were utilized to evaluate and quantify the statistical differences between cultivars and their ripening process. The models for predicting the peroxide value and free acidity of olive oils showed good calibration and prediction values and presented high coefficients of determination (>0.933). Both the R(2), and the correlation equations between the measured chemical parameters, and the values predicted by each approach are presented; these comprehend both PCR and PLS, used to assess SNV normalized Raman data, as well as first and second derivative of the spectra. This study demonstrates that a combination of Raman spectroscopy with multivariate analysis methods can be useful to predict rapidly olive oil chemical characteristics during the maturation process. Copyright © 2014 Elsevier B.V. All rights reserved.

Oximeter for reliable clinical determination of blood oxygen saturation in a fetus

DOEpatents

Robinson, Mark R.; Haaland, David M.; Ward, Kenneth J.

1996-01-01

With the crude instrumentation now in use to continuously monitor the status of the fetus at delivery, the obstetrician and labor room staff not only over-recognize the possibility of fetal distress with the resultant rise in operative deliveries, but at times do not identify fetal distress which may result in preventable fetal neurological harm. The invention, which addresses these two basic problems, comprises a method and apparatus for non-invasive determination of blood oxygen saturation in the fetus. The apparatus includes a multiple frequency light source which is coupled to an optical fiber. The output of the fiber is used to illuminate blood containing tissue of the fetus. In the preferred embodiment, the reflected light is transmitted back to the apparatus where the light intensities are simultaneously detected at multiple frequencies. The resulting spectrum is then analyzed for determination of oxygen saturation. The analysis method uses multivariate calibration techniques that compensate for nonlinear spectral response, model interfering spectral responses and detect outlier data with high sensitivity.

Assessment of the quality attributes of cod caviar paste by means of front-face fluorescence spectroscopy.

PubMed

Airado-Rodríguez, Diego; Skaret, Josefine; Wold, Jens Petter

2010-05-12

This paper describes the fluorescent behavior of cod caviar paste, stored under different conditions, in terms of light exposure and concentration of oxygen in the headspace. Multivariate curve resolution was employed to decompose the overall fluorescence spectra into pure fluorescent components and calculate the relative concentrations of these components in the different samples. Profiles corresponding to protoporphyrin IX, photoprotoporphyrin, and fluorescent oxidation products were identified. Sensory evaluation, TBARS, and analysis of volatiles are typical methods employed in the routine analysis and quality control of such food. Successful calibration models were established between fluorescence and those routine methods. Correlation coefficients higher than 0.80 were found for 79% and higher than 0.90 for 50% of the assessed odors and flavors. For instance, R values of 0.94, and 0.96 were obtained for fresh and rancid flavors respectively, and 0.89 for TBARS. On the basis of these data, it can be argued that front-face fluorescence spectroscopy can substitute all of these expensive and tedious methodologies.

Detection of BCG bacteria using a magnetoresistive biosensor: A step towards a fully electronic platform for tuberculosis point-of-care detection.

PubMed

Barroso, Teresa G; Martins, Rui C; Fernandes, Elisabete; Cardoso, Susana; Rivas, José; Freitas, Paulo P

2018-02-15

Tuberculosis is one of the major public health concerns. This highly contagious disease affects more than 10.4 million people, being a leading cause of morbidity by infection. Tuberculosis is diagnosed at the point-of-care by the Ziehl-Neelsen sputum smear microscopy test. Ziehl-Neelsen is laborious, prone to human error and infection risk, with a limit of detection of 10 4 cells/mL. In resource-poor nations, a more practical test, with lower detection limit, is paramount. This work uses a magnetoresistive biosensor to detect BCG bacteria for tuberculosis diagnosis. Herein we report: i) nanoparticle assembly method and specificity for tuberculosis detection; ii) demonstration of proportionality between BCG cell concentration and magnetoresistive voltage signal; iii) application of multiplicative signal correction for systematic effects removal; iv) investigation of calibration effectiveness using chemometrics methods; and v) comparison with state-of-the-art point-of-care tuberculosis biosensors. Results present a clear correspondence between voltage signal and cell concentration. Multiplicative signal correction removes baseline shifts within and between biochip sensors, allowing accurate and precise voltage signal between different biochips. The corrected signal was used for multivariate regression models, which significantly decreased the calibration standard error from 0.50 to 0.03log 10 (cells/mL). Results show that Ziehl-Neelsen detection limits and below are achievable with the magnetoresistive biochip, when pre-processing and chemometrics are used. Copyright © 2017 Elsevier B.V. All rights reserved.

Analytical robustness of quantitative NIR chemical imaging for Islamic paper characterization

NASA Astrophysics Data System (ADS)

Mahgoub, Hend; Gilchrist, John R.; Fearn, Thomas; Strlič, Matija

2017-07-01

Recently, spectral imaging techniques such as Multispectral (MSI) and Hyperspectral Imaging (HSI) have gained importance in the field of heritage conservation. This paper explores the analytical robustness of quantitative chemical imaging for Islamic paper characterization by focusing on the effect of different measurement and processing parameters, i.e. acquisition conditions and calibration on the accuracy of the collected spectral data. This will provide a better understanding of the technique that can provide a measure of change in collections through imaging. For the quantitative model, special calibration target was devised using 105 samples from a well-characterized reference Islamic paper collection. Two material properties were of interest: starch sizing and cellulose degree of polymerization (DP). Multivariate data analysis methods were used to develop discrimination and regression models which were used as an evaluation methodology for the metrology of quantitative NIR chemical imaging. Spectral data were collected using a pushbroom HSI scanner (Gilden Photonics Ltd) in the 1000-2500 nm range with a spectral resolution of 6.3 nm using a mirror scanning setup and halogen illumination. Data were acquired at different measurement conditions and acquisition parameters. Preliminary results showed the potential of the evaluation methodology to show that measurement parameters such as the use of different lenses and different scanning backgrounds may not have a great influence on the quantitative results. Moreover, the evaluation methodology allowed for the selection of the best pre-treatment method to be applied to the data.

Comparison of TLD calibration methods for  192Ir dosimetry

PubMed Central

Butler, Duncan J.; Wilfert, Lisa; Ebert, Martin A.; Todd, Stephen P.; Hayton, Anna J.M.; Kron, Tomas

2013-01-01

For the purpose of dose measurement using a high‐dose rate  192Ir source, four methods of thermoluminescent dosimeter (TLD) calibration were investigated. Three of the four calibration methods used the  192Ir source. Dwell times were calculated to deliver 1 Gy to the TLDs irradiated either in air or water. Dwell time calculations were confirmed by direct measurement using an ionization chamber. The fourth method of calibration used 6 MV photons from a medical linear accelerator, and an energy correction factor was applied to account for the difference in sensitivity of the TLDs in  192Ir and 6 M V. The results of the four TLD calibration methods are presented in terms of the results of a brachytherapy audit where seven Australian centers irradiated three sets of TLDs in a water phantom. The results were in agreement within estimated uncertainties when the TLDs were calibrated with the  192Ir source. Calibrating TLDs in a phantom similar to that used for the audit proved to be the most practical method and provided the greatest confidence in measured dose. When calibrated using 6 MV photons, the TLD results were consistently higher than the  192Ir−calibrated TLDs, suggesting this method does not fully correct for the response of the TLDs when irradiated in the audit phantom. PACS number: 87 PMID:23318392

Methods for Calibration of Prout-Tompkins Kinetics Parameters Using EZM Iteration and GLO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wemhoff, A P; Burnham, A K; de Supinski, B

2006-11-07

This document contains information regarding the standard procedures used to calibrate chemical kinetics parameters for the extended Prout-Tompkins model to match experimental data. Two methods for calibration are mentioned: EZM calibration and GLO calibration. EZM calibration matches kinetics parameters to three data points, while GLO calibration slightly adjusts kinetic parameters to match multiple points. Information is provided regarding the theoretical approach and application procedure for both of these calibration algorithms. It is recommended that for the calibration process, the user begin with EZM calibration to provide a good estimate, and then fine-tune the parameters using GLO. Two examples have beenmore » provided to guide the reader through a general calibrating process.« less

Interference correction by extracting the information of interference dominant regions: Application to near-infrared spectra

NASA Astrophysics Data System (ADS)

Bi, Yiming; Tang, Liang; Shan, Peng; Xie, Qiong; Hu, Yong; Peng, Silong; Tan, Jie; Li, Changwen

2014-08-01

Interference such as baseline drift and light scattering can degrade the model predictability in multivariate analysis of near-infrared (NIR) spectra. Usually interference can be represented by an additive and a multiplicative factor. In order to eliminate these interferences, correction parameters are needed to be estimated from spectra. However, the spectra are often mixed of physical light scattering effects and chemical light absorbance effects, making it difficult for parameter estimation. Herein, a novel algorithm was proposed to find a spectral region automatically that the interesting chemical absorbance and noise are low, that is, finding an interference dominant region (IDR). Based on the definition of IDR, a two-step method was proposed to find the optimal IDR and the corresponding correction parameters estimated from IDR. Finally, the correction was performed to the full spectral range using previously obtained parameters for the calibration set and test set, respectively. The method can be applied to multi target systems with one IDR suitable for all targeted analytes. Tested on two benchmark data sets of near-infrared spectra, the performance of the proposed method provided considerable improvement compared with full spectral estimation methods and comparable with other state-of-art methods.

A calibration method based on virtual large planar target for cameras with large FOV

NASA Astrophysics Data System (ADS)

Yu, Lei; Han, Yangyang; Nie, Hong; Ou, Qiaofeng; Xiong, Bangshu

2018-02-01

In order to obtain high precision in camera calibration, a target should be large enough to cover the whole field of view (FOV). For cameras with large FOV, using a small target will seriously reduce the precision of calibration. However, using a large target causes many difficulties in making, carrying and employing the large target. In order to solve this problem, a calibration method based on the virtual large planar target (VLPT), which is virtually constructed with multiple small targets (STs), is proposed for cameras with large FOV. In the VLPT-based calibration method, first, the positions and directions of STs are changed several times to obtain a number of calibration images. Secondly, the VLPT of each calibration image is created by finding the virtual point corresponding to the feature points of the STs. Finally, intrinsic and extrinsic parameters of the camera are calculated by using the VLPTs. Experiment results show that the proposed method can not only achieve the similar calibration precision as those employing a large target, but also have good stability in the whole measurement area. Thus, the difficulties to accurately calibrate cameras with large FOV can be perfectly tackled by the proposed method with good operability.

A Full-Envelope Air Data Calibration and Three-Dimensional Wind Estimation Method Using Global Output-Error Optimization and Flight-Test Techniques

NASA Technical Reports Server (NTRS)

Taylor, Brian R.

2012-01-01

A novel, efficient air data calibration method is proposed for aircraft with limited envelopes. This method uses output-error optimization on three-dimensional inertial velocities to estimate calibration and wind parameters. Calibration parameters are based on assumed calibration models for static pressure, angle of attack, and flank angle. Estimated wind parameters are the north, east, and down components. The only assumptions needed for this method are that the inertial velocities and Euler angles are accurate, the calibration models are correct, and that the steady-state component of wind is constant throughout the maneuver. A two-minute maneuver was designed to excite the aircraft over the range of air data calibration parameters and de-correlate the angle-of-attack bias from the vertical component of wind. Simulation of the X-48B (The Boeing Company, Chicago, Illinois) aircraft was used to validate the method, ultimately using data derived from wind-tunnel testing to simulate the un-calibrated air data measurements. Results from the simulation were accurate and robust to turbulence levels comparable to those observed in flight. Future experiments are planned to evaluate the proposed air data calibration in a flight environment.

Effects of univariate and multivariate regression on the accuracy of hydrogen quantification with laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Ytsma, Cai R.; Dyar, M. Darby

2018-01-01

Hydrogen (H) is a critical element to measure on the surface of Mars because its presence in mineral structures is indicative of past hydrous conditions. The Curiosity rover uses the laser-induced breakdown spectrometer (LIBS) on the ChemCam instrument to analyze rocks for their H emission signal at 656.6 nm, from which H can be quantified. Previous LIBS calibrations for H used small data sets measured on standards and/or manufactured mixtures of hydrous minerals and rocks and applied univariate regression to spectra normalized in a variety of ways. However, matrix effects common to LIBS make these calibrations of limited usefulness when applied to the broad range of compositions on the Martian surface. In this study, 198 naturally-occurring hydrous geological samples covering a broad range of bulk compositions with directly-measured H content are used to create more robust prediction models for measuring H in LIBS data acquired under Mars conditions. Both univariate and multivariate prediction models, including partial least square (PLS) and the least absolute shrinkage and selection operator (Lasso), are compared using several different methods for normalization of H peak intensities. Data from the ChemLIBS Mars-analog spectrometer at Mount Holyoke College are compared against spectra from the same samples acquired using a ChemCam-like instrument at Los Alamos National Laboratory and the ChemCam instrument on Mars. Results show that all current normalization and data preprocessing variations for quantifying H result in models with statistically indistinguishable prediction errors (accuracies) ca. ± 1.5 weight percent (wt%) H2O, limiting the applications of LIBS in these implementations for geological studies. This error is too large to allow distinctions among the most common hydrous phases (basalts, amphiboles, micas) to be made, though some clays (e.g., chlorites with ≈ 12 wt% H2O, smectites with 15-20 wt% H2O) and hydrated phases (e.g., gypsum with ≈ 20 wt% H2O) may be differentiated from lower-H phases within the known errors. Analyses of the H emission peak in Curiosity calibration targets and rock and soil targets on the Martian surface suggest that shot-to-shot variations of the ChemCam laser on Mars lead to variations in intensity that are comparable to those represented by the breadth of H standards tested in this study.

A fast calibration method for 3-D tracking of ultrasound images using a spatial localizer.

PubMed

Pagoulatos, N; Haynor, D R; Kim, Y

2001-09-01

We have developed a fast calibration method for computing the position and orientation of 2-D ultrasound (US) images in 3-D space where a position sensor is mounted on the US probe. This calibration is required in the fields of 3-D ultrasound and registration of ultrasound with other imaging modalities. Most of the existing calibration methods require a complex and tedious experimental procedure. Our method is simple and it is based on a custom-built phantom. Thirty N-fiducials (markers in the shape of the letter "N") embedded in the phantom provide the basis for our calibration procedure. We calibrated a 3.5-MHz sector phased-array probe with a magnetic position sensor, and we studied the accuracy and precision of our method. A typical calibration procedure requires approximately 2 min. We conclude that we can achieve accurate and precise calibration using a single US image, provided that a large number (approximately ten) of N-fiducials are captured within the US image, enabling a representative sampling of the imaging plane.

Self-calibration method for rotating laser positioning system using interscanning technology and ultrasonic ranging.

PubMed

Wu, Jun; Yu, Zhijing; Zhuge, Jingchang

2016-04-01

A rotating laser positioning system (RLPS) is an efficient measurement method for large-scale metrology. Due to multiple transmitter stations, which consist of a measurement network, the position relationship of these stations must be first calibrated. However, with such auxiliary devices such as a laser tracker, scale bar, and complex calibration process, the traditional calibration methods greatly reduce the measurement efficiency. This paper proposes a self-calibration method for RLPS, which can automatically obtain the position relationship. The method is implemented through interscanning technology by using a calibration bar mounted on the transmitter station. Each bar is composed of three RLPS receivers and one ultrasonic sensor whose coordinates are known in advance. The calibration algorithm is mainly based on multiplane and distance constraints and is introduced in detail through a two-station mathematical model. The repeated experiments demonstrate that the coordinate measurement uncertainty of spatial points by using this method is about 0.1 mm, and the accuracy experiments show that the average coordinate measurement deviation is about 0.3 mm compared with a laser tracker. The accuracy can meet the requirements of most applications, while the calibration efficiency is significantly improved.

Coupling HYDRUS-1D Code with PA-DDS Algorithms for Inverse Calibration

NASA Astrophysics Data System (ADS)

Wang, Xiang; Asadzadeh, Masoud; Holländer, Hartmut

2017-04-01

Numerical modelling requires calibration to predict future stages. A standard method for calibration is inverse calibration where generally multi-objective optimization algorithms are used to find a solution, e.g. to find an optimal solution of the van Genuchten Mualem (VGM) parameters to predict water fluxes in the vadose zone. We coupled HYDRUS-1D with PA-DDS to add a new, robust function for inverse calibration to the model. The PA-DDS method is a recently developed multi-objective optimization algorithm, which combines Dynamically Dimensioned Search (DDS) and Pareto Archived Evolution Strategy (PAES). The results were compared to a standard method (Marquardt-Levenberg method) implemented in HYDRUS-1D. Calibration performance is evaluated using observed and simulated soil moisture at two soil layers in the Southern Abbotsford, British Columbia, Canada in the terms of the root mean squared error (RMSE) and the Nash-Sutcliffe Efficiency (NSE). Results showed low RMSE values of 0.014 and 0.017 and strong NSE values of 0.961 and 0.939. Compared to the results by the Marquardt-Levenberg method, we received better calibration results for deeper located soil sensors. However, VGM parameters were similar comparing with previous studies. Both methods are equally computational efficient. We claim that a direct implementation of PA-DDS into HYDRUS-1D should reduce the computation effort further. This, the PA-DDS method is efficient for calibrating recharge for complex vadose zone modelling with multiple soil layer and can be a potential tool for calibration of heat and solute transport. Future work should focus on the effectiveness of PA-DDS for calibrating more complex versions of the model with complex vadose zone settings, with more soil layers, and against measured heat and solute transport. Keywords: Recharge, Calibration, HYDRUS-1D, Multi-objective Optimization

Rapid analysis of glucose, fructose, sucrose, and maltose in honeys from different geographic regions using fourier transform infrared spectroscopy and multivariate analysis.

PubMed

Wang, Jun; Kliks, Michael M; Jun, Soojin; Jackson, Mel; Li, Qing X

2010-03-01

Quantitative analysis of glucose, fructose, sucrose, and maltose in different geographic origin honey samples in the world using the Fourier transform infrared (FTIR) spectroscopy and chemometrics such as partial least squares (PLS) and principal component regression was studied. The calibration series consisted of 45 standard mixtures, which were made up of glucose, fructose, sucrose, and maltose. There were distinct peak variations of all sugar mixtures in the spectral "fingerprint" region between 1500 and 800 cm(-1). The calibration model was successfully validated using 7 synthetic blend sets of sugars. The PLS 2nd-derivative model showed the highest degree of prediction accuracy with a highest R(2) value of 0.999. Along with the canonical variate analysis, the calibration model further validated by high-performance liquid chromatography measurements for commercial honey samples demonstrates that FTIR can qualitatively and quantitatively determine the presence of glucose, fructose, sucrose, and maltose in multiple regional honey samples.

Volumetric calibration of a plenoptic camera.

PubMed

Hall, Elise Munz; Fahringer, Timothy W; Guildenbecher, Daniel R; Thurow, Brian S

2018-02-01

The volumetric calibration of a plenoptic camera is explored to correct for inaccuracies due to real-world lens distortions and thin-lens assumptions in current processing methods. Two methods of volumetric calibration based on a polynomial mapping function that does not require knowledge of specific lens parameters are presented and compared to a calibration based on thin-lens assumptions. The first method, volumetric dewarping, is executed by creation of a volumetric representation of a scene using the thin-lens assumptions, which is then corrected in post-processing using a polynomial mapping function. The second method, direct light-field calibration, uses the polynomial mapping in creation of the initial volumetric representation to relate locations in object space directly to image sensor locations. The accuracy and feasibility of these methods is examined experimentally by capturing images of a known dot card at a variety of depths. Results suggest that use of a 3D polynomial mapping function provides a significant increase in reconstruction accuracy and that the achievable accuracy is similar using either polynomial-mapping-based method. Additionally, direct light-field calibration provides significant computational benefits by eliminating some intermediate processing steps found in other methods. Finally, the flexibility of this method is shown for a nonplanar calibration.

Novel crystal timing calibration method based on total variation

NASA Astrophysics Data System (ADS)

Yu, Xingjian; Isobe, Takashi; Watanabe, Mitsuo; Liu, Huafeng

2016-11-01

A novel crystal timing calibration method based on total variation (TV), abbreviated as ‘TV merge’, has been developed for a high-resolution positron emission tomography (PET) system. The proposed method was developed for a system with a large number of crystals, it can provide timing calibration at the crystal level. In the proposed method, the timing calibration process was formulated as a linear problem. To robustly optimize the timing resolution, a TV constraint was added to the linear equation. Moreover, to solve the computer memory problem associated with the calculation of the timing calibration factors for systems with a large number of crystals, the merge component was used for obtaining the crystal level timing calibration values. Compared with other conventional methods, the data measured from a standard cylindrical phantom filled with a radioisotope solution was sufficient for performing a high-precision crystal-level timing calibration. In this paper, both simulation and experimental studies were performed to demonstrate the effectiveness and robustness of the TV merge method. We compare the timing resolutions of a 22Na point source, which was located in the field of view (FOV) of the brain PET system, with various calibration techniques. After implementing the TV merge method, the timing resolution improved from 3.34 ns at full width at half maximum (FWHM) to 2.31 ns FWHM.

BESTEST-EX | Buildings | NREL

Science.gov Websites

method for testing home energy audit software and associated calibration methods. BESTEST-EX is one of Energy Analysis Model Calibration Methods. When completed, the ANSI/RESNET SMOT will specify test procedures for evaluating calibration methods used in conjunction with predicting building energy use and

At-line determination of pharmaceuticals small molecule's blending end point using chemometric modeling combined with Fourier transform near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Tewari, Jagdish; Strong, Richard; Boulas, Pierre

2017-02-01

This article summarizes the development and validation of a Fourier transform near infrared spectroscopy (FT-NIR) method for the rapid at-line prediction of active pharmaceutical ingredient (API) in a powder blend to optimize small molecule formulations. The method was used to determine the blend uniformity end-point for a pharmaceutical solid dosage formulation containing a range of API concentrations. A set of calibration spectra from samples with concentrations ranging from 1% to 15% of API (w/w) were collected at-line from 4000 to 12,500 cm- 1. The ability of the FT-NIR method to predict API concentration in the blend samples was validated against a reference high performance liquid chromatography (HPLC) method. The prediction efficiency of four different types of multivariate data modeling methods such as partial least-squares 1 (PLS1), partial least-squares 2 (PLS2), principal component regression (PCR) and artificial neural network (ANN), were compared using relevant multivariate figures of merit. The prediction ability of the regression models were cross validated against results generated with the reference HPLC method. PLS1 and ANN showed excellent and superior prediction abilities when compared to PLS2 and PCR. Based upon these results and because of its decreased complexity compared to ANN, PLS1 was selected as the best chemometric method to predict blend uniformity at-line. The FT-NIR measurement and the associated chemometric analysis were implemented in the production environment for rapid at-line determination of the end-point of the small molecule blending operation. FIGURE 1: Correlation coefficient vs Rank plot FIGURE 2: FT-NIR spectra of different steps of Blend and final blend FIGURE 3: Predictions ability of PCR FIGURE 4: Blend uniformity predication ability of PLS2 FIGURE 5: Prediction efficiency of blend uniformity using ANN FIGURE 6: Comparison of prediction efficiency of chemometric models TABLE 1: Order of Addition for Blending Steps

High-accuracy self-calibration method for dual-axis rotation-modulating RLG-INS

NASA Astrophysics Data System (ADS)

Wei, Guo; Gao, Chunfeng; Wang, Qi; Wang, Qun; Long, Xingwu

2017-05-01

Inertial navigation system has been the core component of both military and civil navigation systems. Dual-axis rotation modulation can completely eliminate the inertial elements constant errors of the three axes to improve the system accuracy. But the error caused by the misalignment angles and the scale factor error cannot be eliminated through dual-axis rotation modulation. And discrete calibration method cannot fulfill requirements of high-accurate calibration of the mechanically dithered ring laser gyroscope navigation system with shock absorbers. This paper has analyzed the effect of calibration error during one modulated period and presented a new systematic self-calibration method for dual-axis rotation-modulating RLG-INS. Procedure for self-calibration of dual-axis rotation-modulating RLG-INS has been designed. The results of self-calibration simulation experiment proved that: this scheme can estimate all the errors in the calibration error model, the calibration precision of the inertial sensors scale factor error is less than 1ppm and the misalignment is less than 5″. These results have validated the systematic self-calibration method and proved its importance for accuracy improvement of dual -axis rotation inertial navigation system with mechanically dithered ring laser gyroscope.

Uncertainty propagation in the calibration equations for NTC thermistors

NASA Astrophysics Data System (ADS)

Liu, Guang; Guo, Liang; Liu, Chunlong; Wu, Qingwen

2018-06-01

The uncertainty propagation problem is quite important for temperature measurements, since we rely so much on the sensors and calibration equations. Although uncertainty propagation for platinum resistance or radiation thermometers is well known, there have been few publications concerning negative temperature coefficient (NTC) thermistors. Insight into the propagation characteristics of uncertainty that develop when equations are determined using the Lagrange interpolation or least-squares fitting method is presented here with respect to several of the most common equations used in NTC thermistor calibration. Within this work, analytical expressions of the propagated uncertainties for both fitting methods are derived for the uncertainties in the measured temperature and resistance at each calibration point. High-precision calibration of an NTC thermistor in a precision water bath was performed by means of the comparison method. Results show that, for both fitting methods, the propagated uncertainty is flat in the interpolation region but rises rapidly beyond the calibration range. Also, for temperatures interpolated between calibration points, the propagated uncertainty is generally no greater than that associated with the calibration points. For least-squares fitting, the propagated uncertainty is significantly reduced by increasing the number of calibration points and can be well kept below the uncertainty of the calibration points.

Firefly as a novel swarm intelligence variable selection method in spectroscopy.

PubMed

Goodarzi, Mohammad; dos Santos Coelho, Leandro

2014-12-10

A critical step in multivariate calibration is wavelength selection, which is used to build models with better prediction performance when applied to spectral data. Up to now, many feature selection techniques have been developed. Among all different types of feature selection techniques, those based on swarm intelligence optimization methodologies are more interesting since they are usually simulated based on animal and insect life behavior to, e.g., find the shortest path between a food source and their nests. This decision is made by a crowd, leading to a more robust model with less falling in local minima during the optimization cycle. This paper represents a novel feature selection approach to the selection of spectroscopic data, leading to more robust calibration models. The performance of the firefly algorithm, a swarm intelligence paradigm, was evaluated and compared with genetic algorithm and particle swarm optimization. All three techniques were coupled with partial least squares (PLS) and applied to three spectroscopic data sets. They demonstrate improved prediction results in comparison to when only a PLS model was built using all wavelengths. Results show that firefly algorithm as a novel swarm paradigm leads to a lower number of selected wavelengths while the prediction performance of built PLS stays the same. Copyright © 2014. Published by Elsevier B.V.

Administrative data measured surgical site infection probability within 30 days of surgery in elderly patients.

PubMed

van Walraven, Carl; Jackson, Timothy D; Daneman, Nick

2016-09-01

Elderly patients are inordinately affected by surgical site infections (SSIs). This study derived and internally validated a model that used routinely collected health administrative data to measure the probability of SSI in elderly patients within 30 days of surgery. All people exceeding 65 years undergoing surgery from two hospitals with known SSI status were linked to population-based administrative data sets in Ontario, Canada. We used bootstrap methods to create a multivariate model that used health administrative data to predict the probability of SSI. Of 3,436 patients, 177 (5.1%) had an SSI. The Elderly SSI Risk Model included six covariates: number of distinct physician fee codes within 30 days of surgery; presence or absence of a postdischarge prescription for an antibiotic; presence or absence of three diagnostic codes; and a previously derived score that gauged SSI risk based on procedure codes. The model was highly explanatory (Nagelkerke's R 2 , 0.458), strongly discriminative (C statistic, 0.918), and well calibrated (calibration slope, 1). Health administrative data can effectively determine 30-day risk of SSI risk in elderly patients undergoing a broad assortment of surgeries. External validation is necessary before this can be routinely used to monitor SSIs in the elderly. Copyright © 2016 Elsevier Inc. All rights reserved.

Multivariate Calibration Approach for Quantitative Determination of Cell-Line Cross Contamination by Intact Cell Mass Spectrometry and Artificial Neural Networks.

PubMed

Valletta, Elisa; Kučera, Lukáš; Prokeš, Lubomír; Amato, Filippo; Pivetta, Tiziana; Hampl, Aleš; Havel, Josef; Vaňhara, Petr

2016-01-01

Cross-contamination of eukaryotic cell lines used in biomedical research represents a highly relevant problem. Analysis of repetitive DNA sequences, such as Short Tandem Repeats (STR), or Simple Sequence Repeats (SSR), is a widely accepted, simple, and commercially available technique to authenticate cell lines. However, it provides only qualitative information that depends on the extent of reference databases for interpretation. In this work, we developed and validated a rapid and routinely applicable method for evaluation of cell culture cross-contamination levels based on mass spectrometric fingerprints of intact mammalian cells coupled with artificial neural networks (ANNs). We used human embryonic stem cells (hESCs) contaminated by either mouse embryonic stem cells (mESCs) or mouse embryonic fibroblasts (MEFs) as a model. We determined the contamination level using a mass spectra database of known calibration mixtures that served as training input for an ANN. The ANN was then capable of correct quantification of the level of contamination of hESCs by mESCs or MEFs. We demonstrate that MS analysis, when linked to proper mathematical instruments, is a tangible tool for unraveling and quantifying heterogeneity in cell cultures. The analysis is applicable in routine scenarios for cell authentication and/or cell phenotyping in general.

Multivariate Calibration Approach for Quantitative Determination of Cell-Line Cross Contamination by Intact Cell Mass Spectrometry and Artificial Neural Networks

PubMed Central

Prokeš, Lubomír; Amato, Filippo; Pivetta, Tiziana; Hampl, Aleš; Havel, Josef; Vaňhara, Petr

2016-01-01

Cross-contamination of eukaryotic cell lines used in biomedical research represents a highly relevant problem. Analysis of repetitive DNA sequences, such as Short Tandem Repeats (STR), or Simple Sequence Repeats (SSR), is a widely accepted, simple, and commercially available technique to authenticate cell lines. However, it provides only qualitative information that depends on the extent of reference databases for interpretation. In this work, we developed and validated a rapid and routinely applicable method for evaluation of cell culture cross-contamination levels based on mass spectrometric fingerprints of intact mammalian cells coupled with artificial neural networks (ANNs). We used human embryonic stem cells (hESCs) contaminated by either mouse embryonic stem cells (mESCs) or mouse embryonic fibroblasts (MEFs) as a model. We determined the contamination level using a mass spectra database of known calibration mixtures that served as training input for an ANN. The ANN was then capable of correct quantification of the level of contamination of hESCs by mESCs or MEFs. We demonstrate that MS analysis, when linked to proper mathematical instruments, is a tangible tool for unraveling and quantifying heterogeneity in cell cultures. The analysis is applicable in routine scenarios for cell authentication and/or cell phenotyping in general. PMID:26821236

A New Online Calibration Method Based on Lord's Bias-Correction.

PubMed

He, Yinhong; Chen, Ping; Li, Yong; Zhang, Shumei

2017-09-01

Online calibration technique has been widely employed to calibrate new items due to its advantages. Method A is the simplest online calibration method and has attracted many attentions from researchers recently. However, a key assumption of Method A is that it treats person-parameter estimates θ ^ s (obtained by maximum likelihood estimation [MLE]) as their true values θ s , thus the deviation of the estimated θ ^ s from their true values might yield inaccurate item calibration when the deviation is nonignorable. To improve the performance of Method A, a new method, MLE-LBCI-Method A, is proposed. This new method combines a modified Lord's bias-correction method (named as maximum likelihood estimation-Lord's bias-correction with iteration [MLE-LBCI]) with the original Method A in an effort to correct the deviation of θ ^ s which may adversely affect the item calibration precision. Two simulation studies were carried out to explore the performance of both MLE-LBCI and MLE-LBCI-Method A under several scenarios. Simulation results showed that MLE-LBCI could make a significant improvement over the ML ability estimates, and MLE-LBCI-Method A did outperform Method A in almost all experimental conditions.

Simultaneous Calibration: A Joint Optimization Approach for Multiple Kinect and External Cameras.

PubMed

Liao, Yajie; Sun, Ying; Li, Gongfa; Kong, Jianyi; Jiang, Guozhang; Jiang, Du; Cai, Haibin; Ju, Zhaojie; Yu, Hui; Liu, Honghai

2017-06-24

Camera calibration is a crucial problem in many applications, such as 3D reconstruction, structure from motion, object tracking and face alignment. Numerous methods have been proposed to solve the above problem with good performance in the last few decades. However, few methods are targeted at joint calibration of multi-sensors (more than four devices), which normally is a practical issue in the real-time systems. In this paper, we propose a novel method and a corresponding workflow framework to simultaneously calibrate relative poses of a Kinect and three external cameras. By optimizing the final cost function and adding corresponding weights to the external cameras in different locations, an effective joint calibration of multiple devices is constructed. Furthermore, the method is tested in a practical platform, and experiment results show that the proposed joint calibration method can achieve a satisfactory performance in a project real-time system and its accuracy is higher than the manufacturer's calibration.

Simultaneous Calibration: A Joint Optimization Approach for Multiple Kinect and External Cameras

PubMed Central

Liao, Yajie; Sun, Ying; Li, Gongfa; Kong, Jianyi; Jiang, Guozhang; Jiang, Du; Cai, Haibin; Ju, Zhaojie; Yu, Hui; Liu, Honghai

2017-01-01

Camera calibration is a crucial problem in many applications, such as 3D reconstruction, structure from motion, object tracking and face alignment. Numerous methods have been proposed to solve the above problem with good performance in the last few decades. However, few methods are targeted at joint calibration of multi-sensors (more than four devices), which normally is a practical issue in the real-time systems. In this paper, we propose a novel method and a corresponding workflow framework to simultaneously calibrate relative poses of a Kinect and three external cameras. By optimizing the final cost function and adding corresponding weights to the external cameras in different locations, an effective joint calibration of multiple devices is constructed. Furthermore, the method is tested in a practical platform, and experiment results show that the proposed joint calibration method can achieve a satisfactory performance in a project real-time system and its accuracy is higher than the manufacturer’s calibration. PMID:28672823

Calibration procedure of Hukseflux SR25 to Establish the Diffuse Reference for the Outdoor Broadband Radiometer Calibration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reda, Ibrahim M.; Andreas, Afshin M.

2017-08-01

Accurate pyranometer calibrations, traceable to internationally recognized standards, are critical for solar irradiance measurements. One calibration method is the component summation method, where the pyranometers are calibrated outdoors under clear sky conditions, and the reference global solar irradiance is calculated as the sum of two reference components, the diffuse horizontal and subtended beam solar irradiances. The beam component is measured with pyrheliometers traceable to the World Radiometric Reference, while there is no internationally recognized reference for the diffuse component. In the absence of such a reference, we present a method to consistently calibrate pyranometers for measuring the diffuse component. Themore » method is based on using a modified shade/unshade method and a pyranometer with less than 0.5 W/m2 thermal offset. The calibration result shows that the responsivity of Hukseflux SR25 pyranometer equals 10.98 uV/(W/m2) with +/-0.86 percent uncertainty.« less

Radiation calibration for LWIR Hyperspectral Imager Spectrometer

NASA Astrophysics Data System (ADS)

Yang, Zhixiong; Yu, Chunchao; Zheng, Wei-jian; Lei, Zhenggang; Yan, Min; Yuan, Xiaochun; Zhang, Peizhong

2014-11-01

The radiometric calibration of LWIR Hyperspectral imager Spectrometer is presented. The lab has been developed to LWIR Interferometric Hyperspectral imager Spectrometer Prototype(CHIPED-I) to study Lab Radiation Calibration, Two-point linear calibration is carried out for the spectrometer by using blackbody respectively. Firstly, calibration measured relative intensity is converted to the absolute radiation lightness of the object. Then, radiation lightness of the object is is converted the brightness temperature spectrum by the method of brightness temperature. The result indicated †that this method of Radiation Calibration calibration was very good.

A proposed standard method for polarimetric calibration and calibration verification

NASA Astrophysics Data System (ADS)

Persons, Christopher M.; Jones, Michael W.; Farlow, Craig A.; Morell, L. Denise; Gulley, Michael G.; Spradley, Kevin D.

2007-09-01

Accurate calibration of polarimetric sensors is critical to reducing and analyzing phenomenology data, producing uniform polarimetric imagery for deployable sensors, and ensuring predictable performance of polarimetric algorithms. It is desirable to develop a standard calibration method, including verification reporting, in order to increase credibility with customers and foster communication and understanding within the polarimetric community. This paper seeks to facilitate discussions within the community on arriving at such standards. Both the calibration and verification methods presented here are performed easily with common polarimetric equipment, and are applicable to visible and infrared systems with either partial Stokes or full Stokes sensitivity. The calibration procedure has been used on infrared and visible polarimetric imagers over a six year period, and resulting imagery has been presented previously at conferences and workshops. The proposed calibration method involves the familiar calculation of the polarimetric data reduction matrix by measuring the polarimeter's response to a set of input Stokes vectors. With this method, however, linear combinations of Stokes vectors are used to generate highly accurate input states. This allows the direct measurement of all system effects, in contrast with fitting modeled calibration parameters to measured data. This direct measurement of the data reduction matrix allows higher order effects that are difficult to model to be discovered and corrected for in calibration. This paper begins with a detailed tutorial on the proposed calibration and verification reporting methods. Example results are then presented for a LWIR rotating half-wave retarder polarimeter.

The Impact of Indoor and Outdoor Radiometer Calibration on Solar Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habte, Aron; Sengupta, Manajit; Andreas, Afshin

2016-06-02

This study addresses the effect of calibration methodologies on calibration responsivities and the resulting impact on radiometric measurements. The calibration responsivities used in this study are provided by NREL's broadband outdoor radiometer calibration (BORCAL) and a few prominent manufacturers. The BORCAL method provides outdoor calibration responsivity of pyranometers and pyrheliometers at a 45 degree solar zenith angle and responsivity as a function of solar zenith angle determined by clear-sky comparisons to reference irradiance. The BORCAL method also employs a thermal offset correction to the calibration responsivity of single-black thermopile detectors used in pyranometers. Indoor calibrations of radiometers by their manufacturersmore » are performed using a stable artificial light source in a side-by-side comparison of the test radiometer under calibration to a reference radiometer of the same type. These different methods of calibration demonstrated 1percent to 2 percent differences in solar irradiance measurement. Analyzing these values will ultimately enable a reduction in radiometric measurement uncertainties and assist in developing consensus on a standard for calibration.« less

[Application of near infrared reflectance spectroscopy to predict meat chemical compositions: a review].

PubMed

Tao, Lin-Li; Yang, Xiu-Juan; Deng, Jun-Ming; Zhang, Xi

2013-11-01

In contrast to conventional methods for the determination of meat chemical composition, near infrared reflectance spectroscopy enables rapid, simple, secure and simultaneous assessment of numerous meat properties. The present review focuses on the use of near infrared reflectance spectroscopy to predict meat chemical compositions. The potential of near infrared reflectance spectroscopy to predict crude protein, intramuscular fat, fatty acid, moisture, ash, myoglobin and collagen of beef, pork, chicken and lamb is reviewed. This paper discusses existing questions and reasons in the current research. According to the published results, although published results vary considerably, they suggest that near-infrared reflectance spectroscopy shows a great potential to replace the expensive and time-consuming chemical analysis of meat composition. In particular, under commercial conditions where simultaneous measurements of different chemical components are required, near infrared reflectance spectroscopy is expected to be the method of choice. The majority of studies selected feature-related wavelengths using principal components regression, developed the calibration model using partial least squares and modified partial least squares, and estimated the prediction accuracy by means of cross-validation using the same sample set previously used for the calibration. Meat fatty acid composition predicted by near-infrared spectroscopy and non-destructive prediction and visualization of chemical composition in meat using near-infrared hyperspectral imaging and multivariate regression are the hot studying field now. On the other hand, near infrared reflectance spectroscopy shows great difference for predicting different attributes of meat quality which are closely related to the selection of calibration sample set, preprocessing of near-infrared spectroscopy and modeling approach. Sample preparation also has an important effect on the reliability of NIR prediction; in particular, lack of homogeneity of the meat samples influenced the accuracy of estimation of chemical components. In general the predicting results of intramuscular fat, fatty acid and moisture are best, the predicting results of crude protein and myoglobin are better, while the predicting results of ash and collagen are less accurate.

Model Robust Calibration: Method and Application to Electronically-Scanned Pressure Transducers

NASA Technical Reports Server (NTRS)

Walker, Eric L.; Starnes, B. Alden; Birch, Jeffery B.; Mays, James E.

2010-01-01

This article presents the application of a recently developed statistical regression method to the controlled instrument calibration problem. The statistical method of Model Robust Regression (MRR), developed by Mays, Birch, and Starnes, is shown to improve instrument calibration by reducing the reliance of the calibration on a predetermined parametric (e.g. polynomial, exponential, logarithmic) model. This is accomplished by allowing fits from the predetermined parametric model to be augmented by a certain portion of a fit to the residuals from the initial regression using a nonparametric (locally parametric) regression technique. The method is demonstrated for the absolute scale calibration of silicon-based pressure transducers.

Automated multivariate analysis of multi-sensor data submitted online: Real-time environmental monitoring.

PubMed

Eide, Ingvar; Westad, Frank

2018-01-01

A pilot study demonstrating real-time environmental monitoring with automated multivariate analysis of multi-sensor data submitted online has been performed at the cabled LoVe Ocean Observatory located at 258 m depth 20 km off the coast of Lofoten-Vesterålen, Norway. The major purpose was efficient monitoring of many variables simultaneously and early detection of changes and time-trends in the overall response pattern before changes were evident in individual variables. The pilot study was performed with 12 sensors from May 16 to August 31, 2015. The sensors provided data for chlorophyll, turbidity, conductivity, temperature (three sensors), salinity (calculated from temperature and conductivity), biomass at three different depth intervals (5-50, 50-120, 120-250 m), and current speed measured in two directions (east and north) using two sensors covering different depths with overlap. A total of 88 variables were monitored, 78 from the two current speed sensors. The time-resolution varied, thus the data had to be aligned to a common time resolution. After alignment, the data were interpreted using principal component analysis (PCA). Initially, a calibration model was established using data from May 16 to July 31. The data on current speed from two sensors were subject to two separate PCA models and the score vectors from these two models were combined with the other 10 variables in a multi-block PCA model. The observations from August were projected on the calibration model consecutively one at a time and the result was visualized in a score plot. Automated PCA of multi-sensor data submitted online is illustrated with an attached time-lapse video covering the relative short time period used in the pilot study. Methods for statistical validation, and warning and alarm limits are described. Redundant sensors enable sensor diagnostics and quality assurance. In a future perspective, the concept may be used in integrated environmental monitoring.

Spectral characterization and calibration of AOTF spectrometers and hyper-spectral imaging system

NASA Astrophysics Data System (ADS)

Katrašnik, Jaka; Pernuš, Franjo; Likar, Boštjan

2010-02-01

The goal of this article is to present a novel method for spectral characterization and calibration of spectrometers and hyper-spectral imaging systems based on non-collinear acousto-optical tunable filters. The method characterizes the spectral tuning curve (frequency-wavelength characteristic) of the AOTF (Acousto-Optic Tunable Filter) filter by matching the acquired and modeled spectra of the HgAr calibration lamp, which emits line spectrum that can be well modeled via AOTF transfer function. In this way, not only tuning curve characterization and corresponding spectral calibration but also spectral resolution assessment is performed. The obtained results indicated that the proposed method is efficient, accurate and feasible for routine calibration of AOTF spectrometers and hyper-spectral imaging systems and thereby a highly competitive alternative to the existing calibration methods.

Liquid chromatography with diode array detection and multivariate curve resolution for the selective and sensitive quantification of estrogens in natural waters.

PubMed

Pérez, Rocío L; Escandar, Graciela M

2014-07-04

Following the green analytical chemistry principles, an efficient strategy involving second-order data provided by liquid chromatography (LC) with diode array detection (DAD) was applied for the simultaneous determination of estriol, 17β-estradiol, 17α-ethinylestradiol and estrone in natural water samples. After a simple pre-concentration step, LC-DAD matrix data were rapidly obtained (in less than 5 min) with a chromatographic system operating isocratically. Applying a second-order calibration algorithm based on multivariate curve resolution with alternating least-squares (MCR-ALS), successful resolution was achieved in the presence of sample constituents that strongly coelute with the analytes. The flexibility of this multivariate model allowed the quantification of the four estrogens in tap, mineral, underground and river water samples. Limits of detection in the range between 3 and 13 ng L(-1), and relative prediction errors from 2 to 11% were achieved. Copyright © 2014 Elsevier B.V. All rights reserved.

The Calibration of AVHRR/3 Visible Dual Gain Using Meteosat-8 as a MODIS Calibration Transfer Medium

NASA Technical Reports Server (NTRS)

Avey, Lance; Garber, Donald; Nguyen, Louis; Minnis, Patrick

2007-01-01

This viewgraph presentation reviews the NOAA-17 AVHRR visible channels calibrated against MET-8/MODIS using dual gain regression methods. The topics include: 1) Motivation; 2) Methodology; 3) Dual Gain Regression Methods; 4) Examples of Regression methods; 5) AVHRR/3 Regression Strategy; 6) Cross-Calibration Method; 7) Spectral Response Functions; 8) MET8/NOAA-17; 9) Example of gain ratio adjustment; 10) Effect of mixed low/high count FOV; 11) Monitor dual gains over time; and 12) Conclusions

Systematic Calibration for Ultra-High Accuracy Inertial Measurement Units.

PubMed

Cai, Qingzhong; Yang, Gongliu; Song, Ningfang; Liu, Yiliang

2016-06-22

An inertial navigation system (INS) has been widely used in challenging GPS environments. With the rapid development of modern physics, an atomic gyroscope will come into use in the near future with a predicted accuracy of 5 × 10(-6)°/h or better. However, existing calibration methods and devices can not satisfy the accuracy requirements of future ultra-high accuracy inertial sensors. In this paper, an improved calibration model is established by introducing gyro g-sensitivity errors, accelerometer cross-coupling errors and lever arm errors. A systematic calibration method is proposed based on a 51-state Kalman filter and smoother. Simulation results show that the proposed calibration method can realize the estimation of all the parameters using a common dual-axis turntable. Laboratory and sailing tests prove that the position accuracy in a five-day inertial navigation can be improved about 8% by the proposed calibration method. The accuracy can be improved at least 20% when the position accuracy of the atomic gyro INS can reach a level of 0.1 nautical miles/5 d. Compared with the existing calibration methods, the proposed method, with more error sources and high order small error parameters calibrated for ultra-high accuracy inertial measurement units (IMUs) using common turntables, has a great application potential in future atomic gyro INSs.

Evaluation of the Tropical Pacific Observing System from the Data Assimilation Perspective

DTIC Science & Technology

2014-01-01

hereafter, SIDA systems) have the capacity to assimilate salinity profiles imposing a multivariate (mainly T-S) balance relationship (summarized in...Fujii et al., 2011). Current SIDA systems in operational centers generally use Ocean General Circulation Models (OGCM) with resolution typically 1...long-term (typically 20-30 years) ocean DA runs are often performed with SIDA systems in operational centers for validation and calibration of SI

IMU-based online kinematic calibration of robot manipulator.

PubMed

Du, Guanglong; Zhang, Ping

2013-01-01

Robot calibration is a useful diagnostic method for improving the positioning accuracy in robot production and maintenance. An online robot self-calibration method based on inertial measurement unit (IMU) is presented in this paper. The method requires that the IMU is rigidly attached to the robot manipulator, which makes it possible to obtain the orientation of the manipulator with the orientation of the IMU in real time. This paper proposed an efficient approach which incorporates Factored Quaternion Algorithm (FQA) and Kalman Filter (KF) to estimate the orientation of the IMU. Then, an Extended Kalman Filter (EKF) is used to estimate kinematic parameter errors. Using this proposed orientation estimation method will result in improved reliability and accuracy in determining the orientation of the manipulator. Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. Experimental studies on a GOOGOL GRB3016 robot show that this method has better accuracy, convenience, and effectiveness than vision-based methods.

SU-E-I-38: Improved Metal Artifact Correction Using Adaptive Dual Energy Calibration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, X; Elder, E; Roper, J

2015-06-15

Purpose: The empirical dual energy calibration (EDEC) method corrects for beam-hardening artifacts, but shows limited performance on metal artifact correction. In this work, we propose an adaptive dual energy calibration (ADEC) method to correct for metal artifacts. Methods: The empirical dual energy calibration (EDEC) method corrects for beam-hardening artifacts, but shows limited performance on metal artifact correction. In this work, we propose an adaptive dual energy calibration (ADEC) method to correct for metal artifacts. Results: Highly attenuating copper rods cause severe streaking artifacts on standard CT images. EDEC improves the image quality, but cannot eliminate the streaking artifacts. Compared tomore » EDEC, the proposed ADEC method further reduces the streaking resulting from metallic inserts and beam-hardening effects and obtains material decomposition images with significantly improved accuracy. Conclusion: We propose an adaptive dual energy calibration method to correct for metal artifacts. ADEC is evaluated with the Shepp-Logan phantom, and shows superior metal artifact correction performance. In the future, we will further evaluate the performance of the proposed method with phantom and patient data.« less

A holistic calibration method with iterative distortion compensation for stereo deflectometry

NASA Astrophysics Data System (ADS)

Xu, Yongjia; Gao, Feng; Zhang, Zonghua; Jiang, Xiangqian

2018-07-01

This paper presents a novel holistic calibration method for stereo deflectometry system to improve the system measurement accuracy. The reconstruction result of stereo deflectometry is integrated with the calculated normal data of the measured surface. The calculation accuracy of the normal data is seriously influenced by the calibration accuracy of the geometrical relationship of the stereo deflectometry system. Conventional calibration approaches introduce form error to the system due to inaccurate imaging model and distortion elimination. The proposed calibration method compensates system distortion based on an iterative algorithm instead of the conventional distortion mathematical model. The initial value of the system parameters are calculated from the fringe patterns displayed on the systemic LCD screen through a reflection of a markless flat mirror. An iterative algorithm is proposed to compensate system distortion and optimize camera imaging parameters and system geometrical relation parameters based on a cost function. Both simulation work and experimental results show the proposed calibration method can significantly improve the calibration and measurement accuracy of a stereo deflectometry. The PV (peak value) of measurement error of a flat mirror can be reduced to 69.7 nm by applying the proposed method from 282 nm obtained with the conventional calibration approach.

Multimodal Spatial Calibration for Accurately Registering EEG Sensor Positions

PubMed Central

Chen, Shengyong; Xiao, Gang; Li, Xiaoli

2014-01-01

This paper proposes a fast and accurate calibration method to calibrate multiple multimodal sensors using a novel photogrammetry system for fast localization of EEG sensors. The EEG sensors are placed on human head and multimodal sensors are installed around the head to simultaneously obtain all EEG sensor positions. A multiple views' calibration process is implemented to obtain the transformations of multiple views. We first develop an efficient local repair algorithm to improve the depth map, and then a special calibration body is designed. Based on them, accurate and robust calibration results can be achieved. We evaluate the proposed method by corners of a chessboard calibration plate. Experimental results demonstrate that the proposed method can achieve good performance, which can be further applied to EEG source localization applications on human brain. PMID:24803954

Volumetric calibration of a plenoptic camera

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hall, Elise Munz; Fahringer, Timothy W.; Guildenbecher, Daniel Robert

Here, the volumetric calibration of a plenoptic camera is explored to correct for inaccuracies due to real-world lens distortions and thin-lens assumptions in current processing methods. Two methods of volumetric calibration based on a polynomial mapping function that does not require knowledge of specific lens parameters are presented and compared to a calibration based on thin-lens assumptions. The first method, volumetric dewarping, is executed by creation of a volumetric representation of a scene using the thin-lens assumptions, which is then corrected in post-processing using a polynomial mapping function. The second method, direct light-field calibration, uses the polynomial mapping in creationmore » of the initial volumetric representation to relate locations in object space directly to image sensor locations. The accuracy and feasibility of these methods is examined experimentally by capturing images of a known dot card at a variety of depths. Results suggest that use of a 3D polynomial mapping function provides a significant increase in reconstruction accuracy and that the achievable accuracy is similar using either polynomial-mapping-based method. Additionally, direct light-field calibration provides significant computational benefits by eliminating some intermediate processing steps found in other methods. Finally, the flexibility of this method is shown for a nonplanar calibration.« less

Volumetric calibration of a plenoptic camera

DOE PAGES

Hall, Elise Munz; Fahringer, Timothy W.; Guildenbecher, Daniel Robert; ...

2018-02-01

Here, the volumetric calibration of a plenoptic camera is explored to correct for inaccuracies due to real-world lens distortions and thin-lens assumptions in current processing methods. Two methods of volumetric calibration based on a polynomial mapping function that does not require knowledge of specific lens parameters are presented and compared to a calibration based on thin-lens assumptions. The first method, volumetric dewarping, is executed by creation of a volumetric representation of a scene using the thin-lens assumptions, which is then corrected in post-processing using a polynomial mapping function. The second method, direct light-field calibration, uses the polynomial mapping in creationmore » of the initial volumetric representation to relate locations in object space directly to image sensor locations. The accuracy and feasibility of these methods is examined experimentally by capturing images of a known dot card at a variety of depths. Results suggest that use of a 3D polynomial mapping function provides a significant increase in reconstruction accuracy and that the achievable accuracy is similar using either polynomial-mapping-based method. Additionally, direct light-field calibration provides significant computational benefits by eliminating some intermediate processing steps found in other methods. Finally, the flexibility of this method is shown for a nonplanar calibration.« less

Blind calibration of radio interferometric arrays using sparsity constraints and its implications for self-calibration

NASA Astrophysics Data System (ADS)

Chiarucci, Simone; Wijnholds, Stefan J.

2018-02-01

Blind calibration, i.e. calibration without a priori knowledge of the source model, is robust to the presence of unknown sources such as transient phenomena or (low-power) broad-band radio frequency interference that escaped detection. In this paper, we present a novel method for blind calibration of a radio interferometric array assuming that the observed field only contains a small number of discrete point sources. We show the huge computational advantage over previous blind calibration methods and we assess its statistical efficiency and robustness to noise and the quality of the initial estimate. We demonstrate the method on actual data from a Low-Frequency Array low-band antenna station showing that our blind calibration is able to recover the same gain solutions as the regular calibration approach, as expected from theory and simulations. We also discuss the implications of our findings for the robustness of regular self-calibration to poor starting models.

An Accurate Projector Calibration Method Based on Polynomial Distortion Representation

PubMed Central

Liu, Miao; Sun, Changku; Huang, Shujun; Zhang, Zonghua

2015-01-01

In structure light measurement systems or 3D printing systems, the errors caused by optical distortion of a digital projector always affect the precision performance and cannot be ignored. Existing methods to calibrate the projection distortion rely on calibration plate and photogrammetry, so the calibration performance is largely affected by the quality of the plate and the imaging system. This paper proposes a new projector calibration approach that makes use of photodiodes to directly detect the light emitted from a digital projector. By analyzing the output sequence of the photoelectric module, the pixel coordinates can be accurately obtained by the curve fitting method. A polynomial distortion representation is employed to reduce the residuals of the traditional distortion representation model. Experimental results and performance evaluation show that the proposed calibration method is able to avoid most of the disadvantages in traditional methods and achieves a higher accuracy. This proposed method is also practically applicable to evaluate the geometric optical performance of other optical projection system. PMID:26492247

Novel Calibration Algorithm for a Three-Axis Strapdown Magnetometer

PubMed Central

Liu, Yan Xia; Li, Xi Sheng; Zhang, Xiao Juan; Feng, Yi Bo

2014-01-01

A complete error calibration model with 12 independent parameters is established by analyzing the three-axis magnetometer error mechanism. The said model conforms to an ellipsoid restriction, the parameters of the ellipsoid equation are estimated, and the ellipsoid coefficient matrix is derived. However, the calibration matrix cannot be determined completely, as there are fewer ellipsoid parameters than calibration model parameters. Mathematically, the calibration matrix derived from the ellipsoid coefficient matrix by a different matrix decomposition method is not unique, and there exists an unknown rotation matrix R between them. This paper puts forward a constant intersection angle method (angles between the geomagnetic field and gravitational field are fixed) to estimate R. The Tikhonov method is adopted to solve the problem that rounding errors or other errors may seriously affect the calculation results of R when the condition number of the matrix is very large. The geomagnetic field vector and heading error are further corrected by R. The constant intersection angle method is convenient and practical, as it is free from any additional calibration procedure or coordinate transformation. In addition, the simulation experiment indicates that the heading error declines from ±1° calibrated by classical ellipsoid fitting to ±0.2° calibrated by a constant intersection angle method, and the signal-to-noise ratio is 50 dB. The actual experiment exhibits that the heading error is further corrected from ±0.8° calibrated by the classical ellipsoid fitting to ±0.3° calibrated by a constant intersection angle method. PMID:24831110

Application of single-image camera calibration for ultrasound augmented laparoscopic visualization

NASA Astrophysics Data System (ADS)

Liu, Xinyang; Su, He; Kang, Sukryool; Kane, Timothy D.; Shekhar, Raj

2015-03-01

Accurate calibration of laparoscopic cameras is essential for enabling many surgical visualization and navigation technologies such as the ultrasound-augmented visualization system that we have developed for laparoscopic surgery. In addition to accuracy and robustness, there is a practical need for a fast and easy camera calibration method that can be performed on demand in the operating room (OR). Conventional camera calibration methods are not suitable for the OR use because they are lengthy and tedious. They require acquisition of multiple images of a target pattern in its entirety to produce satisfactory result. In this work, we evaluated the performance of a single-image camera calibration tool (rdCalib; Percieve3D, Coimbra, Portugal) featuring automatic detection of corner points in the image, whether partial or complete, of a custom target pattern. Intrinsic camera parameters of a 5-mm and a 10-mm standard Stryker® laparoscopes obtained using rdCalib and the well-accepted OpenCV camera calibration method were compared. Target registration error (TRE) as a measure of camera calibration accuracy for our optical tracking-based AR system was also compared between the two calibration methods. Based on our experiments, the single-image camera calibration yields consistent and accurate results (mean TRE = 1.18 ± 0.35 mm for the 5-mm scope and mean TRE = 1.13 ± 0.32 mm for the 10-mm scope), which are comparable to the results obtained using the OpenCV method with 30 images. The new single-image camera calibration method is promising to be applied to our augmented reality visualization system for laparoscopic surgery.

Application of single-image camera calibration for ultrasound augmented laparoscopic visualization

PubMed Central

Liu, Xinyang; Su, He; Kang, Sukryool; Kane, Timothy D.; Shekhar, Raj

2017-01-01

Accurate calibration of laparoscopic cameras is essential for enabling many surgical visualization and navigation technologies such as the ultrasound-augmented visualization system that we have developed for laparoscopic surgery. In addition to accuracy and robustness, there is a practical need for a fast and easy camera calibration method that can be performed on demand in the operating room (OR). Conventional camera calibration methods are not suitable for the OR use because they are lengthy and tedious. They require acquisition of multiple images of a target pattern in its entirety to produce satisfactory result. In this work, we evaluated the performance of a single-image camera calibration tool (rdCalib; Percieve3D, Coimbra, Portugal) featuring automatic detection of corner points in the image, whether partial or complete, of a custom target pattern. Intrinsic camera parameters of a 5-mm and a 10-mm standard Stryker® laparoscopes obtained using rdCalib and the well-accepted OpenCV camera calibration method were compared. Target registration error (TRE) as a measure of camera calibration accuracy for our optical tracking-based AR system was also compared between the two calibration methods. Based on our experiments, the single-image camera calibration yields consistent and accurate results (mean TRE = 1.18 ± 0.35 mm for the 5-mm scope and mean TRE = 1.13 ± 0.32 mm for the 10-mm scope), which are comparable to the results obtained using the OpenCV method with 30 images. The new single-image camera calibration method is promising to be applied to our augmented reality visualization system for laparoscopic surgery. PMID:28943703

Application of single-image camera calibration for ultrasound augmented laparoscopic visualization.

PubMed

Liu, Xinyang; Su, He; Kang, Sukryool; Kane, Timothy D; Shekhar, Raj

2015-03-01

Accurate calibration of laparoscopic cameras is essential for enabling many surgical visualization and navigation technologies such as the ultrasound-augmented visualization system that we have developed for laparoscopic surgery. In addition to accuracy and robustness, there is a practical need for a fast and easy camera calibration method that can be performed on demand in the operating room (OR). Conventional camera calibration methods are not suitable for the OR use because they are lengthy and tedious. They require acquisition of multiple images of a target pattern in its entirety to produce satisfactory result. In this work, we evaluated the performance of a single-image camera calibration tool ( rdCalib ; Percieve3D, Coimbra, Portugal) featuring automatic detection of corner points in the image, whether partial or complete, of a custom target pattern. Intrinsic camera parameters of a 5-mm and a 10-mm standard Stryker ® laparoscopes obtained using rdCalib and the well-accepted OpenCV camera calibration method were compared. Target registration error (TRE) as a measure of camera calibration accuracy for our optical tracking-based AR system was also compared between the two calibration methods. Based on our experiments, the single-image camera calibration yields consistent and accurate results (mean TRE = 1.18 ± 0.35 mm for the 5-mm scope and mean TRE = 1.13 ± 0.32 mm for the 10-mm scope), which are comparable to the results obtained using the OpenCV method with 30 images. The new single-image camera calibration method is promising to be applied to our augmented reality visualization system for laparoscopic surgery.

A novel calibration method of focused light field camera for 3-D reconstruction of flame temperature

NASA Astrophysics Data System (ADS)

Sun, Jun; Hossain, Md. Moinul; Xu, Chuan-Long; Zhang, Biao; Wang, Shi-Min

2017-05-01

This paper presents a novel geometric calibration method for focused light field camera to trace the rays of flame radiance and to reconstruct the three-dimensional (3-D) temperature distribution of a flame. A calibration model is developed to calculate the corner points and their projections of the focused light field camera. The characteristics of matching main lens and microlens f-numbers are used as an additional constrains for the calibration. Geometric parameters of the focused light field camera are then achieved using Levenberg-Marquardt algorithm. Total focused images in which all the points are in focus, are utilized to validate the proposed calibration method. Calibration results are presented and discussed in details. The maximum mean relative error of the calibration is found less than 0.13%, indicating that the proposed method is capable of calibrating the focused light field camera successfully. The parameters obtained by the calibration are then utilized to trace the rays of flame radiance. A least square QR-factorization algorithm with Plank's radiation law is used to reconstruct the 3-D temperature distribution of a flame. Experiments were carried out on an ethylene air fired combustion test rig to reconstruct the temperature distribution of flames. The flame temperature obtained by the proposed method is then compared with that obtained by using high-precision thermocouple. The difference between the two measurements was found no greater than 6.7%. Experimental results demonstrated that the proposed calibration method and the applied measurement technique perform well in the reconstruction of the flame temperature.

Comparison of infusion pumps calibration methods

NASA Astrophysics Data System (ADS)

Batista, Elsa; Godinho, Isabel; do Céu Ferreira, Maria; Furtado, Andreia; Lucas, Peter; Silva, Claudia

2017-12-01

Nowadays, several types of infusion pump are commonly used for drug delivery, such as syringe pumps and peristaltic pumps. These instruments present different measuring features and capacities according to their use and therapeutic application. In order to ensure the metrological traceability of these flow and volume measuring equipment, it is necessary to use suitable calibration methods and standards. Two different calibration methods can be used to determine the flow error of infusion pumps. One is the gravimetric method, considered as a primary method, commonly used by National Metrology Institutes. The other calibration method, a secondary method, relies on an infusion device analyser (IDA) and is typically used by hospital maintenance offices. The suitability of the IDA calibration method was assessed by testing several infusion instruments at different flow rates using the gravimetric method. In addition, a measurement comparison between Portuguese Accredited Laboratories and hospital maintenance offices was performed under the coordination of the Portuguese Institute for Quality, the National Metrology Institute. The obtained results were directly related to the used calibration method and are presented in this paper. This work has been developed in the framework of the EURAMET projects EMRP MeDD and EMPIR 15SIP03.

Low Frequency Error Analysis and Calibration for High-Resolution Optical Satellite's Uncontrolled Geometric Positioning

NASA Astrophysics Data System (ADS)

Wang, Mi; Fang, Chengcheng; Yang, Bo; Cheng, Yufeng

2016-06-01

The low frequency error is a key factor which has affected uncontrolled geometry processing accuracy of the high-resolution optical image. To guarantee the geometric quality of imagery, this paper presents an on-orbit calibration method for the low frequency error based on geometric calibration field. Firstly, we introduce the overall flow of low frequency error on-orbit analysis and calibration, which includes optical axis angle variation detection of star sensor, relative calibration among star sensors, multi-star sensor information fusion, low frequency error model construction and verification. Secondly, we use optical axis angle change detection method to analyze the law of low frequency error variation. Thirdly, we respectively use the method of relative calibration and information fusion among star sensors to realize the datum unity and high precision attitude output. Finally, we realize the low frequency error model construction and optimal estimation of model parameters based on DEM/DOM of geometric calibration field. To evaluate the performance of the proposed calibration method, a certain type satellite's real data is used. Test results demonstrate that the calibration model in this paper can well describe the law of the low frequency error variation. The uncontrolled geometric positioning accuracy of the high-resolution optical image in the WGS-84 Coordinate Systems is obviously improved after the step-wise calibration.

Non-destructive geographical traceability of sea cucumber (Apostichopus japonicus) using near infrared spectroscopy combined with chemometric methods

PubMed Central

Cai, Rui; Wang, Shisheng; Tang, Bo; Li, Yueqing; Zhao, Weijie

2018-01-01

Sea cucumber is the major tonic seafood worldwide, and geographical origin traceability is an important part of its quality and safety control. In this work, a non-destructive method for origin traceability of sea cucumber (Apostichopus japonicus) from northern China Sea and East China Sea using near infrared spectroscopy (NIRS) and multivariate analysis methods was proposed. Total fat contents of 189 fresh sea cucumber samples were determined and partial least-squares (PLS) regression was used to establish the quantitative NIRS model. The ordered predictor selection algorithm was performed to select feasible wavelength regions for the construction of PLS and identification models. The identification model was developed by principal component analysis combined with Mahalanobis distance and scaling to the first range algorithms. In the test set of the optimum PLS models, the root mean square error of prediction was 0.45, and correlation coefficient was 0.90. The correct classification rates of 100% were obtained in both identification calibration model and test model. The overall results indicated that NIRS method combined with chemometric analysis was a suitable tool for origin traceability and identification of fresh sea cucumber samples from nine origins in China. PMID:29410795

Non-destructive geographical traceability of sea cucumber (Apostichopus japonicus) using near infrared spectroscopy combined with chemometric methods.

PubMed

Guo, Xiuhan; Cai, Rui; Wang, Shisheng; Tang, Bo; Li, Yueqing; Zhao, Weijie

2018-01-01

Sea cucumber is the major tonic seafood worldwide, and geographical origin traceability is an important part of its quality and safety control. In this work, a non-destructive method for origin traceability of sea cucumber ( Apostichopus japonicus ) from northern China Sea and East China Sea using near infrared spectroscopy (NIRS) and multivariate analysis methods was proposed. Total fat contents of 189 fresh sea cucumber samples were determined and partial least-squares (PLS) regression was used to establish the quantitative NIRS model. The ordered predictor selection algorithm was performed to select feasible wavelength regions for the construction of PLS and identification models. The identification model was developed by principal component analysis combined with Mahalanobis distance and scaling to the first range algorithms. In the test set of the optimum PLS models, the root mean square error of prediction was 0.45, and correlation coefficient was 0.90. The correct classification rates of 100% were obtained in both identification calibration model and test model. The overall results indicated that NIRS method combined with chemometric analysis was a suitable tool for origin traceability and identification of fresh sea cucumber samples from nine origins in China.

On-Demand Calibration and Evaluation for Electromagnetically Tracked Laparoscope in Augmented Reality Visualization

PubMed Central

Liu, Xinyang; Plishker, William; Zaki, George; Kang, Sukryool; Kane, Timothy D.; Shekhar, Raj

2017-01-01

Purpose Common camera calibration methods employed in current laparoscopic augmented reality systems require the acquisition of multiple images of an entire checkerboard pattern from various poses. This lengthy procedure prevents performing laparoscope calibration in the operating room (OR). The purpose of this work was to develop a fast calibration method for electromagnetically (EM) tracked laparoscopes, such that calibration can be performed in the OR on demand. Methods We designed a mechanical tracking mount to uniquely and snugly position an EM sensor to an appropriate location on a conventional laparoscope. A tool named fCalib was developed to calibrate intrinsic camera parameters, distortion coefficients, and extrinsic parameters (transformation between the scope lens coordinate system and the EM sensor coordinate system) using a single image that shows an arbitrary portion of a special target pattern. For quick evaluation of calibration result in the OR, we integrated a tube phantom with fCalib and overlaid a virtual representation of the tube on the live video scene. Results We compared spatial target registration error between the common OpenCV method and the fCalib method in a laboratory setting. In addition, we compared the calibration re-projection error between the EM tracking-based fCalib and the optical tracking-based fCalib in a clinical setting. Our results suggested that the proposed method is comparable to the OpenCV method. However, changing the environment, e.g., inserting or removing surgical tools, would affect re-projection accuracy for the EM tracking-based approach. Computational time of the fCalib method averaged 14.0 s (range 3.5 s – 22.7 s). Conclusions We developed and validated a prototype for fast calibration and evaluation of EM tracked conventional (forward viewing) laparoscopes. The calibration method achieved acceptable accuracy and was relatively fast and easy to be performed in the OR on demand. PMID:27250853

A Semi-parametric Multivariate Gap-filling Model for Eddy Covariance Latent Heat Flux

NASA Astrophysics Data System (ADS)

Li, M.; Chen, Y.

2010-12-01

Quantitative descriptions of latent heat fluxes are important to study the water and energy exchanges between terrestrial ecosystems and the atmosphere. The eddy covariance approaches have been recognized as the most reliable technique for measuring surface fluxes over time scales ranging from hours to years. However, unfavorable micrometeorological conditions, instrument failures, and applicable measurement limitations may cause inevitable flux gaps in time series data. Development and application of suitable gap-filling techniques are crucial to estimate long term fluxes. In this study, a semi-parametric multivariate gap-filling model was developed to fill latent heat flux gaps for eddy covariance measurements. Our approach combines the advantages of a multivariate statistical analysis (principal component analysis, PCA) and a nonlinear interpolation technique (K-nearest-neighbors, KNN). The PCA method was first used to resolve the multicollinearity relationships among various hydrometeorological factors, such as radiation, soil moisture deficit, LAI, and wind speed. The KNN method was then applied as a nonlinear interpolation tool to estimate the flux gaps as the weighted sum latent heat fluxes with the K-nearest distances in the PCs’ domain. Two years, 2008 and 2009, of eddy covariance and hydrometeorological data from a subtropical mixed evergreen forest (the Lien-Hua-Chih Site) were collected to calibrate and validate the proposed approach with artificial gaps after standard QC/QA procedures. The optimal K values and weighting factors were determined by the maximum likelihood test. The results of gap-filled latent heat fluxes conclude that developed model successful preserving energy balances of daily, monthly, and yearly time scales. Annual amounts of evapotranspiration from this study forest were 747 mm and 708 mm for 2008 and 2009, respectively. Nocturnal evapotranspiration was estimated with filled gaps and results are comparable with other studies. Seasonal and daily variability of latent heat fluxes were also discussed.

Energy expenditure estimation in beta-blocker-medicated cardiac patients by combining heart rate and body movement data.

PubMed

Kraal, Jos J; Sartor, Francesco; Papini, Gabriele; Stut, Wim; Peek, Niels; Kemps, Hareld Mc; Bonomi, Alberto G

2016-11-01

Accurate assessment of energy expenditure provides an opportunity to monitor physical activity during cardiac rehabilitation. However, the available assessment methods, based on the combination of heart rate (HR) and body movement data, are not applicable for patients using beta-blocker medication. Therefore, we developed an energy expenditure prediction model for beta-blocker-medicated cardiac rehabilitation patients. Sixteen male cardiac rehabilitation patients (age: 55.8 ± 7.3 years, weight: 93.1 ± 11.8 kg) underwent a physical activity protocol with 11 low- to moderate-intensity common daily life activities. Energy expenditure was assessed using a portable indirect calorimeter. HR and body movement data were recorded during the protocol using unobtrusive wearable devices. In addition, patients underwent a symptom-limited exercise test and resting metabolic rate assessment. Energy expenditure estimation models were developed using multivariate regression analyses based on HR and body movement data and/or patient characteristics. In addition, a HR-flex model was developed. The model combining HR and body movement data and patient characteristics showed the highest correlation and lowest error (r 2  = 0.84, root mean squared error = 0.834 kcal/minute) with total energy expenditure. The method based on individual calibration data (HR-flex) showed lower accuracy (i 2  = 0.83, root mean squared error = 0.992 kcal/minute). Our results show that combining HR and body movement data improves the accuracy of energy expenditure prediction models in cardiac patients, similar to methods that have been developed for healthy subjects. The proposed methodology does not require individual calibration and is based on the data that are available in clinical practice. © The European Society of Cardiology 2016.

Chemometrics enhanced HPLC-DAD performance for rapid quantification of carbamazepine and phenobarbital in human serum samples.

PubMed

Vosough, Maryam; Ghafghazi, Shiva; Sabetkasaei, Masoumeh

2014-02-01

This paper describes development and validation of a simple and efficient bioanalytical procedure for simultaneous determination of phenobarbital and carbamazepine in human serum samples using high performance liquid chromatography with photodiode-array detection (HPLC-DAD) regarding a fast elution methodology in less than 5 min. Briefly, this method consisted of a simple deproteinization step of serum samples followed by HPLC analysis on a Bonus-RP column using an isocratic mode of elution with acetonitrile/K2HPO4 (pH=7.5) buffer solution (45:55). Due to the presence of serum endogenous components as non-calibrated components in the sample, second-order calibration based on multivariate curve resolution-alternating least squares (MCR-ALS), has been applied on a set of absorbance matrices collected as a function of retention time and wavelengths. Acceptable resolution and quantification results were achieved in the presence of matrix interferences and the second-order advantage was fully exploited. The average recoveries for carbamazepine and phenobarbital were 89.7% and 86.1% and relative standard deviation values were lower than 9%. Additionally, computed elliptical joint confidence region (EJCR) confirmed the accuracy of the proposed method and indicated the absence of both constant and proportional errors in the predicted concentrations. The developed method enabled the determination of the analytes in different serum samples in the presence of overlapped profiles, while keeping experimental time and extraction steps at minimum. Finally, the serum concentration levels of carbamazepine in three time intervals were reported for morphine-dependents who had received carbamazepine for treating their neuropathic pain. © 2013 Elsevier B.V. All rights reserved.

A Prognostic Indicator for Patients Hospitalized with Heart Failure.

PubMed

Snow, Richard; Vogel, Karen; Vanderhoff, Bruce; Kelch, Benjamin P; Ferris, Frank D

2016-12-01

Current methods for identifying patients at risk of dying within six months suffer from clinician biases resulting in underestimation of this risk. As a result, patients who are potentially eligible for hospice and palliative care services frequently do not benefit from these services until they are very close to the end of their lives. To develop a prospective prognostic indicator based on actual survival within Centers for Medicare and Medicaid Services (CMS) claims data that identifies patients with congestive heart failure (CHF) who are at risk of six-month mortality. CMS claims data from January 1, 2008 to June 30, 2009 were reviewed to find the first hospitalization for CHF patients with episode of care diagnosis-related groups (DRGs) 291, 292, and 293. Univariate and multivariable analyses were used to determine the associations between demographic and clinical factors and six-month mortality. The resulting model was evaluated for discrimination and calibration. The resulting prospective prognostic model demonstrated fair discrimination with an ROC of 0.71 and good calibration with a Hosmer-Lemshow statistic of 0.98. Across all DRGs, 5% of discharged patients had a six-month mortality risk of greater than 50%. This prospective approach appears to provide a method to identify patients with CHF who would potentially benefit from a clinical evaluation for referral to hospice care or for a palliative care consult due to high predicted risk of dying within 180 days after discharge from a hospital. This approach can provide a model to match at-risk patients with evidenced-based care in a more consistent manner. This method of identifying patients at risk needs further prospective evaluation to see if it has value for clinicians, increases referrals to hospice and palliative care services, and benefits patients and families.

Design of an ultra-portable field transfer radiometer supporting automated vicarious calibration

NASA Astrophysics Data System (ADS)

Anderson, Nikolaus; Thome, Kurtis; Czapla-Myers, Jeffrey; Biggar, Stuart

2015-09-01

The University of Arizona Remote Sensing Group (RSG) began outfitting the radiometric calibration test site (RadCaTS) at Railroad Valley Nevada in 2004 for automated vicarious calibration of Earth-observing sensors. RadCaTS was upgraded to use RSG custom 8-band ground viewing radiometers (GVRs) beginning in 2011 and currently four GVRs are deployed providing an average reflectance for the test site. This measurement of ground reflectance is the most critical component of vicarious calibration using the reflectance-based method. In order to ensure the quality of these measurements, RSG has been exploring more efficient and accurate methods of on-site calibration evaluation. This work describes the design of, and initial results from, a small portable transfer radiometer for the purpose of GVR calibration validation on site. Prior to deployment, RSG uses high accuracy laboratory calibration methods in order to provide radiance calibrations with low uncertainties for each GVR. After deployment, a solar radiation based calibration has typically been used. The method is highly dependent on a clear, stable atmosphere, requires at least two people to perform, is time consuming in post processing, and is dependent on several large pieces of equipment. In order to provide more regular and more accurate calibration monitoring, the small portable transfer radiometer is designed for quick, one-person operation and on-site field calibration comparison results. The radiometer is also suited for laboratory calibration use and thus could be used as a transfer radiometer calibration standard for ground viewing radiometers of a RadCalNet site.

The analytical calibration in (bio)imaging/mapping of the metallic elements in biological samples--definitions, nomenclature and strategies: state of the art.

PubMed

Jurowski, Kamil; Buszewski, Bogusław; Piekoszewski, Wojciech

2015-01-01

Nowadays, studies related to the distribution of metallic elements in biological samples are one of the most important issues. There are many articles dedicated to specific analytical atomic spectrometry techniques used for mapping/(bio)imaging the metallic elements in various kinds of biological samples. However, in such literature, there is a lack of articles dedicated to reviewing calibration strategies, and their problems, nomenclature, definitions, ways and methods used to obtain quantitative distribution maps. The aim of this article was to characterize the analytical calibration in the (bio)imaging/mapping of the metallic elements in biological samples including (1) nomenclature; (2) definitions, and (3) selected and sophisticated, examples of calibration strategies with analytical calibration procedures applied in the different analytical methods currently used to study an element's distribution in biological samples/materials such as LA ICP-MS, SIMS, EDS, XRF and others. The main emphasis was placed on the procedures and methodology of the analytical calibration strategy. Additionally, the aim of this work is to systematize the nomenclature for the calibration terms: analytical calibration, analytical calibration method, analytical calibration procedure and analytical calibration strategy. The authors also want to popularize the division of calibration methods that are different than those hitherto used. This article is the first work in literature that refers to and emphasizes many different and complex aspects of analytical calibration problems in studies related to (bio)imaging/mapping metallic elements in different kinds of biological samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Automatic Calibration Method for Driver’s Head Orientation in Natural Driving Environment

PubMed Central

Fu, Xianping; Guan, Xiao; Peli, Eli; Liu, Hongbo; Luo, Gang

2013-01-01

Gaze tracking is crucial for studying driver’s attention, detecting fatigue, and improving driver assistance systems, but it is difficult in natural driving environments due to nonuniform and highly variable illumination and large head movements. Traditional calibrations that require subjects to follow calibrators are very cumbersome to be implemented in daily driving situations. A new automatic calibration method, based on a single camera for determining the head orientation and which utilizes the side mirrors, the rear-view mirror, the instrument board, and different zones in the windshield as calibration points, is presented in this paper. Supported by a self-learning algorithm, the system tracks the head and categorizes the head pose in 12 gaze zones based on facial features. The particle filter is used to estimate the head pose to obtain an accurate gaze zone by updating the calibration parameters. Experimental results show that, after several hours of driving, the automatic calibration method without driver’s corporation can achieve the same accuracy as a manual calibration method. The mean error of estimated eye gazes was less than 5°in day and night driving. PMID:24639620

Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robertson, J.; Polly, B.; Collis, J.

2013-09-01

This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define 'explicit' input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAEmore » 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.« less

Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

and Ben Polly, Joseph Robertson; Polly, Ben; Collis, Jon

2013-09-01

This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define "explicit" input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAEmore » 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.« less

Correlation of porous and functional properties of food materials by NMR relaxometry and multivariate analysis.

PubMed

Haiduc, Adrian Marius; van Duynhoven, John

2005-02-01

The porous properties of food materials are known to determine important macroscopic parameters such as water-holding capacity and texture. In conventional approaches, understanding is built from a long process of establishing macrostructure-property relations in a rational manner. Only recently, multivariate approaches were introduced for the same purpose. The model systems used here are oil-in-water emulsions, stabilised by protein, and form complex structures, consisting of fat droplets dispersed in a porous protein phase. NMR time-domain decay curves were recorded for emulsions with varied levels of fat, protein and water. Hardness, dry matter content and water drainage were determined by classical means and analysed for correlation with the NMR data with multivariate techniques. Partial least squares can calibrate and predict these properties directly from the continuous NMR exponential decays and yields regression coefficients higher than 82%. However, the calibration coefficients themselves belong to the continuous exponential domain and do little to explain the connection between NMR data and emulsion properties. Transformation of the NMR decays into a discreet domain with non-negative least squares permits the use of multilinear regression (MLR) on the resulting amplitudes as predictors and hardness or water drainage as responses. The MLR coefficients show that hardness is highly correlated with the components that have T2 distributions of about 20 and 200 ms whereas water drainage is correlated with components that have T2 distributions around 400 and 1800 ms. These T2 distributions very likely correlate with water populations present in pores with different sizes and/or wall mobility. The results for the emulsions studied demonstrate that NMR time-domain decays can be employed to predict properties and to provide insight in the underlying microstructural features.

Fast wavelength calibration method for spectrometers based on waveguide comb optical filter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Zhengang; Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240; Huang, Meizhen, E-mail: mzhuang@sjtu.edu.cn

2015-04-15

A novel fast wavelength calibration method for spectrometers based on a standard spectrometer and a double metal-cladding waveguide comb optical filter (WCOF) is proposed and demonstrated. By using the WCOF device, a wide-spectrum beam is comb-filtered, which is very suitable for spectrometer wavelength calibration. The influence of waveguide filter’s structural parameters and the beam incident angle on the comb absorption peaks’ wavelength and its bandwidth are also discussed. The verification experiments were carried out in the wavelength range of 200–1100 nm with satisfactory results. Comparing with the traditional wavelength calibration method based on discrete sparse atomic emission or absorption lines,more » the new method has some advantages: sufficient calibration data, high accuracy, short calibration time, fit for produce process, stability, etc.« less

A Flexile and High Precision Calibration Method for Binocular Structured Light Scanning System

PubMed Central

Yuan, Jianying; Wang, Qiong; Li, Bailin

2014-01-01

3D (three-dimensional) structured light scanning system is widely used in the field of reverse engineering, quality inspection, and so forth. Camera calibration is the key for scanning precision. Currently, 2D (two-dimensional) or 3D fine processed calibration reference object is usually applied for high calibration precision, which is difficult to operate and the cost is high. In this paper, a novel calibration method is proposed with a scale bar and some artificial coded targets placed randomly in the measuring volume. The principle of the proposed method is based on hierarchical self-calibration and bundle adjustment. We get initial intrinsic parameters from images. Initial extrinsic parameters in projective space are estimated with the method of factorization and then upgraded to Euclidean space with orthogonality of rotation matrix and rank 3 of the absolute quadric as constraint. Last, all camera parameters are refined through bundle adjustment. Real experiments show that the proposed method is robust, and has the same precision level as the result using delicate artificial reference object, but the hardware cost is very low compared with the current calibration method used in 3D structured light scanning system. PMID:25202736

Radiometric calibration method for large aperture infrared system with broad dynamic range.

PubMed

Sun, Zhiyuan; Chang, Songtao; Zhu, Wei

2015-05-20

Infrared radiometric measurements can acquire important data for missile defense systems. When observation is carried out by ground-based infrared systems, a missile is characterized by long distance, small size, and large variation of radiance. Therefore, the infrared systems should be manufactured with a larger aperture to enhance detection ability and calibrated at a broader dynamic range to extend measurable radiance. Nevertheless, the frequently used calibration methods demand an extended-area blackbody with broad dynamic range or a huge collimator for filling the system's field stop, which would greatly increase manufacturing costs and difficulties. To overcome this restriction, a calibration method based on amendment of inner and outer calibration is proposed. First, the principles and procedures of this method are introduced. Then, a shifting strategy of infrared systems for measuring targets with large fluctuations of infrared radiance is put forward. Finally, several experiments are performed on a shortwave infrared system with Φ400  mm aperture. The results indicate that the proposed method cannot only ensure accuracy of calibration but have the advantage of low cost, low power, and high motility. Hence, it is an effective radiometric calibration method in the outfield.

Automatic alignment method for calibration of hydrometers

NASA Astrophysics Data System (ADS)

Lee, Y. J.; Chang, K. H.; Chon, J. C.; Oh, C. Y.

2004-04-01

This paper presents a new method to automatically align specific scale-marks for the calibration of hydrometers. A hydrometer calibration system adopting the new method consists of a vision system, a stepping motor, and software to control the system. The vision system is composed of a CCD camera and a frame grabber, and is used to acquire images. The stepping motor moves the camera, which is attached to the vessel containing a reference liquid, along the hydrometer. The operating program has two main functions: to process images from the camera to find the position of the horizontal plane and to control the stepping motor for the alignment of the horizontal plane with a particular scale-mark. Any system adopting this automatic alignment method is a convenient and precise means of calibrating a hydrometer. The performance of the proposed method is illustrated by comparing the calibration results using the automatic alignment method with those obtained using the manual method.

An overview of in-orbit radiometric calibration of typical satellite sensors

NASA Astrophysics Data System (ADS)

Zhou, G. Q.; Li, C. Y.; Yue, T.; Jiang, L. J.; Liu, N.; Sun, Y.; Li, M. Y.

2015-06-01

This paper reviews the development of in-orbit radiometric calibration methods in the past 40 years. It summarizes the development of in-orbit radiometric calibration technology of typical satellite sensors in the visible/near-infrared bands and the thermal infrared band. Focuses on the visible/near-infrared bands radiometric calibration method including: Lamp calibration and solar radiationbased calibration. Summarizes the calibration technology of Landsat series satellite sensors including MSS, TM, ETM+, OLI, TIRS; SPOT series satellite sensors including HRV, HRS. In addition to the above sensors, there are also summarizing ALI which was equipped on EO-1, IRMSS which was equipped on CBERS series satellite. Comparing the in-orbit radiometric calibration technology of different periods but the same type satellite sensors analyzes the similarities and differences of calibration technology. Meanwhile summarizes the in-orbit radiometric calibration technology in the same periods but different country satellite sensors advantages and disadvantages of calibration technology.

Cloned plasmid DNA fragments as calibrators for controlling GMOs: different real-time duplex quantitative PCR methods.

PubMed

Taverniers, Isabel; Van Bockstaele, Erik; De Loose, Marc

2004-03-01

Analytical real-time PCR technology is a powerful tool for implementation of the GMO labeling regulations enforced in the EU. The quality of analytical measurement data obtained by quantitative real-time PCR depends on the correct use of calibrator and reference materials (RMs). For GMO methods of analysis, the choice of appropriate RMs is currently under debate. So far, genomic DNA solutions from certified reference materials (CRMs) are most often used as calibrators for GMO quantification by means of real-time PCR. However, due to some intrinsic features of these CRMs, errors may be expected in the estimations of DNA sequence quantities. In this paper, two new real-time PCR methods are presented for Roundup Ready soybean, in which two types of plasmid DNA fragments are used as calibrators. Single-target plasmids (STPs) diluted in a background of genomic DNA were used in the first method. Multiple-target plasmids (MTPs) containing both sequences in one molecule were used as calibrators for the second method. Both methods simultaneously detect a promoter 35S sequence as GMO-specific target and a lectin gene sequence as endogenous reference target in a duplex PCR. For the estimation of relative GMO percentages both "delta C(T)" and "standard curve" approaches are tested. Delta C(T) methods are based on direct comparison of measured C(T) values of both the GMO-specific target and the endogenous target. Standard curve methods measure absolute amounts of target copies or haploid genome equivalents. A duplex delta C(T) method with STP calibrators performed at least as well as a similar method with genomic DNA calibrators from commercial CRMs. Besides this, high quality results were obtained with a standard curve method using MTP calibrators. This paper demonstrates that plasmid DNA molecules containing either one or multiple target sequences form perfect alternative calibrators for GMO quantification and are especially suitable for duplex PCR reactions.

Experimental Demonstration of In-Place Calibration for Time Domain Microwave Imaging System

NASA Astrophysics Data System (ADS)

Kwon, S.; Son, S.; Lee, K.

2018-04-01

In this study, the experimental demonstration of in-place calibration was conducted using the developed time domain measurement system. Experiments were conducted using three calibration methods—in-place calibration and two existing calibrations, that is, array rotation and differential calibration. The in-place calibration uses dual receivers located at an equal distance from the transmitter. The received signals at the dual receivers contain similar unwanted signals, that is, the directly received signal and antenna coupling. In contrast to the simulations, the antennas are not perfectly matched and there might be unexpected environmental errors. Thus, we experimented with the developed experimental system to demonstrate the proposed method. The possible problems with low signal-to-noise ratio and clock jitter, which may exist in time domain systems, were rectified by averaging repeatedly measured signals. The tumor was successfully detected using the three calibration methods according to the experimental results. The cross correlation was calculated using the reconstructed image of the ideal differential calibration for a quantitative comparison between the existing rotation calibration and the proposed in-place calibration. The mean value of cross correlation between the in-place calibration and ideal differential calibration was 0.80, and the mean value of cross correlation of the rotation calibration was 0.55. Furthermore, the results of simulation were compared with the experimental results to verify the in-place calibration method. A quantitative analysis was also performed, and the experimental results show a tendency similar to the simulation.

Influence of Installation Errors On the Output Data of the Piezoelectric Vibrations Transducers

NASA Astrophysics Data System (ADS)

Kozuch, Barbara; Chelmecki, Jaroslaw; Tatara, Tadeusz

2017-10-01

The paper examines an influence of installation errors of the piezoelectric vibrations transducers on the output data. PCB Piezotronics piezoelectric accelerometers were used to perform calibrations by comparison. The measurements were performed with TMS 9155 Calibration Workstation version 5.4.0 at frequency in the range of 5Hz - 2000Hz. Accelerometers were fixed on the calibration station in a so-called back-to-back configuration in accordance with the applicable international standard - ISO 16063-21: Methods for the calibration of vibration and shock transducers - Part 21: Vibration calibration by comparison to a reference transducer. The first accelerometer was calibrated by suitable methods with traceability to a primary reference transducer. Each subsequent calibration was performed when changing one setting in relation to the original calibration. The alterations were related to negligence and failures in relation to the above-mentioned standards and operating guidelines - e.g. the sensor was not tightened or appropriate substance was not placed. Also, there was modified the method of connection which was in the standards requirements. Different kind of wax, light oil, grease and other assembly methods were used. The aim of the study was to verify the significance of standards requirements and to estimate of their validity. The authors also wanted to highlight the most significant calibration errors. Moreover, relation between various appropriate methods of the connection was demonstrated.

Efficient calibration for imperfect computer models

DOE PAGES

Tuo, Rui; Wu, C. F. Jeff

2015-12-01

Many computer models contain unknown parameters which need to be estimated using physical observations. Furthermore, the calibration method based on Gaussian process models may lead to unreasonable estimate for imperfect computer models. In this work, we extend their study to calibration problems with stochastic physical data. We propose a novel method, called the L 2 calibration, and show its semiparametric efficiency. The conventional method of the ordinary least squares is also studied. Theoretical analysis shows that it is consistent but not efficient. Here, numerical examples show that the proposed method outperforms the existing ones.

Support vector machine regression (SVR/LS-SVM)--an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data.

PubMed

Balabin, Roman M; Lomakina, Ekaterina I

2011-04-21

In this study, we make a general comparison of the accuracy and robustness of five multivariate calibration models: partial least squares (PLS) regression or projection to latent structures, polynomial partial least squares (Poly-PLS) regression, artificial neural networks (ANNs), and two novel techniques based on support vector machines (SVMs) for multivariate data analysis: support vector regression (SVR) and least-squares support vector machines (LS-SVMs). The comparison is based on fourteen (14) different datasets: seven sets of gasoline data (density, benzene content, and fractional composition/boiling points), two sets of ethanol gasoline fuel data (density and ethanol content), one set of diesel fuel data (total sulfur content), three sets of petroleum (crude oil) macromolecules data (weight percentages of asphaltenes, resins, and paraffins), and one set of petroleum resins data (resins content). Vibrational (near-infrared, NIR) spectroscopic data are used to predict the properties and quality coefficients of gasoline, biofuel/biodiesel, diesel fuel, and other samples of interest. The four systems presented here range greatly in composition, properties, strength of intermolecular interactions (e.g., van der Waals forces, H-bonds), colloid structure, and phase behavior. Due to the high diversity of chemical systems studied, general conclusions about SVM regression methods can be made. We try to answer the following question: to what extent can SVM-based techniques replace ANN-based approaches in real-world (industrial/scientific) applications? The results show that both SVR and LS-SVM methods are comparable to ANNs in accuracy. Due to the much higher robustness of the former, the SVM-based approaches are recommended for practical (industrial) application. This has been shown to be especially true for complicated, highly nonlinear objects.

On-demand calibration and evaluation for electromagnetically tracked laparoscope in augmented reality visualization.

PubMed

Liu, Xinyang; Plishker, William; Zaki, George; Kang, Sukryool; Kane, Timothy D; Shekhar, Raj

2016-06-01

Common camera calibration methods employed in current laparoscopic augmented reality systems require the acquisition of multiple images of an entire checkerboard pattern from various poses. This lengthy procedure prevents performing laparoscope calibration in the operating room (OR). The purpose of this work was to develop a fast calibration method for electromagnetically (EM) tracked laparoscopes, such that the calibration can be performed in the OR on demand. We designed a mechanical tracking mount to uniquely and snugly position an EM sensor to an appropriate location on a conventional laparoscope. A tool named fCalib was developed to calibrate intrinsic camera parameters, distortion coefficients, and extrinsic parameters (transformation between the scope lens coordinate system and the EM sensor coordinate system) using a single image that shows an arbitrary portion of a special target pattern. For quick evaluation of calibration results in the OR, we integrated a tube phantom with fCalib prototype and overlaid a virtual representation of the tube on the live video scene. We compared spatial target registration error between the common OpenCV method and the fCalib method in a laboratory setting. In addition, we compared the calibration re-projection error between the EM tracking-based fCalib and the optical tracking-based fCalib in a clinical setting. Our results suggest that the proposed method is comparable to the OpenCV method. However, changing the environment, e.g., inserting or removing surgical tools, might affect re-projection accuracy for the EM tracking-based approach. Computational time of the fCalib method averaged 14.0 s (range 3.5 s-22.7 s). We developed and validated a prototype for fast calibration and evaluation of EM tracked conventional (forward viewing) laparoscopes. The calibration method achieved acceptable accuracy and was relatively fast and easy to be performed in the OR on demand.

Determining geometric error model parameters of a terrestrial laser scanner through Two-face, Length-consistency, and Network methods

PubMed Central

Wang, Ling; Muralikrishnan, Bala; Rachakonda, Prem; Sawyer, Daniel

2017-01-01

Terrestrial laser scanners (TLS) are increasingly used in large-scale manufacturing and assembly where required measurement uncertainties are on the order of few tenths of a millimeter or smaller. In order to meet these stringent requirements, systematic errors within a TLS are compensated in-situ through self-calibration. In the Network method of self-calibration, numerous targets distributed in the work-volume are measured from multiple locations with the TLS to determine parameters of the TLS error model. In this paper, we propose two new self-calibration methods, the Two-face method and the Length-consistency method. The Length-consistency method is proposed as a more efficient way of realizing the Network method where the length between any pair of targets from multiple TLS positions are compared to determine TLS model parameters. The Two-face method is a two-step process. In the first step, many model parameters are determined directly from the difference between front-face and back-face measurements of targets distributed in the work volume. In the second step, all remaining model parameters are determined through the Length-consistency method. We compare the Two-face method, the Length-consistency method, and the Network method in terms of the uncertainties in the model parameters, and demonstrate the validity of our techniques using a calibrated scale bar and front-face back-face target measurements. The clear advantage of these self-calibration methods is that a reference instrument or calibrated artifacts are not required, thus significantly lowering the cost involved in the calibration process. PMID:28890607

Air-assisted liquid-liquid microextraction using floating organic droplet solidification for simultaneous extraction and spectrophotometric determination of some drugs in biological samples through chemometrics methods

NASA Astrophysics Data System (ADS)

Farahmand, Farnaz; Ghasemzadeh, Bahar; Naseri, Abdolhossein

2018-01-01

An air assisted liquid-liquid microextraction by applying the solidification of a floating organic droplet method (AALLME-SFOD) coupled with a multivariate calibration method, namely partial least squares (PLS), was introduced for the fast and easy determination of Atenolol (ATE), Propanolol (PRO) and Carvedilol (CAR) in biological samples via a spectrophotometric approach. The analytes would be extracted from neutral aqueous solution into 1-dodecanol as an organic solvent, using AALLME. In this approach a low-density solvent with a melting point close to room temperature was applied as the extraction solvent. The emulsion was immediately formed by repeatedly pulling in and pushing out the aqueous sample solution and extraction solvent mixture via a 10-mL glass syringe for ten times. After centrifugation, the extractant droplet could be simply collected from the aqueous samples by solidifying the emulsion at a lower than the melting point temperature. In the next step, analytes were back extracted simultaneously into the acidic aqueous solution. Derringer and Suich multi-response optimization were utilized for simultaneous optimizing the parameters of three analytes. This method incorporates the benefits of AALLME and dispersive liquid-liquid microextraction considering the solidification of floating organic droplets (DLLME-SFOD). Calibration graphs under optimized conditions were linear in the range of 0.30-6.00, 0.32-2.00 and 0.30-1.40 μg mL- 1 for ATE, CAR and PRO, respectively. Other analytical parameters were obtained as follows: enrichment factors (EFs) were found to be 11.24, 16.55 and 14.90, and limits of detection (LODs) were determined to be 0.09, 0.10 and 0.08 μg mL- 1 for ATE, CAR and PRO, respectively. The proposed method will require neither a highly toxic chlorinated solvent for extraction nor an organic dispersive solvent in the application process; hence, it is more environmentally friendly.

Microwave-assisted of dispersive liquid-liquid microextraction and spectrophotometric determination of uranium after optimization based on Box-Behnken design and chemometrics methods.

PubMed

Niazi, Ali; Khorshidi, Neda; Ghaemmaghami, Pegah

2015-01-25

In this study an analytical procedure based on microwave-assisted dispersive liquid-liquid microextraction (MA-DLLME) and spectrophotometric coupled with chemometrics methods is proposed to determine uranium. In the proposed method, 4-(2-pyridylazo) resorcinol (PAR) is used as a chelating agent, and chloroform and ethanol are selected as extraction and dispersive solvent. The optimization strategy is carried out by using two level full factorial designs. Results of the two level full factorial design (2(4)) based on an analysis of variance demonstrated that the pH, concentration of PAR, amount of dispersive and extraction solvents are statistically significant. Optimal condition for three variables: pH, concentration of PAR, amount of dispersive and extraction solvents are obtained by using Box-Behnken design. Under the optimum conditions, the calibration graphs are linear in the range of 20.0-350.0 ng mL(-1) with detection limit of 6.7 ng mL(-1) (3δB/slope) and the enrichment factor of this method for uranium reached at 135. The relative standard deviation (R.S.D.) is 1.64% (n=7, c=50 ng mL(-1)). The partial least squares (PLS) modeling was used for multivariate calibration of the spectrophotometric data. The orthogonal signal correction (OSC) was used for preprocessing of data matrices and the prediction results of model, with and without using OSC, were statistically compared. MA-DLLME-OSC-PLS method was presented for the first time in this study. The root mean squares error of prediction (RMSEP) for uranium determination using PLS and OSC-PLS models were 4.63 and 0.98, respectively. This procedure allows the determination of uranium synthesis and real samples such as waste water with good reliability of the determination. Copyright © 2014. Published by Elsevier B.V.

Air-assisted liquid-liquid microextraction using floating organic droplet solidification for simultaneous extraction and spectrophotometric determination of some drugs in biological samples through chemometrics methods.

PubMed

Farahmand, Farnaz; Ghasemzadeh, Bahar; Naseri, Abdolhossein

2018-01-05

An air assisted liquid-liquid microextraction by applying the solidification of a floating organic droplet method (AALLME-SFOD) coupled with a multivariate calibration method, namely partial least squares (PLS), was introduced for the fast and easy determination of Atenolol (ATE), Propanolol (PRO) and Carvedilol (CAR) in biological samples via a spectrophotometric approach. The analytes would be extracted from neutral aqueous solution into 1-dodecanol as an organic solvent, using AALLME. In this approach a low-density solvent with a melting point close to room temperature was applied as the extraction solvent. The emulsion was immediately formed by repeatedly pulling in and pushing out the aqueous sample solution and extraction solvent mixture via a 10-mL glass syringe for ten times. After centrifugation, the extractant droplet could be simply collected from the aqueous samples by solidifying the emulsion at a lower than the melting point temperature. In the next step, analytes were back extracted simultaneously into the acidic aqueous solution. Derringer and Suich multi-response optimization were utilized for simultaneous optimizing the parameters of three analytes. This method incorporates the benefits of AALLME and dispersive liquid-liquid microextraction considering the solidification of floating organic droplets (DLLME-SFOD). Calibration graphs under optimized conditions were linear in the range of 0.30-6.00, 0.32-2.00 and 0.30-1.40μg mL -1 for ATE, CAR and PRO, respectively. Other analytical parameters were obtained as follows: enrichment factors (EFs) were found to be 11.24, 16.55 and 14.90, and limits of detection (LODs) were determined to be 0.09, 0.10 and 0.08μg mL -1 for ATE, CAR and PRO, respectively. The proposed method will require neither a highly toxic chlorinated solvent for extraction nor an organic dispersive solvent in the application process; hence, it is more environmentally friendly. Copyright © 2017 Elsevier B.V. All rights reserved.

Developing and refining NIR calibrations for total carbohydrate composition and isoflavones and saponins in ground whole soy meal

USDA-ARS?s Scientific Manuscript database

Although many near infrared (NIR) spectrometric calibrations exist for a variety of components in soy, current calibration methods are often limited by either a small sample size on which the calibrations are based or a wide variation in sample preparation and measurement methods, which yields unrel...

Multiplexed fluctuation-dissipation-theorem calibration of optical tweezers inside living cells

NASA Astrophysics Data System (ADS)

Yan, Hao; Johnston, Jessica F.; Cahn, Sidney B.; King, Megan C.; Mochrie, Simon G. J.

2017-11-01

In order to apply optical tweezers-based force measurements within an uncharacterized viscoelastic medium such as the cytoplasm of a living cell, a quantitative calibration method that may be applied in this complex environment is needed. We describe an improved version of the fluctuation-dissipation-theorem calibration method, which has been developed to perform in situ calibration in viscoelastic media without prior knowledge of the trapped object. Using this calibration procedure, it is possible to extract values of the medium's viscoelastic moduli as well as the force constant describing the optical trap. To demonstrate our method, we calibrate an optical trap in water, in polyethylene oxide solutions of different concentrations, and inside living fission yeast (S. pombe).

Flight Test Results of an Angle of Attack and Angle of Sideslip Calibration Method Using Output-Error Optimization

NASA Technical Reports Server (NTRS)

Siu, Marie-Michele; Martos, Borja; Foster, John V.

2013-01-01

As part of a joint partnership between the NASA Aviation Safety Program (AvSP) and the University of Tennessee Space Institute (UTSI), research on advanced air data calibration methods has been in progress. This research was initiated to expand a novel pitot-static calibration method that was developed to allow rapid in-flight calibration for the NASA Airborne Subscale Transport Aircraft Research (AirSTAR) facility. This approach uses Global Positioning System (GPS) technology coupled with modern system identification methods that rapidly computes optimal pressure error models over a range of airspeed with defined confidence bounds. Subscale flight tests demonstrated small 2-s error bounds with significant reduction in test time compared to other methods. Recent UTSI full scale flight tests have shown airspeed calibrations with the same accuracy or better as the Federal Aviation Administration (FAA) accepted GPS 'four-leg' method in a smaller test area and in less time. The current research was motivated by the desire to extend this method for inflight calibration of angle of attack (AOA) and angle of sideslip (AOS) flow vanes. An instrumented Piper Saratoga research aircraft from the UTSI was used to collect the flight test data and evaluate flight test maneuvers. Results showed that the output-error approach produces good results for flow vane calibration. In addition, maneuvers for pitot-static and flow vane calibration can be integrated to enable simultaneous and efficient testing of each system.

SandiaMRCR

DOE Office of Scientific and Technical Information (OSTI.GOV)

2012-01-05

SandiaMCR was developed to identify pure components and their concentrations from spectral data. This software efficiently implements the multivariate calibration regression alternating least squares (MCR-ALS), principal component analysis (PCA), and singular value decomposition (SVD). Version 3.37 also includes the PARAFAC-ALS Tucker-1 (for trilinear analysis) algorithms. The alternating least squares methods can be used to determine the composition without or with incomplete prior information on the constituents and their concentrations. It allows the specification of numerous preprocessing, initialization and data selection and compression options for the efficient processing of large data sets. The software includes numerous options including the definition ofmore » equality and non-negativety constraints to realistically restrict the solution set, various normalization or weighting options based on the statistics of the data, several initialization choices and data compression. The software has been designed to provide a practicing spectroscopist the tools required to routinely analysis data in a reasonable time and without requiring expert intervention.« less

Signal-to-noise optimization and evaluation of a home-made visible diode-array spectrophotometer

PubMed Central

Raimundo, Jr., Ivo M.; Pasquini, Celio

1993-01-01

This paper describes a simple low-cost multichannel visible spectrophotometer built with an RL512G EGG-Reticon photodiode array. A symmetric Czerny-Turner optical design was employed; instrument control was via a single-board microcomputer based on the 8085 Intel microprocessor. Spectral intensity data are stored in the single-board's RAM and then transferred to an IBM-AT 3865X compatible microcomputer through a RS-232C interface. This external microcomputer processes the data to recover transmittance, absorbance or relative intensity of the spectra. The signal-to-noise ratio and dynamic range were improved by using variable integration times, which increase during the same scan; and by the use of either weighted or unweighted sliding average of consecutive diodes. The instrument is suitable for automatic methods requiring quasi-simultaneous multiwavelength detections, such as multivariative calibration and flow-injection gradient scan techniques. PMID:18924979

Development of Rapid, Continuous Calibration Techniques and Implementation as a Prototype System for Civil Engineering Materials Evaluation

NASA Astrophysics Data System (ADS)

Scott, M. L.; Gagarin, N.; Mekemson, J. R.; Chintakunta, S. R.

2011-06-01

Until recently, civil engineering material calibration data could only be obtained from material sample cores or via time consuming, stationary calibration measurements in a limited number of locations. Calibration data are used to determine material propagation velocities of electromagnetic waves in test materials for use in layer thickness measurements and subsurface imaging. Limitations these calibration methods impose have been a significant impediment to broader use of nondestructive evaluation methods such as ground-penetrating radar (GPR). In 2006, a new rapid, continuous calibration approach was designed using simulation software to address these measurement limitations during a Federal Highway Administration (FHWA) research and development effort. This continuous calibration method combines a digitally-synthesized step-frequency (SF)-GPR array and a data collection protocol sequence for the common midpoint (CMP) method. Modeling and laboratory test results for various data collection protocols and materials are presented in this paper. The continuous-CMP concept was finally implemented for FHWA in a prototype demonstration system called the Advanced Pavement Evaluation (APE) system in 2009. Data from the continuous-CMP protocol is processed using a semblance/coherency analysis to determine material propagation velocities. Continuously calibrated pavement thicknesses measured with the APE system in 2009 are presented. This method is efficient, accurate, and cost-effective.

User-friendly freehand ultrasound calibration using Lego bricks and automatic registration.

PubMed

Xiao, Yiming; Yan, Charles Xiao Bo; Drouin, Simon; De Nigris, Dante; Kochanowska, Anna; Collins, D Louis

2016-09-01

As an inexpensive, noninvasive, and portable clinical imaging modality, ultrasound (US) has been widely employed in many interventional procedures for monitoring potential tissue deformation, surgical tool placement, and locating surgical targets. The application requires the spatial mapping between 2D US images and 3D coordinates of the patient. Although positions of the devices (i.e., ultrasound transducer) and the patient can be easily recorded by a motion tracking system, the spatial relationship between the US image and the tracker attached to the US transducer needs to be estimated through an US calibration procedure. Previously, various calibration techniques have been proposed, where a spatial transformation is computed to match the coordinates of corresponding features in a physical phantom and those seen in the US scans. However, most of these methods are difficult to use for novel users. We proposed an ultrasound calibration method by constructing a phantom from simple Lego bricks and applying an automated multi-slice 2D-3D registration scheme without volumetric reconstruction. The method was validated for its calibration accuracy and reproducibility. Our method yields a calibration accuracy of [Formula: see text] mm and a calibration reproducibility of 1.29 mm. We have proposed a robust, inexpensive, and easy-to-use ultrasound calibration method.

Development of rapid, continuous calibration techniques and implementation as a prototype system for civil engineering materials evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scott, M. L.; Gagarin, N.; Mekemson, J. R.

Until recently, civil engineering material calibration data could only be obtained from material sample cores or via time consuming, stationary calibration measurements in a limited number of locations. Calibration data are used to determine material propagation velocities of electromagnetic waves in test materials for use in layer thickness measurements and subsurface imaging. Limitations these calibration methods impose have been a significant impediment to broader use of nondestructive evaluation methods such as ground-penetrating radar (GPR). In 2006, a new rapid, continuous calibration approach was designed using simulation software to address these measurement limitations during a Federal Highway Administration (FHWA) research andmore » development effort. This continuous calibration method combines a digitally-synthesized step-frequency (SF)-GPR array and a data collection protocol sequence for the common midpoint (CMP) method. Modeling and laboratory test results for various data collection protocols and materials are presented in this paper. The continuous-CMP concept was finally implemented for FHWA in a prototype demonstration system called the Advanced Pavement Evaluation (APE) system in 2009. Data from the continuous-CMP protocol is processed using a semblance/coherency analysis to determine material propagation velocities. Continuously calibrated pavement thicknesses measured with the APE system in 2009 are presented. This method is efficient, accurate, and cost-effective.« less

IMU-Based Online Kinematic Calibration of Robot Manipulator

PubMed Central

2013-01-01

Robot calibration is a useful diagnostic method for improving the positioning accuracy in robot production and maintenance. An online robot self-calibration method based on inertial measurement unit (IMU) is presented in this paper. The method requires that the IMU is rigidly attached to the robot manipulator, which makes it possible to obtain the orientation of the manipulator with the orientation of the IMU in real time. This paper proposed an efficient approach which incorporates Factored Quaternion Algorithm (FQA) and Kalman Filter (KF) to estimate the orientation of the IMU. Then, an Extended Kalman Filter (EKF) is used to estimate kinematic parameter errors. Using this proposed orientation estimation method will result in improved reliability and accuracy in determining the orientation of the manipulator. Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. Experimental studies on a GOOGOL GRB3016 robot show that this method has better accuracy, convenience, and effectiveness than vision-based methods. PMID:24302854

Extrinsic Calibration of Camera Networks Based on Pedestrians

PubMed Central

Guan, Junzhi; Deboeverie, Francis; Slembrouck, Maarten; Van Haerenborgh, Dirk; Van Cauwelaert, Dimitri; Veelaert, Peter; Philips, Wilfried

2016-01-01

In this paper, we propose a novel extrinsic calibration method for camera networks by analyzing tracks of pedestrians. First of all, we extract the center lines of walking persons by detecting their heads and feet in the camera images. We propose an easy and accurate method to estimate the 3D positions of the head and feet w.r.t. a local camera coordinate system from these center lines. We also propose a RANSAC-based orthogonal Procrustes approach to compute relative extrinsic parameters connecting the coordinate systems of cameras in a pairwise fashion. Finally, we refine the extrinsic calibration matrices using a method that minimizes the reprojection error. While existing state-of-the-art calibration methods explore epipolar geometry and use image positions directly, the proposed method first computes 3D positions per camera and then fuses the data. This results in simpler computations and a more flexible and accurate calibration method. Another advantage of our method is that it can also handle the case of persons walking along straight lines, which cannot be handled by most of the existing state-of-the-art calibration methods since all head and feet positions are co-planar. This situation often happens in real life. PMID:27171080

Hybrid Geometric Calibration Method for Multi-Platform Spaceborne SAR Image with Sparse Gcps

NASA Astrophysics Data System (ADS)

Lv, G.; Tang, X.; Ai, B.; Li, T.; Chen, Q.

2018-04-01

Geometric calibration is able to provide high-accuracy geometric coordinates of spaceborne SAR image through accurate geometric parameters in the Range-Doppler model by ground control points (GCPs). However, it is very difficult to obtain GCPs that covering large-scale areas, especially in the mountainous regions. In addition, the traditional calibration method is only used for single platform SAR images and can't support the hybrid geometric calibration for multi-platform images. To solve the above problems, a hybrid geometric calibration method for multi-platform spaceborne SAR images with sparse GCPs is proposed in this paper. First, we calibrate the master image that contains GCPs. Secondly, the point tracking algorithm is used to obtain the tie points (TPs) between the master and slave images. Finally, we calibrate the slave images using TPs as the GCPs. We take the Beijing-Tianjin- Hebei region as an example to study SAR image hybrid geometric calibration method using 3 TerraSAR-X images, 3 TanDEM-X images and 5 GF-3 images covering more than 235 kilometers in the north-south direction. Geometric calibration of all images is completed using only 5 GCPs. The GPS data extracted from GNSS receiver are used to assess the plane accuracy after calibration. The results after geometric calibration with sparse GCPs show that the geometric positioning accuracy is 3 m for TSX/TDX images and 7.5 m for GF-3 images.

Standardization of glycohemoglobin results and reference values in whole blood studied in 103 laboratories using 20 methods.

PubMed

Weykamp, C W; Penders, T J; Miedema, K; Muskiet, F A; van der Slik, W

1995-01-01

We investigated the effect of calibration with lyophilized calibrators on whole-blood glycohemoglobin (glyHb) results. One hundred three laboratories, using 20 different methods, determined glyHb in two lyophilized calibrators and two whole-blood samples. For whole-blood samples with low (5%) and high (9%) glyHb percentages, respectively, calibration decreased overall interlaboratory variation (CV) from 16% to 9% and from 11% to 6% and decreased intermethod variation from 14% to 6% and from 12% to 5%. Forty-seven laboratories, using 14 different methods, determined mean glyHb percentages in self-selected groups of 10 nondiabetic volunteers each. With calibration their overall mean (2SD) was 5.0% (0.5%), very close to the 5.0% (0.3%) derived from the reference method used in the Diabetes Control and Complications Trial. In both experiments the Abbott IMx and Vision showed deviating results. We conclude that, irrespective of the analytical method used, calibration enables standardization of glyHb results, reference values, and interpretation criteria.

Input variable selection and calibration data selection for storm water quality regression models.

PubMed

Sun, Siao; Bertrand-Krajewski, Jean-Luc

2013-01-01

Storm water quality models are useful tools in storm water management. Interest has been growing in analyzing existing data for developing models for urban storm water quality evaluations. It is important to select appropriate model inputs when many candidate explanatory variables are available. Model calibration and verification are essential steps in any storm water quality modeling. This study investigates input variable selection and calibration data selection in storm water quality regression models. The two selection problems are mutually interacted. A procedure is developed in order to fulfil the two selection tasks in order. The procedure firstly selects model input variables using a cross validation method. An appropriate number of variables are identified as model inputs to ensure that a model is neither overfitted nor underfitted. Based on the model input selection results, calibration data selection is studied. Uncertainty of model performances due to calibration data selection is investigated with a random selection method. An approach using the cluster method is applied in order to enhance model calibration practice based on the principle of selecting representative data for calibration. The comparison between results from the cluster selection method and random selection shows that the former can significantly improve performances of calibrated models. It is found that the information content in calibration data is important in addition to the size of calibration data.

An Improved Fast Self-Calibration Method for Hybrid Inertial Navigation System under Stationary Condition

PubMed Central

Liu, Bingqi; Wei, Shihui; Su, Guohua; Wang, Jiping; Lu, Jiazhen

2018-01-01

The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible. PMID:29695041

An Improved Fast Self-Calibration Method for Hybrid Inertial Navigation System under Stationary Condition.

PubMed

Liu, Bingqi; Wei, Shihui; Su, Guohua; Wang, Jiping; Lu, Jiazhen

2018-04-24

The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible.

A method for soil moisture probes calibration and validation of satellite estimates.

PubMed

Holzman, Mauro; Rivas, Raúl; Carmona, Facundo; Niclòs, Raquel

2017-01-01

Optimization of field techniques is crucial to ensure high quality soil moisture data. The aim of the work is to present a sampling method for undisturbed soil and soil water content to calibrated soil moisture probes, in a context of the SMOS (Soil Moisture and Ocean Salinity) mission MIRAS Level 2 soil moisture product validation in Pampean Region of Argentina. The method avoids soil alteration and is recommended to calibrated probes based on soil type under a freely drying process at ambient temperature. A detailed explanation of field and laboratory procedures to obtain reference soil moisture is shown. The calibration results reflected accurate operation for the Delta-T thetaProbe ML2x probes in most of analyzed cases (RMSE and bias ≤ 0.05 m 3 /m 3 ). Post-calibration results indicated that the accuracy improves significantly applying the adjustments of the calibration based on soil types (RMSE ≤ 0.022 m 3 /m 3 , bias ≤ -0.010 m 3 /m 3 ). •A sampling method that provides high quality data of soil water content for calibration of probes is described.•Importance of calibration based on soil types.•A calibration process for similar soil types could be suitable in practical terms, depending on the required accuracy level.

Simplified stereo-optical ultrasound plane calibration

NASA Astrophysics Data System (ADS)

Hoßbach, Martin; Noll, Matthias; Wesarg, Stefan

2013-03-01

Image guided therapy is a natural concept and commonly used in medicine. In anesthesia, a common task is the injection of an anesthetic close to a nerve under freehand ultrasound guidance. Several guidance systems exist using electromagnetic tracking of the ultrasound probe as well as the needle, providing the physician with a precise projection of the needle into the ultrasound image. This, however, requires additional expensive devices. We suggest using optical tracking with miniature cameras attached to a 2D ultrasound probe to achieve a higher acceptance among physicians. The purpose of this paper is to present an intuitive method to calibrate freehand ultrasound needle guidance systems employing a rigid stereo camera system. State of the art methods are based on a complex series of error prone coordinate system transformations which makes them susceptible to error accumulation. By reducing the amount of calibration steps to a single calibration procedure we provide a calibration method that is equivalent, yet not prone to error accumulation. It requires a linear calibration object and is validated on three datasets utilizing di erent calibration objects: a 6mm metal bar and a 1:25mm biopsy needle were used for experiments. Compared to existing calibration methods for freehand ultrasound needle guidance systems, we are able to achieve higher accuracy results while additionally reducing the overall calibration complexity. Ke

Improved intact soil-core carbon determination applying regression shrinkage and variable selection techniques to complete spectrum laser-induced breakdown spectroscopy (LIBS).

PubMed

Bricklemyer, Ross S; Brown, David J; Turk, Philip J; Clegg, Sam M

2013-10-01

Laser-induced breakdown spectroscopy (LIBS) provides a potential method for rapid, in situ soil C measurement. In previous research on the application of LIBS to intact soil cores, we hypothesized that ultraviolet (UV) spectrum LIBS (200-300 nm) might not provide sufficient elemental information to reliably discriminate between soil organic C (SOC) and inorganic C (IC). In this study, using a custom complete spectrum (245-925 nm) core-scanning LIBS instrument, we analyzed 60 intact soil cores from six wheat fields. Predictive multi-response partial least squares (PLS2) models using full and reduced spectrum LIBS were compared for directly determining soil total C (TC), IC, and SOC. Two regression shrinkage and variable selection approaches, the least absolute shrinkage and selection operator (LASSO) and sparse multivariate regression with covariance estimation (MRCE), were tested for soil C predictions and the identification of wavelengths important for soil C prediction. Using complete spectrum LIBS for PLS2 modeling reduced the calibration standard error of prediction (SEP) 15 and 19% for TC and IC, respectively, compared to UV spectrum LIBS. The LASSO and MRCE approaches provided significantly improved calibration accuracy and reduced SEP 32-55% over UV spectrum PLS2 models. We conclude that (1) complete spectrum LIBS is superior to UV spectrum LIBS for predicting soil C for intact soil cores without pretreatment; (2) LASSO and MRCE approaches provide improved calibration prediction accuracy over PLS2 but require additional testing with increased soil and target analyte diversity; and (3) measurement errors associated with analyzing intact cores (e.g., sample density and surface roughness) require further study and quantification.

Simultaneous multi-headed imager geometry calibration method

DOEpatents

Tran, Vi-Hoa [Newport News, VA; Meikle, Steven Richard [Penshurst, AU; Smith, Mark Frederick [Yorktown, VA

2008-02-19

A method for calibrating multi-headed high sensitivity and high spatial resolution dynamic imaging systems, especially those useful in the acquisition of tomographic images of small animals. The method of the present invention comprises: simultaneously calibrating two or more detectors to the same coordinate system; and functionally correcting for unwanted detector movement due to gantry flexing.

Model independent approach to the single photoelectron calibration of photomultiplier tubes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saldanha, R.; Grandi, L.; Guardincerri, Y.

2017-08-01

The accurate calibration of photomultiplier tubes is critical in a wide variety of applications in which it is necessary to know the absolute number of detected photons or precisely determine the resolution of the signal. Conventional calibration methods rely on fitting the photomultiplier response to a low intensity light source with analytical approximations to the single photoelectron distribution, often leading to biased estimates due to the inability to accurately model the full distribution, especially at low charge values. In this paper we present a simple statistical method to extract the relevant single photoelectron calibration parameters without making any assumptions aboutmore » the underlying single photoelectron distribution. We illustrate the use of this method through the calibration of a Hamamatsu R11410 photomultiplier tube and study the accuracy and precision of the method using Monte Carlo simulations. The method is found to have significantly reduced bias compared to conventional methods and works under a wide range of light intensities, making it suitable for simultaneously calibrating large arrays of photomultiplier tubes.« less

A Theoretical Framework for Calibration in Computer Models: Parametrization, Estimation and Convergence Properties

DOE PAGES

Tuo, Rui; Jeff Wu, C. F.

2016-07-19

Calibration parameters in deterministic computer experiments are those attributes that cannot be measured or available in physical experiments. Here, an approach to estimate them by using data from physical experiments and computer simulations. A theoretical framework is given which allows us to study the issues of parameter identifiability and estimation. We define the L 2-consistency for calibration as a justification for calibration methods. It is shown that a simplified version of the original KO method leads to asymptotically L 2-inconsistent calibration. This L 2-inconsistency can be remedied by modifying the original estimation procedure. A novel calibration method, called the Lmore » 2 calibration, is proposed and proven to be L 2-consistent and enjoys optimal convergence rate. Furthermore a numerical example and some mathematical analysis are used to illustrate the source of the L 2-inconsistency problem.« less

ASTER preflight and inflight calibration and the validation of level 2 products

USGS Publications Warehouse

Thome, K.; Aral, K.; Hook, S.; Kieffer, H.; Lang, H.; Matsunaga, T.; Ono, A.; Palluconi, F. D.; Sakuma, H.; Slater, P.; Takashima, T.; Tonooka, H.; Tsuchida, S.; Welch, R.M.; Zalewski, E.

1998-01-01

This paper describes the preflight and inflight calibration approaches used for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The system is a multispectral, high-spatial resolution sensor on the Earth Observing System's (EOS)-AMl platform. Preflight calibration of ASTER uses well-characterized sources to provide calibration and preflight round-robin exercises to understand biases between the calibration sources of ASTER and other EOS sensors. These round-robins rely on well-characterized, ultra-stable radiometers. An experiment held in Yokohama, Japan, showed that the output from the source used for the visible and near-infrared (VNIR) subsystem of ASTER may be underestimated by 1.5%, but this is still within the 4% specification for the absolute, radiometric calibration of these bands. Inflight calibration will rely on vicarious techniques and onboard blackbodies and lamps. Vicarious techniques include ground-reference methods using desert and water sites. A recent joint field campaign gives confidence that these methods currently provide absolute calibration to better than 5%, and indications are that uncertainties less than the required 4% should be achievable at launch. The EOS-AMI platform will also provide a spacecraft maneuver that will allow ASTER to see the moon, allowing further characterization of the sensor. A method for combining the results of these independent calibration results is presented. The paper also describes the plans for validating the Level 2 data products from ASTER. These plans rely heavily upon field campaigns using methods similar to those used for the ground-reference, vicarious calibration methods. ?? 1998 IEEE.

Rapid analysis of composition and reactivity in cellulosic biomass feedstocks with near-infrared spectroscopy.

PubMed

Payne, Courtney E; Wolfrum, Edward J

2015-01-01

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. Our objective was to use near-infrared (NIR) spectroscopy and partial least squares (PLS) multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. Major feedstocks included in the calibration models are corn stover, sorghum, switchgrass, perennial cool season grasses, rice straw, and miscanthus. We present individual model statistics to demonstrate model performance and validation samples to more accurately measure predictive quality of the models. The PLS-2 model for composition predicts glucan, xylan, lignin, and ash (wt%) with uncertainties similar to primary measurement methods. A PLS-2 model was developed to predict glucose and xylose release following pretreatment and enzymatic hydrolysis. An additional PLS-2 model was developed to predict glucan and xylan yield. PLS-1 models were developed to predict the sum of glucose/glucan and xylose/xylan for release and yield (grams per gram). The release and yield models have higher uncertainties than the primary methods used to develop the models. It is possible to build effective multispecies feedstock models for composition, as well as carbohydrate release and yield. The model for composition is useful for predicting glucan, xylan, lignin, and ash with good uncertainties. The release and yield models have higher uncertainties; however, these models are useful for rapidly screening sample populations to identify unusual samples.

Estimation of soil clay and organic matter using two quantitative methods (PLSR and MARS) based on reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Nawar, Said; Buddenbaum, Henning; Hill, Joachim

2014-05-01

A rapid and inexpensive soil analytical technique is needed for soil quality assessment and accurate mapping. This study investigated a method for improved estimation of soil clay (SC) and organic matter (OM) using reflectance spectroscopy. Seventy soil samples were collected from Sinai peninsula in Egypt to estimate the soil clay and organic matter relative to the soil spectra. Soil samples were scanned with an Analytical Spectral Devices (ASD) spectrometer (350-2500 nm). Three spectral formats were used in the calibration models derived from the spectra and the soil properties: (1) original reflectance spectra (OR), (2) first-derivative spectra smoothened using the Savitzky-Golay technique (FD-SG) and (3) continuum-removed reflectance (CR). Partial least-squares regression (PLSR) models using the CR of the 400-2500 nm spectral region resulted in R2 = 0.76 and 0.57, and RPD = 2.1 and 1.5 for estimating SC and OM, respectively, indicating better performance than that obtained using OR and SG. The multivariate adaptive regression splines (MARS) calibration model with the CR spectra resulted in an improved performance (R2 = 0.89 and 0.83, RPD = 3.1 and 2.4) for estimating SC and OM, respectively. The results show that the MARS models have a great potential for estimating SC and OM compared with PLSR models. The results obtained in this study have potential value in the field of soil spectroscopy because they can be applied directly to the mapping of soil properties using remote sensing imagery in arid environment conditions. Key Words: soil clay, organic matter, PLSR, MARS, reflectance spectroscopy.

In line NIR quantification of film thickness on pharmaceutical pellets during a fluid bed coating process.

PubMed

Lee, Min-Jeong; Seo, Da-Young; Lee, Hea-Eun; Wang, In-Chun; Kim, Woo-Sik; Jeong, Myung-Yung; Choi, Guang J

2011-01-17

Along with the risk-based approach, process analytical technology (PAT) has emerged as one of the key elements to fully implement QbD (quality-by-design). Near-infrared (NIR) spectroscopy has been extensively applied as an in-line/on-line analytical tool in biomedical and chemical industries. In this study, the film thickness on pharmaceutical pellets was examined for quantification using in-line NIR spectroscopy during a fluid-bed coating process. A precise monitoring of coating thickness and its prediction with a suitable control strategy is crucial to the quality assurance of solid dosage forms including dissolution characteristics. Pellets of a test formulation were manufactured and coated in a fluid-bed by spraying a hydroxypropyl methylcellulose (HPMC) coating solution. NIR spectra were acquired via a fiber-optic probe during the coating process, followed by multivariate analysis utilizing partial least squares (PLS) calibration models. The actual coating thickness of pellets was measured by two separate methods, confocal laser scanning microscopy (CLSM) and laser diffraction particle size analysis (LD-PSA). Both characterization methods gave superb correlation results, and all determination coefficient (R(2)) values exceeded 0.995. In addition, a prediction coating experiment for 70min demonstrated that the end-point can be accurately designated via NIR in-line monitoring with appropriate calibration models. In conclusion, our approach combining in-line NIR monitoring with CLSM and LD-PSA can be applied as an effective PAT tool for fluid-bed pellet coating processes. Copyright © 2010 Elsevier B.V. All rights reserved.

Apparatus for in-situ calibration of instruments that measure fluid depth

DOEpatents

Campbell, Melvin D.

1994-01-01

The present invention provides a method and apparatus for in-situ calibration of distance measuring equipment. The method comprises obtaining a first distance measurement in a first location, then obtaining at least one other distance measurement in at least one other location of a precisely known distance from the first location, and calculating a calibration constant. The method is applied specifically to calculating a calibration constant for obtaining fluid level and embodied in an apparatus using a pressure transducer and a spacer of precisely known length. The calibration constant is used to calculate the depth of a fluid from subsequent single pressure measurements at any submerged position.

New spectrophotometric/chemometric assisted methods for the simultaneous determination of imatinib, gemifloxacin, nalbuphine and naproxen in pharmaceutical formulations and human urine

NASA Astrophysics Data System (ADS)

Belal, F.; Ibrahim, F.; Sheribah, Z. A.; Alaa, H.

2018-06-01

In this paper, novel univariate and multivariate regression methods along with model-updating technique were developed and validated for the simultaneous determination of quaternary mixture of imatinib (IMB), gemifloxacin (GMI), nalbuphine (NLP) and naproxen (NAP). The univariate method is extended derivative ratio (EDR) which depends on measuring every drug in the quaternary mixture by using a ternary mixture of the other three drugs as divisor. Peak amplitudes were measured at 294 nm, 250 nm, 283 nm and 239 nm within linear concentration ranges of 4.0-17.0, 3.0-15.0, 4.0-80.0 and 1.0-6.0 μg mL-1 for IMB, GMI, NLP and NAB, respectively. Multivariate methods adopted are partial least squares (PLS) in original and derivative mode. These models were constructed for simultaneous determination of the studied drugs in the ranges of 4.0-8.0, 3.0-11.0, 10.0-18.0 and 1.0-3.0 μg mL-1 for IMB, GMI, NLP and NAB, respectively, by using eighteen mixtures as a calibration set and seven mixtures as a validation set. The root mean square error of predication (RMSEP) were 0.09 and 0.06 for IMB, 0.14 and 0.13 for GMI, 0.07 and 0.02 for NLP and 0.64 and 0.27 for NAP by PLS in original and derivative mode, respectively. Both models were successfully applied for analysis of IMB, GMI, NLP and NAP in their dosage forms. Updated PLS in derivative mode and EDR were applied for determination of the studied drugs in spiked human urine. The obtained results were statistically compared with those obtained by the reported methods giving a conclusion that there is no significant difference regarding accuracy and precision.

New spectrophotometric/chemometric assisted methods for the simultaneous determination of imatinib, gemifloxacin, nalbuphine and naproxen in pharmaceutical formulations and human urine.

PubMed

Belal, F; Ibrahim, F; Sheribah, Z A; Alaa, H

2018-06-05

In this paper, novel univariate and multivariate regression methods along with model-updating technique were developed and validated for the simultaneous determination of quaternary mixture of imatinib (IMB), gemifloxacin (GMI), nalbuphine (NLP) and naproxen (NAP). The univariate method is extended derivative ratio (EDR) which depends on measuring every drug in the quaternary mixture by using a ternary mixture of the other three drugs as divisor. Peak amplitudes were measured at 294nm, 250nm, 283nm and 239nm within linear concentration ranges of 4.0-17.0, 3.0-15.0, 4.0-80.0 and 1.0-6.0μgmL -1 for IMB, GMI, NLP and NAB, respectively. Multivariate methods adopted are partial least squares (PLS) in original and derivative mode. These models were constructed for simultaneous determination of the studied drugs in the ranges of 4.0-8.0, 3.0-11.0, 10.0-18.0 and 1.0-3.0μgmL -1 for IMB, GMI, NLP and NAB, respectively, by using eighteen mixtures as a calibration set and seven mixtures as a validation set. The root mean square error of predication (RMSEP) were 0.09 and 0.06 for IMB, 0.14 and 0.13 for GMI, 0.07 and 0.02 for NLP and 0.64 and 0.27 for NAP by PLS in original and derivative mode, respectively. Both models were successfully applied for analysis of IMB, GMI, NLP and NAP in their dosage forms. Updated PLS in derivative mode and EDR were applied for determination of the studied drugs in spiked human urine. The obtained results were statistically compared with those obtained by the reported methods giving a conclusion that there is no significant difference regarding accuracy and precision. Copyright © 2018 Elsevier B.V. All rights reserved.

Adaptive Prior Variance Calibration in the Bayesian Continual Reassessment Method

PubMed Central

Zhang, Jin; Braun, Thomas M.; Taylor, Jeremy M.G.

2012-01-01

Use of the Continual Reassessment Method (CRM) and other model-based approaches to design in Phase I clinical trials has increased due to the ability of the CRM to identify the maximum tolerated dose (MTD) better than the 3+3 method. However, the CRM can be sensitive to the variance selected for the prior distribution of the model parameter, especially when a small number of patients are enrolled. While methods have emerged to adaptively select skeletons and to calibrate the prior variance only at the beginning of a trial, there has not been any approach developed to adaptively calibrate the prior variance throughout a trial. We propose three systematic approaches to adaptively calibrate the prior variance during a trial and compare them via simulation to methods proposed to calibrate the variance at the beginning of a trial. PMID:22987660

The Use of Color Sensors for Spectrographic Calibration

NASA Astrophysics Data System (ADS)

Thomas, Neil B.

2018-04-01

The wavelength calibration of spectrographs is an essential but challenging task in many disciplines. Calibration is traditionally accomplished by imaging the spectrum of a light source containing features that are known to appear at certain wavelengths and mapping them to their location on the sensor. This is typically required in conjunction with each scientific observation to account for mechanical and optical variations of the instrument over time, which may span years for certain projects. The method presented here investigates the usage of color itself instead of spectral features to calibrate a spectrograph. The primary advantage of such a calibration is that any broad-spectrum light source such as the sky or an incandescent bulb is suitable. This method allows for calibration using the full optical pathway of the instrument instead of incorporating separate calibration equipment that may introduce errors. This paper focuses on the potential for color calibration in the field of radial velocity astronomy, in which instruments must be finely calibrated for long periods of time to detect tiny Doppler wavelength shifts. This method is not restricted to radial velocity, however, and may find application in any field requiring calibrated spectrometers such as sea water analysis, cellular biology, chemistry, atmospheric studies, and so on. This paper demonstrates that color sensors have the potential to provide calibration with greatly reduced complexity.

On-orbit characterization of hyperspectral imagers

NASA Astrophysics Data System (ADS)

McCorkel, Joel

Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne- and satellite-based sensors. Often, ground-truth measurements at these tests sites are not always successful due to weather and funding availability. Therefore, RSG has also employed automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor. This dissertation presents a method for determining the radiometric calibration of a hyperspectral imager using multispectral imagery. The work relies on a multispectral sensor, Moderate-resolution Imaging Spectroradiometer (MODIS), as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. A method to predict hyperspectral surface reflectance using a combination of MODIS data and spectral shape information is developed and applied for the characterization of Hyperion. Spectral shape information is based on RSG's historical in situ data for the Railroad Valley test site and spectral library data for the Libyan test site. Average atmospheric parameters, also based on historical measurements, are used in reflectance prediction and transfer to space. Results of several cross-calibration scenarios that differ in image acquisition coincidence, test site, and reference sensor are found for the characterization of Hyperion. These are compared with results from the reflectance-based approach of vicarious calibration, a well-documented method developed by the RSG that serves as a baseline for calibration performance for the cross-calibration method developed here. Cross-calibration provides results that are within 2% of those of reflectance-based results in most spectral regions. Larger disagreements exist for shorter wavelengths studied in this work as well as in spectral areas that experience absorption by the atmosphere.

The research on calibration methods of dual-CCD laser three-dimensional human face scanning system

NASA Astrophysics Data System (ADS)

Wang, Jinjiang; Chang, Tianyu; Ge, Baozhen; Tian, Qingguo; Yang, Fengting; Shi, Shendong

2013-09-01

In this paper, on the basis of considering the performance advantages of two-step method, we combines the stereo matching of binocular stereo vision with active laser scanning to calibrate the system. Above all, we select a reference camera coordinate system as the world coordinate system and unity the coordinates of two CCD cameras. And then obtain the new perspective projection matrix (PPM) of each camera after the epipolar rectification. By those, the corresponding epipolar equation of two cameras can be defined. So by utilizing the trigonometric parallax method, we can measure the space point position after distortion correction and achieve stereo matching calibration between two image points. Experiments verify that this method can improve accuracy and system stability is guaranteed. The stereo matching calibration has a simple process with low-cost, and simplifies regular maintenance work. It can acquire 3D coordinates only by planar checkerboard calibration without the need of designing specific standard target or using electronic theodolite. It is found that during the experiment two-step calibration error and lens distortion lead to the stratification of point cloud data. The proposed calibration method which combining active line laser scanning and binocular stereo vision has the both advantages of them. It has more flexible applicability. Theory analysis and experiment shows the method is reasonable.

Simultaneous determination of specific alpha and beta emitters by LSC-PLS in water samples.

PubMed

Fons-Castells, J; Tent-Petrus, J; Llauradó, M

2017-01-01

Liquid scintillation counting (LSC) is a commonly used technique for the determination of alpha and beta emitters. However, LSC has poor resolution and the continuous spectra for beta emitters hinder the simultaneous determination of several alpha and beta emitters from the same spectrum. In this paper, the feasibility of multivariate calibration by partial least squares (PLS) models for the determination of several alpha ( nat U, 241 Am and 226 Ra) and beta emitters ( 40 K, 60 Co, 90 Sr/ 90 Y, 134 Cs and 137 Cs) in water samples is reported. A set of alpha and beta spectra from radionuclide calibration standards were used to construct three PLS models. Experimentally mixed radionuclides and intercomparision materials were used to validate the models. The results had a maximum relative bias of 25% when all the radionuclides in the sample were included in the calibration set; otherwise the relative bias was over 100% for some radionuclides. The results obtained show that LSC-PLS is a useful approach for the simultaneous determination of alpha and beta emitters in multi-radionuclide samples. However, to obtain useful results, it is important to include all the radionuclides expected in the studied scenario in the calibration set. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development and external multicenter validation of Chinese Prostate Cancer Consortium prostate cancer risk calculator for initial prostate biopsy.

PubMed

Chen, Rui; Xie, Liping; Xue, Wei; Ye, Zhangqun; Ma, Lulin; Gao, Xu; Ren, Shancheng; Wang, Fubo; Zhao, Lin; Xu, Chuanliang; Sun, Yinghao

2016-09-01

Substantial differences exist in the relationship of prostate cancer (PCa) detection rate and prostate-specific antigen (PSA) level between Western and Asian populations. Classic Western risk calculators, European Randomized Study for Screening of Prostate Cancer Risk Calculator, and Prostate Cancer Prevention Trial Risk Calculator, were shown to be not applicable in Asian populations. We aimed to develop and validate a risk calculator for predicting the probability of PCa and high-grade PCa (defined as Gleason Score sum 7 or higher) at initial prostate biopsy in Chinese men. Urology outpatients who underwent initial prostate biopsy according to the inclusion criteria were included. The multivariate logistic regression-based Chinese Prostate Cancer Consortium Risk Calculator (CPCC-RC) was constructed with cases from 2 hospitals in Shanghai. Discriminative ability, calibration and decision curve analysis were externally validated in 3 CPCC member hospitals. Of the 1,835 patients involved, PCa was identified in 338/924 (36.6%) and 294/911 (32.3%) men in the development and validation cohort, respectively. Multivariate logistic regression analyses showed that 5 predictors (age, logPSA, logPV, free PSA ratio, and digital rectal examination) were associated with PCa (Model 1) or high-grade PCa (Model 2), respectively. The area under the curve of Model 1 and Model 2 was 0.801 (95% CI: 0.771-0.831) and 0.826 (95% CI: 0.796-0.857), respectively. Both models illustrated good calibration and substantial improvement in decision curve analyses than any single predictors at all threshold probabilities. Higher predicting accuracy, better calibration, and greater clinical benefit were achieved by CPCC-RC, compared with European Randomized Study for Screening of Prostate Cancer Risk Calculator and Prostate Cancer Prevention Trial Risk Calculator in predicting PCa. CPCC-RC performed well in discrimination and calibration and decision curve analysis in external validation compared with Western risk calculators. CPCC-RC may aid in decision-making of prostate biopsy in Chinese or in other Asian populations with similar genetic and environmental backgrounds. Copyright © 2016 Elsevier Inc. All rights reserved.

A Method of Calibrating Airspeed Installations on Airplanes at Transonic and Supersonic Speeds by the Use of Accelerometer and Attitude-Angle Measurements

NASA Technical Reports Server (NTRS)

Zalovick, John A; Lina, Lindsay J; Trant, James P , Jr

1953-01-01

A method is described for calibrating airspeed installation on airplanes at transonic and supersonic speeds in vertical-plane maneuvers in which use is made of measurements of normal and longitudinal accelerations and attitude angle. In this method all the required instrumentation is carried within the airplane. An analytical study of the effects of various sources of error on the accuracy of an airspeed calibration by the accelerometer method indicated that the required measurements can be made accurately enough to insure a satisfactory calibration.

A variable acceleration calibration system

NASA Astrophysics Data System (ADS)

Johnson, Thomas H.

2011-12-01

A variable acceleration calibration system that applies loads using gravitational and centripetal acceleration serves as an alternative, efficient and cost effective method for calibrating internal wind tunnel force balances. Two proof-of-concept variable acceleration calibration systems are designed, fabricated and tested. The NASA UT-36 force balance served as the test balance for the calibration experiments. The variable acceleration calibration systems are shown to be capable of performing three component calibration experiments with an approximate applied load error on the order of 1% of the full scale calibration loads. Sources of error are indentified using experimental design methods and a propagation of uncertainty analysis. Three types of uncertainty are indentified for the systems and are attributed to prediction error, calibration error and pure error. Angular velocity uncertainty is shown to be the largest indentified source of prediction error. The calibration uncertainties using a production variable acceleration based system are shown to be potentially equivalent to current methods. The production quality system can be realized using lighter materials and a more precise instrumentation. Further research is needed to account for balance deflection, forcing effects due to vibration, and large tare loads. A gyroscope measurement technique is shown to be capable of resolving the balance deflection angle calculation. Long term research objectives include a demonstration of a six degree of freedom calibration, and a large capacity balance calibration.

Fast calibration of electromagnetically tracked oblique-viewing rigid endoscopes.

PubMed

Liu, Xinyang; Rice, Christina E; Shekhar, Raj

2017-10-01

The oblique-viewing (i.e., angled) rigid endoscope is a commonly used tool in conventional endoscopic surgeries. The relative rotation between its two moveable parts, the telescope and the camera head, creates a rotation offset between the actual and the projection of an object in the camera image. A calibration method tailored to compensate such offset is needed. We developed a fast calibration method for oblique-viewing rigid endoscopes suitable for clinical use. In contrast to prior approaches based on optical tracking, we used electromagnetic (EM) tracking as the external tracking hardware to improve compactness and practicality. Two EM sensors were mounted on the telescope and the camera head, respectively, with considerations to minimize EM tracking errors. Single-image calibration was incorporated into the method, and a sterilizable plate, laser-marked with the calibration pattern, was also developed. Furthermore, we proposed a general algorithm to estimate the rotation center in the camera image. Formulas for updating the camera matrix in terms of clockwise and counterclockwise rotations were also developed. The proposed calibration method was validated using a conventional [Formula: see text], 5-mm laparoscope. Freehand calibrations were performed using the proposed method, and the calibration time averaged 2 min and 8 s. The calibration accuracy was evaluated in a simulated clinical setting with several surgical tools present in the magnetic field of EM tracking. The root-mean-square re-projection error averaged 4.9 pixel (range 2.4-8.5 pixel, with image resolution of [Formula: see text] for rotation angles ranged from [Formula: see text] to [Formula: see text]. We developed a method for fast and accurate calibration of oblique-viewing rigid endoscopes. The method was also designed to be performed in the operating room and will therefore support clinical translation of many emerging endoscopic computer-assisted surgical systems.

A New Calibration Method for Commercial RGB-D Sensors.

PubMed

Darwish, Walid; Tang, Shenjun; Li, Wenbin; Chen, Wu

2017-05-24

Commercial RGB-D sensors such as Kinect and Structure Sensors have been widely used in the game industry, where geometric fidelity is not of utmost importance. For applications in which high quality 3D is required, i.e., 3D building models of centimeter‑level accuracy, accurate and reliable calibrations of these sensors are required. This paper presents a new model for calibrating the depth measurements of RGB-D sensors based on the structured light concept. Additionally, a new automatic method is proposed for the calibration of all RGB-D parameters, including internal calibration parameters for all cameras, the baseline between the infrared and RGB cameras, and the depth error model. When compared with traditional calibration methods, this new model shows a significant improvement in depth precision for both near and far ranges.

Model Calibration with Censored Data

DOE PAGES

Cao, Fang; Ba, Shan; Brenneman, William A.; ...

2017-06-28

Here, the purpose of model calibration is to make the model predictions closer to reality. The classical Kennedy-O'Hagan approach is widely used for model calibration, which can account for the inadequacy of the computer model while simultaneously estimating the unknown calibration parameters. In many applications, the phenomenon of censoring occurs when the exact outcome of the physical experiment is not observed, but is only known to fall within a certain region. In such cases, the Kennedy-O'Hagan approach cannot be used directly, and we propose a method to incorporate the censoring information when performing model calibration. The method is applied tomore » study the compression phenomenon of liquid inside a bottle. The results show significant improvement over the traditional calibration methods, especially when the number of censored observations is large.« less

Assessment of opacimeter calibration according to International Standard Organization 10155.

PubMed

Gomes, J F

2001-01-01

This paper compares the calibration method for opacimeters issued by the International Standard Organization (ISO) 10155 with the manual reference method for determination of dust content in stack gases. ISO 10155 requires at least nine operational measurements, corresponding to three operational measurements per each dust emission range within the stack. The procedure is assessed by comparison with previous calibration methods for opacimeters using only two operational measurements from a set of measurements made at stacks from pulp mills. The results show that even if the international standard for opacimeter calibration requires that the calibration curve is to be obtained using 3 x 3 points, a calibration curve derived using 3 points could be, at times, acceptable in statistical terms, provided that the amplitude of individual measurements is low.

Patient-specific calibration of cone-beam computed tomography data sets for radiotherapy dose calculations and treatment plan assessment.

PubMed

MacFarlane, Michael; Wong, Daniel; Hoover, Douglas A; Wong, Eugene; Johnson, Carol; Battista, Jerry J; Chen, Jeff Z

2018-03-01

In this work, we propose a new method of calibrating cone beam computed tomography (CBCT) data sets for radiotherapy dose calculation and plan assessment. The motivation for this patient-specific calibration (PSC) method is to develop an efficient, robust, and accurate CBCT calibration process that is less susceptible to deformable image registration (DIR) errors. Instead of mapping the CT numbers voxel-by-voxel with traditional DIR calibration methods, the PSC methods generates correlation plots between deformably registered planning CT and CBCT voxel values, for each image slice. A linear calibration curve specific to each slice is then obtained by least-squares fitting, and applied to the CBCT slice's voxel values. This allows each CBCT slice to be corrected using DIR without altering the patient geometry through regional DIR errors. A retrospective study was performed on 15 head-and-neck cancer patients, each having routine CBCTs and a middle-of-treatment re-planning CT (reCT). The original treatment plan was re-calculated on the patient's reCT image set (serving as the gold standard) as well as the image sets produced by voxel-to-voxel DIR, density-overriding, and the new PSC calibration methods. Dose accuracy of each calibration method was compared to the reference reCT data set using common dose-volume metrics and 3D gamma analysis. A phantom study was also performed to assess the accuracy of the DIR and PSC CBCT calibration methods compared with planning CT. Compared with the gold standard using reCT, the average dose metric differences were ≤ 1.1% for all three methods (PSC: -0.3%; DIR: -0.7%; density-override: -1.1%). The average gamma pass rates with thresholds 3%, 3 mm were also similar among the three techniques (PSC: 95.0%; DIR: 96.1%; density-override: 94.4%). An automated patient-specific calibration method was developed which yielded strong dosimetric agreement with the results obtained using a re-planning CT for head-and-neck patients. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Research on orbit prediction for solar-based calibration proper satellite

NASA Astrophysics Data System (ADS)

Chen, Xuan; Qi, Wenwen; Xu, Peng

2018-03-01

Utilizing the mathematical model of the orbit mechanics, the orbit prediction is to forecast the space target's orbit information of a certain time based on the orbit of the initial moment. The proper satellite radiometric calibration and calibration orbit prediction process are introduced briefly. On the basis of the research of the calibration space position design method and the radiative transfer model, an orbit prediction method for proper satellite radiometric calibration is proposed to select the appropriate calibration arc for the remote sensor and to predict the orbit information of the proper satellite and the remote sensor. By analyzing the orbit constraint of the proper satellite calibration, the GF-1solar synchronous orbit is chose as the proper satellite orbit in order to simulate the calibration visible durance for different satellites to be calibrated. The results of simulation and analysis provide the basis for the improvement of the radiometric calibration accuracy of the satellite remote sensor, which lays the foundation for the high precision and high frequency radiometric calibration.

A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2013-01-01

Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between-study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta-regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example. PMID:23401213

Evaluation of a physically based quasi-linear and a conceptually based nonlinear Muskingum methods

NASA Astrophysics Data System (ADS)

Perumal, Muthiah; Tayfur, Gokmen; Rao, C. Madhusudana; Gurarslan, Gurhan

2017-03-01

Two variants of the Muskingum flood routing method formulated for accounting nonlinearity of the channel routing process are investigated in this study. These variant methods are: (1) The three-parameter conceptual Nonlinear Muskingum (NLM) method advocated by Gillin 1978, and (2) The Variable Parameter McCarthy-Muskingum (VPMM) method recently proposed by Perumal and Price in 2013. The VPMM method does not require rigorous calibration and validation procedures as required in the case of NLM method due to established relationships of its parameters with flow and channel characteristics based on hydrodynamic principles. The parameters of the conceptual nonlinear storage equation used in the NLM method were calibrated using the Artificial Intelligence Application (AIA) techniques, such as the Genetic Algorithm (GA), the Differential Evolution (DE), the Particle Swarm Optimization (PSO) and the Harmony Search (HS). The calibration was carried out on a given set of hypothetical flood events obtained by routing a given inflow hydrograph in a set of 40 km length prismatic channel reaches using the Saint-Venant (SV) equations. The validation of the calibrated NLM method was investigated using a different set of hypothetical flood hydrographs obtained in the same set of channel reaches used for calibration studies. Both the sets of solutions obtained in the calibration and validation cases using the NLM method were compared with the corresponding solutions of the VPMM method based on some pertinent evaluation measures. The results of the study reveal that the physically based VPMM method is capable of accounting for nonlinear characteristics of flood wave movement better than the conceptually based NLM method which requires the use of tedious calibration and validation procedures.

On-orbit calibration for star sensors without priori information.

PubMed

Zhang, Hao; Niu, Yanxiong; Lu, Jiazhen; Zhang, Chengfen; Yang, Yanqiang

2017-07-24

The star sensor is a prerequisite navigation device for a spacecraft. The on-orbit calibration is an essential guarantee for its operation performance. However, traditional calibration methods rely on ground information and are invalid without priori information. The uncertain on-orbit parameters will eventually influence the performance of guidance navigation and control system. In this paper, a novel calibration method without priori information for on-orbit star sensors is proposed. Firstly, the simplified back propagation neural network is designed for focal length and main point estimation along with system property evaluation, called coarse calibration. Then the unscented Kalman filter is adopted for the precise calibration of all parameters, including focal length, main point and distortion. The proposed method benefits from self-initialization and no attitude or preinstalled sensor parameter is required. Precise star sensor parameter estimation can be achieved without priori information, which is a significant improvement for on-orbit devices. Simulations and experiments results demonstrate that the calibration is easy for operation with high accuracy and robustness. The proposed method can satisfy the stringent requirement for most star sensors.

A Visual Servoing-Based Method for ProCam Systems Calibration

PubMed Central

Berry, Francois; Aider, Omar Ait; Mosnier, Jeremie

2013-01-01

Projector-camera systems are currently used in a wide field of applications, such as 3D reconstruction and augmented reality, and can provide accurate measurements, depending on the configuration and calibration. Frequently, the calibration task is divided into two steps: camera calibration followed by projector calibration. The latter still poses certain problems that are not easy to solve, such as the difficulty in obtaining a set of 2D–3D points to compute the projection matrix between the projector and the world. Existing methods are either not sufficiently accurate or not flexible. We propose an easy and automatic method to calibrate such systems that consists in projecting a calibration pattern and superimposing it automatically on a known printed pattern. The projected pattern is provided by a virtual camera observing a virtual pattern in an OpenGL model. The projector displays what the virtual camera visualizes. Thus, the projected pattern can be controlled and superimposed on the printed one with the aid of visual servoing. Our experimental results compare favorably with those of other methods considering both usability and accuracy. PMID:24084121

75 FR 8039 - Announcement of the American Petroleum Institute's Standards Activities

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-23

... Provers, 3rd Ed. MPMS Ch. 4.9.3, Methods of Calibration for Displacement and Volumetric Tank Provers, Part 3--Determination of the Volume of Displacement Provers by the Master Meter Method of Calibration, 1st Ed. MPMS Ch. 4.9.4, Methods of Calibration for Displacement and Volumetric Tank Provers, Part 4...

Absolute Radiometric Calibration of Narrow-Swath Imaging Sensors with Reference to Non-Coincident Wide-Swath Sensors

NASA Technical Reports Server (NTRS)

McCorkel, Joel; Thome, Kurtis; Lockwood, Ronald

2012-01-01

An inter-calibration method is developed to provide absolute radiometric calibration of narrow-swath imaging sensors with reference to non-coincident wide-swath sensors. The method predicts at-sensor radiance using non-coincident imagery from the reference sensor and knowledge of spectral reflectance of the test site. The imagery of the reference sensor is restricted to acquisitions that provide similar view and solar illumination geometry to reduce uncertainties due to directional reflectance effects. Spectral reflectance of the test site is found with a simple iterative radiative transfer method using radiance values of a well-understood wide-swath sensor and spectral shape information based on historical ground-based measurements. At-sensor radiance is calculated for the narrow-swath sensor using this spectral reflectance and atmospheric parameters that are also based on historical in situ measurements. Results of the inter-calibration method show agreement on the 2 5 percent level in most spectral regions with the vicarious calibration technique relying on coincident ground-based measurements referred to as the reflectance-based approach. While the variability of the inter-calibration method based on non-coincident image pairs is significantly larger, results are consistent with techniques relying on in situ measurements. The method is also insensitive to spectral differences between the sensors by transferring to surface spectral reflectance prior to prediction of at-sensor radiance. The utility of this inter-calibration method is made clear by its flexibility to utilize image pairings with acquisition dates differing in excess of 30 days allowing frequent absolute calibration comparisons between wide- and narrow-swath sensors.

Wavelet Analysis Used for Spectral Background Removal in the Determination of Glucose from Near-Infrared Single-Beam Spectra

PubMed Central

Wan, Boyong; Small, Gary W.

2010-01-01

Wavelet analysis is developed as a preprocessing tool for use in removing background information from near-infrared (near-IR) single-beam spectra before the construction of multivariate calibration models. Three data sets collected with three different near-IR spectrometers are investigated that involve the determination of physiological levels of glucose (1-30 mM) in a simulated biological matrix containing alanine, ascorbate, lactate, triacetin, and urea in phosphate buffer. A factorial design is employed to optimize the specific wavelet function used and the level of decomposition applied, in addition to the spectral range and number of latent variables associated with a partial least-squares calibration model. The prediction performance of the computed models is studied with separate data acquired after the collection of the calibration spectra. This evaluation includes one data set collected over a period of more than six months. Preprocessing with wavelet analysis is also compared to the calculation of second-derivative spectra. Over the three data sets evaluated, wavelet analysis is observed to produce better-performing calibration models, with improvements in concentration predictions on the order of 30% being realized relative to models based on either second-derivative spectra or spectra preprocessed with simple additive and multiplicative scaling correction. This methodology allows the construction of stable calibrations directly with single-beam spectra, thereby eliminating the need for the collection of a separate background or reference spectrum. PMID:21035604

Wavelet analysis used for spectral background removal in the determination of glucose from near-infrared single-beam spectra.

PubMed

Wan, Boyong; Small, Gary W

2010-11-29

Wavelet analysis is developed as a preprocessing tool for use in removing background information from near-infrared (near-IR) single-beam spectra before the construction of multivariate calibration models. Three data sets collected with three different near-IR spectrometers are investigated that involve the determination of physiological levels of glucose (1-30 mM) in a simulated biological matrix containing alanine, ascorbate, lactate, triacetin, and urea in phosphate buffer. A factorial design is employed to optimize the specific wavelet function used and the level of decomposition applied, in addition to the spectral range and number of latent variables associated with a partial least-squares calibration model. The prediction performance of the computed models is studied with separate data acquired after the collection of the calibration spectra. This evaluation includes one data set collected over a period of more than 6 months. Preprocessing with wavelet analysis is also compared to the calculation of second-derivative spectra. Over the three data sets evaluated, wavelet analysis is observed to produce better-performing calibration models, with improvements in concentration predictions on the order of 30% being realized relative to models based on either second-derivative spectra or spectra preprocessed with simple additive and multiplicative scaling correction. This methodology allows the construction of stable calibrations directly with single-beam spectra, thereby eliminating the need for the collection of a separate background or reference spectrum. Copyright © 2010 Elsevier B.V. All rights reserved.

Calibration of Multiple In Silico Tools for Predicting Pathogenicity of Mismatch Repair Gene Missense Substitutions

PubMed Central

Thompson, Bryony A.; Greenblatt, Marc S.; Vallee, Maxime P.; Herkert, Johanna C.; Tessereau, Chloe; Young, Erin L.; Adzhubey, Ivan A.; Li, Biao; Bell, Russell; Feng, Bingjian; Mooney, Sean D.; Radivojac, Predrag; Sunyaev, Shamil R.; Frebourg, Thierry; Hofstra, Robert M.W.; Sijmons, Rolf H.; Boucher, Ken; Thomas, Alun; Goldgar, David E.; Spurdle, Amanda B.; Tavtigian, Sean V.

2015-01-01

Classification of rare missense substitutions observed during genetic testing for patient management is a considerable problem in clinical genetics. The Bayesian integrated evaluation of unclassified variants is a solution originally developed for BRCA1/2. Here, we take a step toward an analogous system for the mismatch repair (MMR) genes (MLH1, MSH2, MSH6, and PMS2) that confer colon cancer susceptibility in Lynch syndrome by calibrating in silico tools to estimate prior probabilities of pathogenicity for MMR gene missense substitutions. A qualitative five-class classification system was developed and applied to 143 MMR missense variants. This identified 74 missense substitutions suitable for calibration. These substitutions were scored using six different in silico tools (Align-Grantham Variation Grantham Deviation, multivariate analysis of protein polymorphisms [MAPP], Mut-Pred, PolyPhen-2.1, Sorting Intolerant From Tolerant, and Xvar), using curated MMR multiple sequence alignments where possible. The output from each tool was calibrated by regression against the classifications of the 74 missense substitutions; these calibrated outputs are interpretable as prior probabilities of pathogenicity. MAPP was the most accurate tool and MAPP + PolyPhen-2.1 provided the best-combined model (R2 = 0.62 and area under receiver operating characteristic = 0.93). The MAPP + PolyPhen-2.1 output is sufficiently predictive to feed as a continuous variable into the quantitative Bayesian integrated evaluation for clinical classification of MMR gene missense substitutions. PMID:22949387

Non-orthogonal tool/flange and robot/world calibration.

PubMed

Ernst, Floris; Richter, Lars; Matthäus, Lars; Martens, Volker; Bruder, Ralf; Schlaefer, Alexander; Schweikard, Achim

2012-12-01

For many robot-assisted medical applications, it is necessary to accurately compute the relation between the robot's coordinate system and the coordinate system of a localisation or tracking device. Today, this is typically carried out using hand-eye calibration methods like those proposed by Tsai/Lenz or Daniilidis. We present a new method for simultaneous tool/flange and robot/world calibration by estimating a solution to the matrix equation AX = YB. It is computed using a least-squares approach. Because real robots and localisation are all afflicted by errors, our approach allows for non-orthogonal matrices, partially compensating for imperfect calibration of the robot or localisation device. We also introduce a new method where full robot/world and partial tool/flange calibration is possible by using localisation devices providing less than six degrees of freedom (DOFs). The methods are evaluated on simulation data and on real-world measurements from optical and magnetical tracking devices, volumetric ultrasound providing 3-DOF data, and a surface laser scanning device. We compare our methods with two classical approaches: the method by Tsai/Lenz and the method by Daniilidis. In all experiments, the new algorithms outperform the classical methods in terms of translational accuracy by up to 80% and perform similarly in terms of rotational accuracy. Additionally, the methods are shown to be stable: the number of calibration stations used has far less influence on calibration quality than for the classical methods. Our work shows that the new method can be used for estimating the relationship between the robot's and the localisation device's coordinate systems. The new method can also be used for deficient systems providing only 3-DOF data, and it can be employed in real-time scenarios because of its speed. Copyright © 2012 John Wiley & Sons, Ltd.

Use of chemometrics to compare NIR and HPLC for the simultaneous determination of drug levels in fixed-dose combination tablets employed in tuberculosis treatment.

PubMed

Teixeira, Kelly Sivocy Sampaio; da Cruz Fonseca, Said Gonçalves; de Moura, Luís Carlos Brigido; de Moura, Mario Luís Ribeiro; Borges, Márcia Herminia Pinheiro; Barbosa, Euzébio Guimaraes; De Lima E Moura, Túlio Flávio Accioly

2018-02-05

The World Health Organization recommends that TB treatment be administered using combination therapy. The methodologies for quantifying simultaneously associated drugs are highly complex, being costly, extremely time consuming and producing chemical residues harmful to the environment. The need to seek alternative techniques that minimize these drawbacks is widely discussed in the pharmaceutical industry. Therefore, the objective of this study was to develop and validate a multivariate calibration model in association with the near infrared spectroscopy technique (NIR) for the simultaneous determination of rifampicin, isoniazid, pyrazinamide and ethambutol. These models allow the quality control of these medicines to be optimized using simple, fast, low-cost techniques that produce no chemical waste. In the NIR - PLS method, spectra readings were acquired in the 10,000-4000cm -1 range using an infrared spectrophotometer (IRPrestige - 21 - Shimadzu) with a resolution of 4cm -1 , 20 sweeps, under controlled temperature and humidity. For construction of the model, the central composite experimental design was employed on the program Statistica 13 (StatSoft Inc.). All spectra were treated by computational tools for multivariate analysis using partial least squares regression (PLS) on the software program Pirouette 3.11 (Infometrix, Inc.). Variable selections were performed by the QSAR modeling program. The models developed by NIR in association with multivariate analysis provided good prediction of the APIs for the external samples and were therefore validated. For the tablets, however, the slightly different quantitative compositions of excipients compared to the mixtures prepared for building the models led to results that were not statistically similar, despite having prediction errors considered acceptable in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.

Regression Analysis and Calibration Recommendations for the Characterization of Balance Temperature Effects

NASA Technical Reports Server (NTRS)

Ulbrich, N.; Volden, T.

2018-01-01

Analysis and use of temperature-dependent wind tunnel strain-gage balance calibration data are discussed in the paper. First, three different methods are presented and compared that may be used to process temperature-dependent strain-gage balance data. The first method uses an extended set of independent variables in order to process the data and predict balance loads. The second method applies an extended load iteration equation during the analysis of balance calibration data. The third method uses temperature-dependent sensitivities for the data analysis. Physical interpretations of the most important temperature-dependent regression model terms are provided that relate temperature compensation imperfections and the temperature-dependent nature of the gage factor to sets of regression model terms. Finally, balance calibration recommendations are listed so that temperature-dependent calibration data can be obtained and successfully processed using the reviewed analysis methods.

A Review on Microdialysis Calibration Methods: the Theory and Current Related Efforts.

PubMed

Kho, Chun Min; Enche Ab Rahim, Siti Kartini; Ahmad, Zainal Arifin; Abdullah, Norazharuddin Shah

2017-07-01

Microdialysis is a sampling technique first introduced in the late 1950s. Although this technique was originally designed to study endogenous compounds in animal brain, it is later modified to be used in other organs. Additionally, microdialysis is not only able to collect unbound concentration of compounds from tissue sites; this technique can also be used to deliver exogenous compounds to a designated area. Due to its versatility, microdialysis technique is widely employed in a number of areas, including biomedical research. However, for most in vivo studies, the concentration of substance obtained directly from the microdialysis technique does not accurately describe the concentration of the substance on-site. In order to relate the results collected from microdialysis to the actual in vivo condition, a calibration method is required. To date, various microdialysis calibration methods have been reported, with each method being capable to provide valuable insights of the technique itself and its applications. This paper aims to provide a critical review on various calibration methods used in microdialysis applications, inclusive of a detailed description of the microdialysis technique itself to start with. It is expected that this article shall review in detail, the various calibration methods employed, present examples of work related to each calibration method including clinical efforts, plus the advantages and disadvantages of each of the methods.

Apparatus for in-situ calibration of instruments that measure fluid depth

DOEpatents

Campbell, M.D.

1994-01-11

The present invention provides a method and apparatus for in-situ calibration of distance measuring equipment. The method comprises obtaining a first distance measurement in a first location, then obtaining at least one other distance measurement in at least one other location of a precisely known distance from the first location, and calculating a calibration constant. The method is applied specifically to calculating a calibration constant for obtaining fluid level and embodied in an apparatus using a pressure transducer and a spacer of precisely known length. The calibration constant is used to calculate the depth of a fluid from subsequent single pressure measurements at any submerged position. 8 figures.

Effects of calibration methods on quantitative material decomposition in photon-counting spectral computed tomography using a maximum a posteriori estimator.

PubMed

Curtis, Tyler E; Roeder, Ryan K

2017-10-01

Advances in photon-counting detectors have enabled quantitative material decomposition using multi-energy or spectral computed tomography (CT). Supervised methods for material decomposition utilize an estimated attenuation for each material of interest at each photon energy level, which must be calibrated based upon calculated or measured values for known compositions. Measurements using a calibration phantom can advantageously account for system-specific noise, but the effect of calibration methods on the material basis matrix and subsequent quantitative material decomposition has not been experimentally investigated. Therefore, the objective of this study was to investigate the influence of the range and number of contrast agent concentrations within a modular calibration phantom on the accuracy of quantitative material decomposition in the image domain. Gadolinium was chosen as a model contrast agent in imaging phantoms, which also contained bone tissue and water as negative controls. The maximum gadolinium concentration (30, 60, and 90 mM) and total number of concentrations (2, 4, and 7) were independently varied to systematically investigate effects of the material basis matrix and scaling factor calibration on the quantitative (root mean squared error, RMSE) and spatial (sensitivity and specificity) accuracy of material decomposition. Images of calibration and sample phantoms were acquired using a commercially available photon-counting spectral micro-CT system with five energy bins selected to normalize photon counts and leverage the contrast agent k-edge. Material decomposition of gadolinium, calcium, and water was performed for each calibration method using a maximum a posteriori estimator. Both the quantitative and spatial accuracy of material decomposition were most improved by using an increased maximum gadolinium concentration (range) in the basis matrix calibration; the effects of using a greater number of concentrations were relatively small in magnitude by comparison. The material basis matrix calibration was more sensitive to changes in the calibration methods than the scaling factor calibration. The material basis matrix calibration significantly influenced both the quantitative and spatial accuracy of material decomposition, while the scaling factor calibration influenced quantitative but not spatial accuracy. Importantly, the median RMSE of material decomposition was as low as ~1.5 mM (~0.24 mg/mL gadolinium), which was similar in magnitude to that measured by optical spectroscopy on the same samples. The accuracy of quantitative material decomposition in photon-counting spectral CT was significantly influenced by calibration methods which must therefore be carefully considered for the intended diagnostic imaging application. © 2017 American Association of Physicists in Medicine.

Simulation of temperature field for temperature-controlled radio frequency ablation using a hyperbolic bioheat equation and temperature-varied voltage calibration: a liver-mimicking phantom study.

PubMed

Zhang, Man; Zhou, Zhuhuang; Wu, Shuicai; Lin, Lan; Gao, Hongjian; Feng, Yusheng

2015-12-21

This study aims at improving the accuracy of temperature simulation for temperature-controlled radio frequency ablation (RFA). We proposed a new voltage-calibration method in the simulation and investigated the feasibility of a hyperbolic bioheat equation (HBE) in the RFA simulation with longer durations and higher power. A total of 40 RFA experiments was conducted in a liver-mimicking phantom. Four mathematical models with multipolar electrodes were developed by the finite element method in COMSOL software: HBE with/without voltage calibration, and the Pennes bioheat equation (PBE) with/without voltage calibration. The temperature-varied voltage calibration used in the simulation was calculated from an experimental power output and temperature-dependent resistance of liver tissue. We employed the HBE in simulation by considering the delay time τ of 16 s. First, for simulations by each kind of bioheat equation (PBE or HBE), we compared the differences between the temperature-varied voltage-calibration and the fixed-voltage values used in the simulations. Then, the comparisons were conducted between the PBE and the HBE in the simulations with temperature-varied voltage calibration. We verified the simulation results by experimental temperature measurements on nine specific points of the tissue phantom. The results showed that: (1) the proposed voltage-calibration method improved the simulation accuracy of temperature-controlled RFA for both the PBE and the HBE, and (2) for temperature-controlled RFA simulation with the temperature-varied voltage calibration, the HBE method was 0.55 °C more accurate than the PBE method. The proposed temperature-varied voltage calibration may be useful in temperature field simulations of temperature-controlled RFA. Besides, the HBE may be used as an alternative in the simulation of long-duration high-power RFA.

Simultaneous auto-calibration and gradient delays estimation (SAGE) in non-Cartesian parallel MRI using low-rank constraints.

PubMed

Jiang, Wenwen; Larson, Peder E Z; Lustig, Michael

2018-03-09

To correct gradient timing delays in non-Cartesian MRI while simultaneously recovering corruption-free auto-calibration data for parallel imaging, without additional calibration scans. The calibration matrix constructed from multi-channel k-space data should be inherently low-rank. This property is used to construct reconstruction kernels or sensitivity maps. Delays between the gradient hardware across different axes and RF receive chain, which are relatively benign in Cartesian MRI (excluding EPI), lead to trajectory deviations and hence data inconsistencies for non-Cartesian trajectories. These in turn lead to higher rank and corrupted calibration information which hampers the reconstruction. Here, a method named Simultaneous Auto-calibration and Gradient delays Estimation (SAGE) is proposed that estimates the actual k-space trajectory while simultaneously recovering the uncorrupted auto-calibration data. This is done by estimating the gradient delays that result in the lowest rank of the calibration matrix. The Gauss-Newton method is used to solve the non-linear problem. The method is validated in simulations using center-out radial, projection reconstruction and spiral trajectories. Feasibility is demonstrated on phantom and in vivo scans with center-out radial and projection reconstruction trajectories. SAGE is able to estimate gradient timing delays with high accuracy at a signal to noise ratio level as low as 5. The method is able to effectively remove artifacts resulting from gradient timing delays and restore image quality in center-out radial, projection reconstruction, and spiral trajectories. The low-rank based method introduced simultaneously estimates gradient timing delays and provides accurate auto-calibration data for improved image quality, without any additional calibration scans. © 2018 International Society for Magnetic Resonance in Medicine.

Dry calibration of electromagnetic flowmeters based on numerical models combining multiple physical phenomena (multiphysics)

NASA Astrophysics Data System (ADS)

Fu, X.; Hu, L.; Lee, K. M.; Zou, J.; Ruan, X. D.; Yang, H. Y.

2010-10-01

This paper presents a method for dry calibration of an electromagnetic flowmeter (EMF). This method, which determines the voltage induced in the EMF as conductive liquid flows through a magnetic field, numerically solves a coupled set of multiphysical equations with measured boundary conditions for the magnetic, electric, and flow fields in the measuring pipe of the flowmeter. Specifically, this paper details the formulation of dry calibration and an efficient algorithm (that adaptively minimizes the number of measurements and requires only the normal component of the magnetic flux density as boundary conditions on the pipe surface to reconstruct the magnetic field involved) for computing the sensitivity of EMF. Along with an in-depth discussion on factors that could significantly affect the final precision of a dry calibrated EMF, the effects of flow disturbance on measuring errors have been experimentally studied by installing a baffle at the inflow port of the EMF. Results of the dry calibration on an actual EMF were compared against flow-rig calibration; excellent agreements (within 0.3%) between dry calibration and flow-rig tests verify the multiphysical computation of the fields and the robustness of the method. As requiring no actual flow, the dry calibration is particularly useful for calibrating large-diameter EMFs where conventional flow-rig methods are often costly and difficult to implement.

The Value of Hydrograph Partitioning Curves for Calibrating Hydrological Models in Glacierized Basins

NASA Astrophysics Data System (ADS)

He, Zhihua; Vorogushyn, Sergiy; Unger-Shayesteh, Katy; Gafurov, Abror; Kalashnikova, Olga; Omorova, Elvira; Merz, Bruno

2018-03-01

This study refines the method for calibrating a glacio-hydrological model based on Hydrograph Partitioning Curves (HPCs), and evaluates its value in comparison to multidata set optimization approaches which use glacier mass balance, satellite snow cover images, and discharge. The HPCs are extracted from the observed flow hydrograph using catchment precipitation and temperature gradients. They indicate the periods when the various runoff processes, such as glacier melt or snow melt, dominate the basin hydrograph. The annual cumulative curve of the difference between average daily temperature and melt threshold temperature over the basin, as well as the annual cumulative curve of average daily snowfall on the glacierized areas are used to identify the starting and end dates of snow and glacier ablation periods. Model parameters characterizing different runoff processes are calibrated on different HPCs in a stepwise and iterative way. Results show that the HPC-based method (1) delivers model-internal consistency comparably to the tri-data set calibration method; (2) improves the stability of calibrated parameter values across various calibration periods; and (3) estimates the contributions of runoff components similarly to the tri-data set calibration method. Our findings indicate the potential of the HPC-based approach as an alternative for hydrological model calibration in glacierized basins where other calibration data sets than discharge are often not available or very costly to obtain.

Detection of Nitrogen Content in Rubber Leaves Using Near-Infrared (NIR) Spectroscopy with Correlation-Based Successive Projections Algorithm (SPA).

PubMed

Tang, Rongnian; Chen, Xupeng; Li, Chuang

2018-05-01

Near-infrared spectroscopy is an efficient, low-cost technology that has potential as an accurate method in detecting the nitrogen content of natural rubber leaves. Successive projections algorithm (SPA) is a widely used variable selection method for multivariate calibration, which uses projection operations to select a variable subset with minimum multi-collinearity. However, due to the fluctuation of correlation between variables, high collinearity may still exist in non-adjacent variables of subset obtained by basic SPA. Based on analysis to the correlation matrix of the spectra data, this paper proposed a correlation-based SPA (CB-SPA) to apply the successive projections algorithm in regions with consistent correlation. The result shows that CB-SPA can select variable subsets with more valuable variables and less multi-collinearity. Meanwhile, models established by the CB-SPA subset outperform basic SPA subsets in predicting nitrogen content in terms of both cross-validation and external prediction. Moreover, CB-SPA is assured to be more efficient, for the time cost in its selection procedure is one-twelfth that of the basic SPA.

Removal of batch effects using distribution-matching residual networks.

PubMed

Shaham, Uri; Stanton, Kelly P; Zhao, Jun; Li, Huamin; Raddassi, Khadir; Montgomery, Ruth; Kluger, Yuval

2017-08-15

Sources of variability in experimentally derived data include measurement error in addition to the physical phenomena of interest. This measurement error is a combination of systematic components, originating from the measuring instrument and random measurement errors. Several novel biological technologies, such as mass cytometry and single-cell RNA-seq (scRNA-seq), are plagued with systematic errors that may severely affect statistical analysis if the data are not properly calibrated. We propose a novel deep learning approach for removing systematic batch effects. Our method is based on a residual neural network, trained to minimize the Maximum Mean Discrepancy between the multivariate distributions of two replicates, measured in different batches. We apply our method to mass cytometry and scRNA-seq datasets, and demonstrate that it effectively attenuates batch effects. our codes and data are publicly available at https://github.com/ushaham/BatchEffectRemoval.git. yuval.kluger@yale.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Determination of total polyphenol index in wines employing a voltammetric electronic tongue.

PubMed

Cetó, Xavier; Gutiérrez, Juan Manuel; Gutiérrez, Manuel; Céspedes, Francisco; Capdevila, Josefina; Mínguez, Santiago; Jiménez-Jorquera, Cecilia; del Valle, Manel

2012-06-30

This work reports the application of a voltammetric electronic tongue system (ET) made from an array of modified graphite-epoxy composites plus a gold microelectrode in the qualitative and quantitative analysis of polyphenols found in wine. Wine samples were analyzed using cyclic voltammetry without any sample pretreatment. The obtained responses were preprocessed employing discrete wavelet transform (DWT) in order to compress and extract significant features from the voltammetric signals, and the obtained approximation coefficients fed a multivariate calibration method (artificial neural network-ANN-or partial least squares-PLS-) which accomplished the quantification of total polyphenol content. External test subset samples results were compared with the ones obtained with the Folin-Ciocalteu (FC) method and UV absorbance polyphenol index (I(280)) as reference values, with highly significant correlation coefficients of 0.979 and 0.963 in the range from 50 to 2400 mg L(-1) gallic acid equivalents, respectively. In a separate experiment, qualitative discrimination of different polyphenols found in wine was also assessed by principal component analysis (PCA). Copyright © 2012 Elsevier B.V. All rights reserved.

Near infra red spectroscopy as a multivariate process analytical tool for predicting pharmaceutical co-crystal concentration.

PubMed

Wood, Clive; Alwati, Abdolati; Halsey, Sheelagh; Gough, Tim; Brown, Elaine; Kelly, Adrian; Paradkar, Anant

2016-09-10

The use of near infra red spectroscopy to predict the concentration of two pharmaceutical co-crystals; 1:1 ibuprofen-nicotinamide (IBU-NIC) and 1:1 carbamazepine-nicotinamide (CBZ-NIC) has been evaluated. A partial least squares (PLS) regression model was developed for both co-crystal pairs using sets of standard samples to create calibration and validation data sets with which to build and validate the models. Parameters such as the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP) and correlation coefficient were used to assess the accuracy and linearity of the models. Accurate PLS regression models were created for both co-crystal pairs which can be used to predict the co-crystal concentration in a powder mixture of the co-crystal and the active pharmaceutical ingredient (API). The IBU-NIC model had smaller errors than the CBZ-NIC model, possibly due to the complex CBZ-NIC spectra which could reflect the different arrangement of hydrogen bonding associated with the co-crystal compared to the IBU-NIC co-crystal. These results suggest that NIR spectroscopy can be used as a PAT tool during a variety of pharmaceutical co-crystal manufacturing methods and the presented data will facilitate future offline and in-line NIR studies involving pharmaceutical co-crystals. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Nomograms Predicting Progression-Free Survival, Overall Survival, and Pelvic Recurrence in Locally Advanced Cervical Cancer Developed From an Analysis of Identifiable Prognostic Factors in Patients From NRG Oncology/Gynecologic Oncology Group Randomized Trials of Chemoradiotherapy

PubMed Central

Rose, Peter G.; Java, James; Whitney, Charles W.; Stehman, Frederick B.; Lanciano, Rachelle; Thomas, Gillian M.; DiSilvestro, Paul A.

2015-01-01

Purpose To evaluate the prognostic factors in locally advanced cervical cancer limited to the pelvis and develop nomograms for 2-year progression-free survival (PFS), 5-year overall survival (OS), and pelvic recurrence. Patients and Methods We retrospectively reviewed 2,042 patients with locally advanced cervical carcinoma enrolled onto Gynecologic Oncology Group clinical trials of concurrent cisplatin-based chemotherapy and radiotherapy. Nomograms for 2-year PFS, five-year OS, and pelvic recurrence were created as visualizations of Cox proportional hazards regression models. The models were validated by bootstrap-corrected, relatively unbiased estimates of discrimination and calibration. Results Multivariable analysis identified prognostic factors including histology, race/ethnicity, performance status, tumor size, International Federation of Gynecology and Obstetrics stage, tumor grade, pelvic node status, and treatment with concurrent cisplatin-based chemotherapy. PFS, OS, and pelvic recurrence nomograms had bootstrap-corrected concordance indices of 0.62, 0.64, and 0.73, respectively, and were well calibrated. Conclusion Prognostic factors were used to develop nomograms for 2-year PFS, 5-year OS, and pelvic recurrence for locally advanced cervical cancer clinically limited to the pelvis treated with concurrent cisplatin-based chemotherapy and radiotherapy. These nomograms can be used to better estimate individual and collective outcomes. PMID:25732170

Multivariate optimization of the factors influencing the solid-phase microextraction of pyrethroid pesticides in water.

PubMed

Casas, Vanessa; Llompart, Maria; García-Jares, Carmen; Cela, Rafael; Dagnac, Thierry

2006-08-18

A method based on solid-phase microextraction (SPME) and gas chromatography with micro-electron capture detection (GC-microECD) has been optimized for the analysis of pyrethroids in water samples. The influence of parameters such as temperature, fibre coating, salting-out effect and sampling mode on the extraction efficiency has been studied by means of a mix-level factorial design, which allowed the study of main effects as well as two factor interactions. Finally, a method based on direct SPME at 50 degrees C, using polydimethylsiloxane fibre is proposed. The method showed good linearity (R2>0.995) and repeatability (RSD

[Monitoring method for macroporous resin column chromatography process of salvianolic acids based on near infrared spectroscopy].

PubMed

Hou, Xiang-Mei; Zhang, Lei; Yue, Hong-Shui; Ju, Ai-Chun; Ye, Zheng-Liang

2016-07-01

To study and establish a monitoring method for macroporous resin column chromatography process of salvianolic acids by using near infrared spectroscopy (NIR) as a process analytical technology (PAT).The multivariate statistical process control (MSPC) model was developed based on 7 normal operation batches, and 2 test batches (including one normal operation batch and one abnormal operation batch) were used to verify the monitoring performance of this model. The results showed that MSPC model had a good monitoring ability for the column chromatography process. Meanwhile, NIR quantitative calibration model was established for three key quality indexes (rosmarinic acid, lithospermic acid and salvianolic acid B) by using partial least squares (PLS) algorithm. The verification results demonstrated that this model had satisfactory prediction performance. The combined application of the above two models could effectively achieve real-time monitoring for macroporous resin column chromatography process of salvianolic acids, and can be used to conduct on-line analysis of key quality indexes. This established process monitoring method could provide reference for the development of process analytical technology for traditional Chinese medicines manufacturing. Copyright© by the Chinese Pharmaceutical Association.

Green analytical determination of emerging pollutants in environmental waters using excitation-emission photoinduced fluorescence data and multivariate calibration.

PubMed

Hurtado-Sánchez, María Del Carmen; Lozano, Valeria A; Rodríguez-Cáceres, María Isabel; Durán-Merás, Isabel; Escandar, Graciela M

2015-03-01

An eco-friendly strategy for the simultaneous quantification of three emerging pharmaceutical contaminants is presented. The proposed analytical method, which involves photochemically induced fluorescence matrix data combined with second-order chemometric analysis, was used for the determination of carbamazepine, ofloxacin and piroxicam in water samples of different complexity without the need of chromatographic separation. Excitation-emission photoinduced fluorescence matrices were obtained after UV irradiation, and processed with second-order algorithms. Only one of the tested algorithms was able to overcome the strong spectral overlapping among the studied pollutants and allowed their successful quantitation in very interferent media. The method sensitivity in superficial and underground water samples was enhanced by a simple solid-phase extraction with C18 membranes, which was successful for the extraction/preconcentration of the pollutants at trace levels. Detection limits in preconcentrated (1:125) real water samples ranged from 0.04 to 0.3 ng mL(-1). Relative prediction errors around 10% were achieved. The proposed strategy is significantly simpler and greener than liquid chromatography-mass spectrometry methods, without compromising the analytical quality of the results. Copyright © 2014 Elsevier B.V. All rights reserved.

Gaussian-based routines to impute categorical variables in health surveys.

PubMed

Yucel, Recai M; He, Yulei; Zaslavsky, Alan M

2011-12-20

The multivariate normal (MVN) distribution is arguably the most popular parametric model used in imputation and is available in most software packages (e.g., SAS PROC MI, R package norm). When it is applied to categorical variables as an approximation, practitioners often either apply simple rounding techniques for ordinal variables or create a distinct 'missing' category and/or disregard the nominal variable from the imputation phase. All of these practices can potentially lead to biased and/or uninterpretable inferences. In this work, we develop a new rounding methodology calibrated to preserve observed distributions to multiply impute missing categorical covariates. The major attractiveness of this method is its flexibility to use any 'working' imputation software, particularly those based on MVN, allowing practitioners to obtain usable imputations with small biases. A simulation study demonstrates the clear advantage of the proposed method in rounding ordinal variables and, in some scenarios, its plausibility in imputing nominal variables. We illustrate our methods on a widely used National Survey of Children with Special Health Care Needs where incomplete values on race posed a valid threat on inferences pertaining to disparities. Copyright © 2011 John Wiley & Sons, Ltd.

A new time calibration method for switched-capacitor-array-based waveform samplers

NASA Astrophysics Data System (ADS)

Kim, H.; Chen, C.-T.; Eclov, N.; Ronzhin, A.; Murat, P.; Ramberg, E.; Los, S.; Moses, W.; Choong, W.-S.; Kao, C.-M.

2014-12-01

We have developed a new time calibration method for the DRS4 waveform sampler that enables us to precisely measure the non-uniform sampling interval inherent in the switched-capacitor cells of the DRS4. The method uses the proportionality between the differential amplitude and sampling interval of adjacent switched-capacitor cells responding to a sawtooth-shape pulse. In the experiment, a sawtooth-shape pulse with a 40 ns period generated by a Tektronix AWG7102 is fed to a DRS4 evaluation board for calibrating the sampling intervals of all 1024 cells individually. The electronic time resolution of the DRS4 evaluation board with the new time calibration is measured to be 2.4 ps RMS by using two simultaneous Gaussian pulses with 2.35 ns full-width at half-maximum and applying a Gaussian fit. The time resolution dependencies on the time difference with the new time calibration are measured and compared to results obtained by another method. The new method could be applicable for other switched-capacitor-array technology-based waveform samplers for precise time calibration.

A New Time Calibration Method for Switched-capacitor-array-based Waveform Samplers.

PubMed

Kim, H; Chen, C-T; Eclov, N; Ronzhin, A; Murat, P; Ramberg, E; Los, S; Moses, W; Choong, W-S; Kao, C-M

2014-12-11

We have developed a new time calibration method for the DRS4 waveform sampler that enables us to precisely measure the non-uniform sampling interval inherent in the switched-capacitor cells of the DRS4. The method uses the proportionality between the differential amplitude and sampling interval of adjacent switched-capacitor cells responding to a sawtooth-shape pulse. In the experiment, a sawtooth-shape pulse with a 40 ns period generated by a Tektronix AWG7102 is fed to a DRS4 evaluation board for calibrating the sampling intervals of all 1024 cells individually. The electronic time resolution of the DRS4 evaluation board with the new time calibration is measured to be ~2.4 ps RMS by using two simultaneous Gaussian pulses with 2.35 ns full-width at half-maximum and applying a Gaussian fit. The time resolution dependencies on the time difference with the new time calibration are measured and compared to results obtained by another method. The new method could be applicable for other switched-capacitor-array technology-based waveform samplers for precise time calibration.

A New Time Calibration Method for Switched-capacitor-array-based Waveform Samplers

PubMed Central

Kim, H.; Chen, C.-T.; Eclov, N.; Ronzhin, A.; Murat, P.; Ramberg, E.; Los, S.; Moses, W.; Choong, W.-S.; Kao, C.-M.

2014-01-01

We have developed a new time calibration method for the DRS4 waveform sampler that enables us to precisely measure the non-uniform sampling interval inherent in the switched-capacitor cells of the DRS4. The method uses the proportionality between the differential amplitude and sampling interval of adjacent switched-capacitor cells responding to a sawtooth-shape pulse. In the experiment, a sawtooth-shape pulse with a 40 ns period generated by a Tektronix AWG7102 is fed to a DRS4 evaluation board for calibrating the sampling intervals of all 1024 cells individually. The electronic time resolution of the DRS4 evaluation board with the new time calibration is measured to be ~2.4 ps RMS by using two simultaneous Gaussian pulses with 2.35 ns full-width at half-maximum and applying a Gaussian fit. The time resolution dependencies on the time difference with the new time calibration are measured and compared to results obtained by another method. The new method could be applicable for other switched-capacitor-array technology-based waveform samplers for precise time calibration. PMID:25506113

Application of six sigma and AHP in analysis of variable lead time calibration process instrumentation

NASA Astrophysics Data System (ADS)

Rimantho, Dino; Rahman, Tomy Abdul; Cahyadi, Bambang; Tina Hernawati, S.

2017-02-01

Calibration of instrumentation equipment in the pharmaceutical industry is an important activity to determine the true value of a measurement. Preliminary studies indicated that occur lead-time calibration resulted in disruption of production and laboratory activities. This study aimed to analyze the causes of lead-time calibration. Several methods used in this study such as, Six Sigma in order to determine the capability process of the calibration instrumentation of equipment. Furthermore, the method of brainstorming, Pareto diagrams, and Fishbone diagrams were used to identify and analyze the problems. Then, the method of Hierarchy Analytical Process (AHP) was used to create a hierarchical structure and prioritize problems. The results showed that the value of DPMO around 40769.23 which was equivalent to the level of sigma in calibration equipment approximately 3,24σ. This indicated the need for improvements in the calibration process. Furthermore, the determination of problem-solving strategies Lead Time Calibration such as, shortens the schedule preventive maintenance, increase the number of instrument Calibrators, and train personnel. Test results on the consistency of the whole matrix of pairwise comparisons and consistency test showed the value of hierarchy the CR below 0.1.

Comparison of global optimization approaches for robust calibration of hydrologic model parameters

NASA Astrophysics Data System (ADS)

Jung, I. W.

2015-12-01

Robustness of the calibrated parameters of hydrologic models is necessary to provide a reliable prediction of future performance of watershed behavior under varying climate conditions. This study investigated calibration performances according to the length of calibration period, objective functions, hydrologic model structures and optimization methods. To do this, the combination of three global optimization methods (i.e. SCE-UA, Micro-GA, and DREAM) and four hydrologic models (i.e. SAC-SMA, GR4J, HBV, and PRMS) was tested with different calibration periods and objective functions. Our results showed that three global optimization methods provided close calibration performances under different calibration periods, objective functions, and hydrologic models. However, using the agreement of index, normalized root mean square error, Nash-Sutcliffe efficiency as the objective function showed better performance than using correlation coefficient and percent bias. Calibration performances according to different calibration periods from one year to seven years were hard to generalize because four hydrologic models have different levels of complexity and different years have different information content of hydrological observation. Acknowledgements This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Influence of Ultrasonic Nonlinear Propagation on Hydrophone Calibration Using Two-Transducer Reciprocity Method

NASA Astrophysics Data System (ADS)

Yoshioka, Masahiro; Sato, Sojun; Kikuchi, Tsuneo; Matsuda, Yoichi

2006-05-01

In this study, the influence of ultrasonic nonlinear propagation on hydrophone calibration by the two-transducer reciprocity method is investigated quantitatively using the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation. It is proposed that the correction for the diffraction and attenuation of ultrasonic waves used in two-transducer reciprocity calibration can be derived using the KZK equation to remove the influence of nonlinear propagation. The validity of the correction is confirmed by comparing the sensitivities calibrated by the two-transducer reciprocity method and laser interferometry.

A multivariate model and statistical method for validating tree grade lumber yield equations

Treesearch

Donald W. Seegrist

1975-01-01

Lumber yields within lumber grades can be described by a multivariate linear model. A method for validating lumber yield prediction equations when there are several tree grades is presented. The method is based on multivariate simultaneous test procedures.

Technique for Radiometer and Antenna Array Calibration - TRAAC

NASA Technical Reports Server (NTRS)

Meyer, Paul; Sims, William; Varnavas, Kosta; McCracken, Jeff; Srinivasan, Karthik; Limaye, Ashutosh; Laymon, Charles; Richeson. James

2012-01-01

Highly sensitive receivers are used to detect minute amounts of emitted electromagnetic energy. Calibration of these receivers is vital to the accuracy of the measurements. Traditional calibration techniques depend on calibration reference internal to the receivers as reference for the calibration of the observed electromagnetic energy. Such methods can only calibrate errors in measurement introduced by the receiver only. The disadvantage of these existing methods is that they cannot account for errors introduced by devices, such as antennas, used for capturing electromagnetic radiation. This severely limits the types of antennas that can be used to make measurements with a high degree of accuracy. Complex antenna systems, such as electronically steerable antennas (also known as phased arrays), while offering potentially significant advantages, suffer from a lack of a reliable and accurate calibration technique. The proximity of antenna elements in an array results in interaction between the electromagnetic fields radiated (or received) by the individual elements. This phenomenon is called mutual coupling. The new calibration method uses a known noise source as a calibration load to determine the instantaneous characteristics of the antenna. The noise source is emitted from one element of the antenna array and received by all the other elements due to mutual coupling. This received noise is used as a calibration standard to monitor the stability of the antenna electronics.

A New Calibration Method for Commercial RGB-D Sensors

PubMed Central

Darwish, Walid; Tang, Shenjun; Li, Wenbin; Chen, Wu

2017-01-01

Commercial RGB-D sensors such as Kinect and Structure Sensors have been widely used in the game industry, where geometric fidelity is not of utmost importance. For applications in which high quality 3D is required, i.e., 3D building models of centimeter-level accuracy, accurate and reliable calibrations of these sensors are required. This paper presents a new model for calibrating the depth measurements of RGB-D sensors based on the structured light concept. Additionally, a new automatic method is proposed for the calibration of all RGB-D parameters, including internal calibration parameters for all cameras, the baseline between the infrared and RGB cameras, and the depth error model. When compared with traditional calibration methods, this new model shows a significant improvement in depth precision for both near and far ranges. PMID:28538695

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tuo, Rui; Jeff Wu, C. F.

Calibration parameters in deterministic computer experiments are those attributes that cannot be measured or available in physical experiments. Here, an approach to estimate them by using data from physical experiments and computer simulations. A theoretical framework is given which allows us to study the issues of parameter identifiability and estimation. We define the L 2-consistency for calibration as a justification for calibration methods. It is shown that a simplified version of the original KO method leads to asymptotically L 2-inconsistent calibration. This L 2-inconsistency can be remedied by modifying the original estimation procedure. A novel calibration method, called the Lmore » 2 calibration, is proposed and proven to be L 2-consistent and enjoys optimal convergence rate. Furthermore a numerical example and some mathematical analysis are used to illustrate the source of the L 2-inconsistency problem.« less

The preliminary checkout, evaluation and calibration of a 3-component force measurement system for calibrating propulsion simulators for wind tunnel models

NASA Technical Reports Server (NTRS)

Scott, W. A.

1984-01-01

The propulsion simulator calibration laboratory (PSCL) in which calibrations can be performed to determine the gross thrust and airflow of propulsion simulators installed in wind tunnel models is described. The preliminary checkout, evaluation and calibration of the PSCL's 3 component force measurement system is reported. Methods and equipment were developed for the alignment and calibration of the force measurement system. The initial alignment of the system demonstrated the need for more efficient means of aligning system's components. The use of precision alignment jigs increases both the speed and accuracy with which the system is aligned. The calibration of the force measurement system shows that the methods and equipment for this procedure can be successful.

Hand-eye calibration for rigid laparoscopes using an invariant point.

PubMed

Thompson, Stephen; Stoyanov, Danail; Schneider, Crispin; Gurusamy, Kurinchi; Ourselin, Sébastien; Davidson, Brian; Hawkes, David; Clarkson, Matthew J

2016-06-01

Laparoscopic liver resection has significant advantages over open surgery due to less patient trauma and faster recovery times, yet it can be difficult due to the restricted field of view and lack of haptic feedback. Image guidance provides a potential solution but one current challenge is in accurate "hand-eye" calibration, which determines the position and orientation of the laparoscope camera relative to the tracking markers. In this paper, we propose a simple and clinically feasible calibration method based on a single invariant point. The method requires no additional hardware, can be constructed by theatre staff during surgical setup, requires minimal image processing and can be visualised in real time. Real-time visualisation allows the surgical team to assess the calibration accuracy before use in surgery. In addition, in the laboratory, we have developed a laparoscope with an electromagnetic tracking sensor attached to the camera end and an optical tracking marker attached to the distal end. This enables a comparison of tracking performance. We have evaluated our method in the laboratory and compared it to two widely used methods, "Tsai's method" and "direct" calibration. The new method is of comparable accuracy to existing methods, and we show RMS projected error due to calibration of 1.95 mm for optical tracking and 0.85 mm for EM tracking, versus 4.13 and 1.00 mm respectively, using existing methods. The new method has also been shown to be workable under sterile conditions in the operating room. We have proposed a new method of hand-eye calibration, based on a single invariant point. Initial experience has shown that the method provides visual feedback, satisfactory accuracy and can be performed during surgery. We also show that an EM sensor placed near the camera would provide significantly improved image overlay accuracy.

Innovative self-calibration method for accelerometer scale factor of the missile-borne RINS with fiber optic gyro.

PubMed

Zhang, Qian; Wang, Lei; Liu, Zengjun; Zhang, Yiming

2016-09-19

The calibration of an inertial measurement unit (IMU) is a key technique to improve the preciseness of the inertial navigation system (INS) for missile, especially for the calibration of accelerometer scale factor. Traditional calibration method is generally based on the high accuracy turntable, however, it leads to expensive costs and the calibration results are not suitable to the actual operating environment. In the wake of developments in multi-axis rotational INS (RINS) with optical inertial sensors, self-calibration is utilized as an effective way to calibrate IMU on missile and the calibration results are more accurate in practical application. However, the introduction of multi-axis RINS causes additional calibration errors, including non-orthogonality errors of mechanical processing and non-horizontal errors of operating environment, it means that the multi-axis gimbals could not be regarded as a high accuracy turntable. As for its application on missiles, in this paper, after analyzing the relationship between the calibration error of accelerometer scale factor and non-orthogonality and non-horizontal angles, an innovative calibration procedure using the signals of fiber optic gyro and photoelectric encoder is proposed. The laboratory and vehicle experiment results validate the theory and prove that the proposed method relaxes the orthogonality requirement of rotation axes and eliminates the strict application condition of the system.

Two laboratory methods for the calibration of GPS speed meters

NASA Astrophysics Data System (ADS)

Bai, Yin; Sun, Qiao; Du, Lei; Yu, Mei; Bai, Jie

2015-01-01

The set-ups of two calibration systems are presented to investigate calibration methods of GPS speed meters. The GPS speed meter calibrated is a special type of high accuracy speed meter for vehicles which uses Doppler demodulation of GPS signals to calculate the measured speed of a moving target. Three experiments are performed: including simulated calibration, field-test signal replay calibration, and in-field test comparison with an optical speed meter. The experiments are conducted at specific speeds in the range of 40-180 km h-1 with the same GPS speed meter as the device under calibration. The evaluation of measurement results validates both methods for calibrating GPS speed meters. The relative deviations between the measurement results of the GPS-based high accuracy speed meter and those of the optical speed meter are analyzed, and the equivalent uncertainty of the comparison is evaluated. The comparison results justify the utilization of GPS speed meters as reference equipment if no fewer than seven satellites are available. This study contributes to the widespread use of GPS-based high accuracy speed meters as legal reference equipment in traffic speed metrology.

Data Adjustments for TRACE-P, INTEX-A and INTEX-B

Atmospheric Science Data Center

2013-08-06

... that time, we have done repeated calibrations with two other methods: measuring the production of ozone from oxygen photolysis and the ... this notification.   All of our four calibration methods indicate that the PMT calibration is incorrect, but they differ in the ...

Contributions to the problem of piezoelectric accelerometer calibration. [using lock-in voltmeter

NASA Technical Reports Server (NTRS)

Jakab, I.; Bordas, A.

1974-01-01

After discussing the principal calibration methods for piezoelectric accelerometers, an experimental setup for accelerometer calibration by the reciprocity method is described It is shown how the use of a lock-in voltmeter eliminates errors due to viscous damping and electrical loading.

A novel calibration method for non-orthogonal shaft laser theodolite measurement system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Bin, E-mail: wubin@tju.edu.cn, E-mail: xueting@tju.edu.cn; Yang, Fengting; Ding, Wen

2016-03-15

Non-orthogonal shaft laser theodolite (N-theodolite) is a new kind of large-scale metrological instrument made up by two rotary tables and one collimated laser. There are three axes for an N-theodolite. According to naming conventions in traditional theodolite, rotary axes of two rotary tables are called as horizontal axis and vertical axis, respectively, and the collimated laser beam is named as sight axis. And the difference between N-theodolite and traditional theodolite is obvious, since the former one with no orthogonal and intersecting accuracy requirements. So the calibration method for traditional theodolite is no longer suitable for N-theodolite, while the calibration methodmore » applied currently is really complicated. Thus this paper introduces a novel calibration method for non-orthogonal shaft laser theodolite measurement system to simplify the procedure and to improve the calibration accuracy. A simple two-step process, calibration for intrinsic parameters and for extrinsic parameters, is proposed by the novel method. And experiments have shown its efficiency and accuracy.« less

A new method to calibrate Lagrangian model with ASAR images for oil slick trajectory.

PubMed

Tian, Siyu; Huang, Xiaoxia; Li, Hongga

2017-03-15

Since Lagrangian model coefficients vary with different conditions, it is necessary to calibrate the model to obtain optimal coefficient combination for special oil spill accident. This paper focuses on proposing a new method to calibrate Lagrangian model with time series of Envisat ASAR images. Oil slicks extracted from time series images form a detected trajectory of special oil slick. Lagrangian model is calibrated by minimizing the difference between simulated trajectory and detected trajectory. mean center position distance difference (MCPD) and rotation difference (RD) of Oil slicks' or particles' standard deviational ellipses (SDEs) are calculated as two evaluations. The two parameters are taken to evaluate the performance of Lagrangian transport model with different coefficient combinations. This method is applied to Penglai 19-3 oil spill accident. The simulation result with calibrated model agrees well with related satellite observations. It is suggested the new method is effective to calibrate Lagrangian model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improvement of Accuracy in Environmental Dosimetry by TLD Cards Using Three-dimensional Calibration Method

PubMed Central

HosseiniAliabadi, S. J.; Hosseini Pooya, S. M.; Afarideh, H.; Mianji, F.

2015-01-01

Introduction The angular dependency of response for TLD cards may cause deviation from its true value on the results of environmental dosimetry, since TLDs may be exposed to radiation at different angles of incidence from the surrounding area. Objective A 3D setting of TLD cards has been calibrated isotropically in a standard radiation field to evaluate the improvement of the accuracy of measurement for environmental dosimetry. Method Three personal TLD cards were rectangularly placed in a cylindrical holder, and calibrated using 1D and 3D calibration methods. Then, the dosimeter has been used simultaneously with a reference instrument in a real radiation field measuring the accumulated dose within a time interval. Result The results show that the accuracy of measurement has been improved by 6.5% using 3D calibration factor in comparison with that of normal 1D calibration method. Conclusion This system can be utilized in large scale environmental monitoring with a higher accuracy. PMID:26157729

Calibration of gravitational radiation antenna by dynamic Newton field

NASA Astrophysics Data System (ADS)

Suzuki, T.; Tsubono, K.; Kuroda, K.; Hirakawa, H.

1981-07-01

A method is presented of calibrating antennas for gravitational radiation. The method, which used the dynamic Newton field of a rotating body, is suitable in experiments for frequencies up to several hundred hertz. What is more, the method requires no hardware inside the vacuum chamber of the antenna and is particularly convenient for calibration of low-temperature antenna systems.

Fluorescence of the Flavin group in choline oxidase. Insights and analytical applications for the determination of choline and betaine aldehyde.

PubMed

Ortega, E; de Marcos, S; Sanz-Vicente, I; Ubide, C; Ostra, M; Vidal, M; Galbán, J

2016-01-15

Choline oxidase (ChOx) is a flavoenzyme catalysing the oxidation of choline (Ch) to betaine aldehyde (BA) and glycine betaine (GB). In this paper a fundamental study of the intrinsic fluorescence properties of ChOx due to Flavin Adenine Dinucleotide (FAD) is presented and some analytical applications are studied in detail. Firstly, an unusual alteration in the excitation spectra, in comparison with the absorption spectra, has been observed as a function of the pH. This is ascribed to a change of polarity in the excited state. Secondly, the evolution of the fluorescence spectra during the reaction seems to indicate that the reaction takes place in two consecutive, but partially overlapped, steps and each of them follows a different mechanism. Thirdly, the chemical system can be used to determine the Ch concentration in the range from 5×10(-6)M to 5×10(-5)M (univariate and multivariate calibration) in the presence of BA as interference, and the joint Ch+BA concentration in the range 5×10(-6)-5×10(-4)M (multivariate calibration) with mean errors under 10%; a semiquantitative determination of the BA concentration can be deduced by difference. Finally, Ch has been successfully determined in an infant milk sample. Copyright © 2015 Elsevier B.V. All rights reserved.

Laser-Induced Breakdown Spectroscopy (LIBS) Measurement of Uranium in Molten Salt.

PubMed

Williams, Ammon; Phongikaroon, Supathorn

2018-01-01

In this current study, the molten salt aerosol-laser-induced breakdown spectroscopy (LIBS) system was used to measure the uranium (U) content in a ternary UCl 3 -LiCl-KCl salt to investigate and assess a near real-time analytical approach for material safeguards and accountability. Experiments were conducted using five different U concentrations to determine the analytical figures of merit for the system with respect to U. In the analysis, three U lines were used to develop univariate calibration curves at the 367.01 nm, 385.96 nm, and 387.10 nm lines. The 367.01 nm line had the lowest limit of detection (LOD) of 0.065 wt% U. The 385.96 nm line had the best root mean square error of cross-validation (RMSECV) of 0.20 wt% U. In addition to the univariate calibration approach, a multivariate partial least squares (PLS) model was developed to further analyze the data. Using partial least squares (PLS) modeling, an RMSECV of 0.085 wt% U was determined. The RMSECV from the multivariate approach was significantly better than the univariate case and the PLS model is recommended for future LIBS analysis. Overall, the aerosol-LIBS system performed well in monitoring the U concentration and it is expected that the system could be used to quantitatively determine the U compositions within the normal operational concentrations of U in pyroprocessing molten salts.

Determination of Leaf Water Content by Visible and Near-Infrared Spectrometry and Multivariate Calibration in Miscanthus

DOE PAGES

Jin, Xiaoli; Shi, Chunhai; Yu, Chang Yeon; ...

2017-05-19

Leaf water content is one of the most common physiological parameters limiting efficiency of photosynthesis and biomass productivity in plants including Miscanthus. Therefore, it is of great significance to determine or predict the water content quickly and non-destructively. In this study, we explored the relationship between leaf water content and diffuse reflectance spectra in Miscanthus. Three multivariate calibrations including partial least squares (PLS), least squares support vector machine regression (LSSVR), and radial basis function (RBF) neural network (NN) were developed for the models of leaf water content determination. The non-linear models including RBF_LSSVR and RBF_NN showed higher accuracy than themore » PLS and Lin_LSSVR models. Moreover, 75 sensitive wavelengths were identified to be closely associated with the leaf water content in Miscanthus. The RBF_LSSVR and RBF_NN models for predicting leaf water content, based on 75 characteristic wavelengths, obtained the high determination coefficients of 0.9838 and 0.9899, respectively. The results indicated the non-linear models were more accurate than the linear models using both wavelength intervals. These results demonstrated that visible and near-infrared (VIS/NIR) spectroscopy combined with RBF_LSSVR or RBF_NN is a useful, non-destructive tool for determinations of the leaf water content in Miscanthus, and thus very helpful for development of drought-resistant varieties in Miscanthus.« less

Determination of Leaf Water Content by Visible and Near-Infrared Spectrometry and Multivariate Calibration in Miscanthus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Xiaoli; Shi, Chunhai; Yu, Chang Yeon

Leaf water content is one of the most common physiological parameters limiting efficiency of photosynthesis and biomass productivity in plants including Miscanthus. Therefore, it is of great significance to determine or predict the water content quickly and non-destructively. In this study, we explored the relationship between leaf water content and diffuse reflectance spectra in Miscanthus. Three multivariate calibrations including partial least squares (PLS), least squares support vector machine regression (LSSVR), and radial basis function (RBF) neural network (NN) were developed for the models of leaf water content determination. The non-linear models including RBF_LSSVR and RBF_NN showed higher accuracy than themore » PLS and Lin_LSSVR models. Moreover, 75 sensitive wavelengths were identified to be closely associated with the leaf water content in Miscanthus. The RBF_LSSVR and RBF_NN models for predicting leaf water content, based on 75 characteristic wavelengths, obtained the high determination coefficients of 0.9838 and 0.9899, respectively. The results indicated the non-linear models were more accurate than the linear models using both wavelength intervals. These results demonstrated that visible and near-infrared (VIS/NIR) spectroscopy combined with RBF_LSSVR or RBF_NN is a useful, non-destructive tool for determinations of the leaf water content in Miscanthus, and thus very helpful for development of drought-resistant varieties in Miscanthus.« less

Reflectance calibration of focal plane array hyperspectral imaging system for agricultural and food safety applications

NASA Astrophysics Data System (ADS)

Lawrence, Kurt C.; Park, Bosoon; Windham, William R.; Mao, Chengye; Poole, Gavin H.

2003-03-01

A method to calibrate a pushbroom hyperspectral imaging system for "near-field" applications in agricultural and food safety has been demonstrated. The method consists of a modified geometric control point correction applied to a focal plane array to remove smile and keystone distortion from the system. Once a FPA correction was applied, single wavelength and distance calibrations were used to describe all points on the FPA. Finally, a percent reflectance calibration, applied on a pixel-by-pixel basis, was used for accurate measurements for the hyperspectral imaging system. The method was demonstrated with a stationary prism-grating-prism, pushbroom hyperspectral imaging system. For the system described, wavelength and distance calibrations were used to reduce the wavelength errors to <0.5 nm and distance errors to <0.01mm (across the entrance slit width). The pixel-by-pixel percent reflectance calibration, which was performed at all wavelengths with dark current and 99% reflectance calibration-panel measurements, was verified with measurements on a certified gradient Spectralon panel with values ranging from about 14% reflectance to 99% reflectance with errors generally less than 5% at the mid-wavelength measurements. Results from the calibration method, indicate the hyperspectral imaging system has a usable range between 420 nm and 840 nm. Outside this range, errors increase significantly.

Wind Tunnel Force Balance Calibration Study - Interim Results

NASA Technical Reports Server (NTRS)

Rhew, Ray D.

2012-01-01

Wind tunnel force balance calibration is preformed utilizing a variety of different methods and does not have a direct traceable standard such as standards used for most calibration practices (weights, and voltmeters). These different calibration methods and practices include, but are not limited to, the loading schedule, the load application hardware, manual and automatic systems, re-leveling and non-re-leveling. A study of the balance calibration techniques used by NASA was undertaken to develop metrics for reviewing and comparing results using sample calibrations. The study also includes balances of different designs, single and multi-piece. The calibration systems include, the manual, and the automatic that are provided by NASA and its vendors. The results to date will be presented along with the techniques for comparing the results. In addition, future planned calibrations and investigations based on the results will be provided.

Comparison of spectral radiance responsivity calibration techniques used for backscatter ultraviolet satellite instruments

NASA Astrophysics Data System (ADS)

Kowalewski, M. G.; Janz, S. J.

2015-02-01

Methods of absolute radiometric calibration of backscatter ultraviolet (BUV) satellite instruments are compared as part of an effort to minimize pre-launch calibration uncertainties. An internally illuminated integrating sphere source has been used for the Shuttle Solar BUV, Total Ozone Mapping Spectrometer, Ozone Mapping Instrument, and Global Ozone Monitoring Experiment 2 using standardized procedures traceable to national standards. These sphere-based spectral responsivities agree to within the derived combined standard uncertainty of 1.87% relative to calibrations performed using an external diffuser illuminated by standard irradiance sources, the customary spectral radiance responsivity calibration method for BUV instruments. The combined standard uncertainty for these calibration techniques as implemented at the NASA Goddard Space Flight Center’s Radiometric Calibration and Development Laboratory is shown to less than 2% at 250 nm when using a single traceable calibration standard.

Management of groundwater in-situ bioremediation system using reactive transport modelling under parametric uncertainty: field scale application

NASA Astrophysics Data System (ADS)

Verardo, E.; Atteia, O.; Rouvreau, L.

2015-12-01

In-situ bioremediation is a commonly used remediation technology to clean up the subsurface of petroleum-contaminated sites. Forecasting remedial performance (in terms of flux and mass reduction) is a challenge due to uncertainties associated with source properties and the uncertainties associated with contribution and efficiency of concentration reducing mechanisms. In this study, predictive uncertainty analysis of bio-remediation system efficiency is carried out with the null-space Monte Carlo (NSMC) method which combines the calibration solution-space parameters with the ensemble of null-space parameters, creating sets of calibration-constrained parameters for input to follow-on remedial efficiency. The first step in the NSMC methodology for uncertainty analysis is model calibration. The model calibration was conducted by matching simulated BTEX concentration to a total of 48 observations from historical data before implementation of treatment. Two different bio-remediation designs were then implemented in the calibrated model. The first consists in pumping/injection wells and the second in permeable barrier coupled with infiltration across slotted piping. The NSMC method was used to calculate 1000 calibration-constrained parameter sets for the two different models. Several variants of the method were implemented to investigate their effect on the efficiency of the NSMC method. The first variant implementation of the NSMC is based on a single calibrated model. In the second variant, models were calibrated from different initial parameter sets. NSMC calibration-constrained parameter sets were sampled from these different calibrated models. We demonstrate that in context of nonlinear model, second variant avoids to underestimate parameter uncertainty which may lead to a poor quantification of predictive uncertainty. Application of the proposed approach to manage bioremediation of groundwater in a real site shows that it is effective to provide support in management of the in-situ bioremediation systems. Moreover, this study demonstrates that the NSMC method provides a computationally efficient and practical methodology of utilizing model predictive uncertainty methods in environmental management.

Innovative methodology for intercomparison of radionuclide calibrators using short half-life in situ prepared radioactive sources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oliveira, P. A.; Santos, J. A. M., E-mail: joao.santos@ipoporto.min-saude.pt; Serviço de Física Médica do Instituto Português de Oncologia do Porto Francisco Gentil, EPE, Porto

2014-07-15

Purpose: An original radionuclide calibrator method for activity determination is presented. The method could be used for intercomparison surveys for short half-life radioactive sources used in Nuclear Medicine, such as{sup 99m}Tc or most positron emission tomography radiopharmaceuticals. Methods: By evaluation of the resulting net optical density (netOD) using a standardized scanning method of irradiated Gafchromic XRQA2 film, a comparison of the netOD measurement with a previously determined calibration curve can be made and the difference between the tested radionuclide calibrator and a radionuclide calibrator used as reference device can be calculated. To estimate the total expected measurement uncertainties, a carefulmore » analysis of the methodology, for the case of{sup 99m}Tc, was performed: reproducibility determination, scanning conditions, and possible fadeout effects. Since every factor of the activity measurement procedure can influence the final result, the method also evaluates correct syringe positioning inside the radionuclide calibrator. Results: As an alternative to using a calibrated source sent to the surveyed site, which requires a relatively long half-life of the nuclide, or sending a portable calibrated radionuclide calibrator, the proposed method uses a source preparedin situ. An indirect activity determination is achieved by the irradiation of a radiochromic film using {sup 99m}Tc under strictly controlled conditions, and cumulated activity calculation from the initial activity and total irradiation time. The irradiated Gafchromic film and the irradiator, without the source, can then be sent to a National Metrology Institute for evaluation of the results. Conclusions: The methodology described in this paper showed to have a good potential for accurate (3%) radionuclide calibrators intercomparison studies for{sup 99m}Tc between Nuclear Medicine centers without source transfer and can easily be adapted to other short half-life radionuclides.« less

Molecular Imaging of Kerogen and Minerals in Shale Rocks across Micro- and Nano- Scales

NASA Astrophysics Data System (ADS)

Hao, Z.; Bechtel, H.; Sannibale, F.; Kneafsey, T. J.; Gilbert, B.; Nico, P. S.

2016-12-01

Fourier transform infrared (FTIR) spectroscopy is a reliable and non-destructive quantitative method to evaluate mineralogy and kerogen content / maturity of shale rocks, although it is traditionally difficult to assess the organic and mineralogical heterogeneity at micrometer and nanometer scales due to the diffraction limit of the infrared light. However, it is truly at these scales that the kerogen and mineral content and their formation in share rocks determines the quality of shale gas reserve, the gas flow mechanisms and the gas production. Therefore, it's necessary to develop new approaches which can image across both micro- and nano- scales. In this presentation, we will describe two new molecular imaging approaches to obtain kerogen and mineral information in shale rocks at the unprecedented high spatial resolution, and a cross-scale quantitative multivariate analysis method to provide rapid geochemical characterization of large size samples. The two imaging approaches are enhanced at nearfield respectively by a Ge-hemisphere (GE) and by a metallic scanning probe (SINS). The GE method is a modified microscopic attenuated total reflectance (ATR) method which rapidly captures a chemical image of the shale rock surface at 1 to 5 micrometer resolution with a large field of view of 600 X 600 micrometer, while the SINS probes the surface at 20 nm resolution which provides a chemically "deconvoluted" map at the nano-pore level. The detailed geochemical distribution at nanoscale is then used to build a machine learning model to generate self-calibrated chemical distribution map at micrometer scale with the input of the GE images. A number of geochemical contents across these two important scales are observed and analyzed, including the minerals (oxides, carbonates, sulphides), the organics (carbohydrates, aromatics), and the absorbed gases. These approaches are self-calibrated, optics friendly and non-destructive, so they hold the potential to monitor shale gas flow at real time inside the micro- or nano- pore network, which is of great interest for optimizing the shale gas extraction.

Calibration of multivariate scatter plots for exploratory analysis of relations within and between sets of variables in genomic research.

PubMed

Graffelman, Jan; van Eeuwijk, Fred

2005-12-01

The scatter plot is a well known and easily applicable graphical tool to explore relationships between two quantitative variables. For the exploration of relations between multiple variables, generalisations of the scatter plot are useful. We present an overview of multivariate scatter plots focussing on the following situations. Firstly, we look at a scatter plot for portraying relations between quantitative variables within one data matrix. Secondly, we discuss a similar plot for the case of qualitative variables. Thirdly, we describe scatter plots for the relationships between two sets of variables where we focus on correlations. Finally, we treat plots of the relationships between multiple response and predictor variables, focussing on the matrix of regression coefficients. We will present both known and new results, where an important original contribution concerns a procedure for the inclusion of scales for the variables in multivariate scatter plots. We provide software for drawing such scales. We illustrate the construction and interpretation of the plots by means of examples on data collected in a genomic research program on taste in tomato.

Calibration method for spectroscopic systems

DOEpatents

Sandison, David R.

1998-01-01

Calibration spots of optically-characterized material placed in the field of view of a spectroscopic system allow calibration of the spectroscopic system. Response from the calibration spots is measured and used to calibrate for varying spectroscopic system operating parameters. The accurate calibration achieved allows quantitative spectroscopic analysis of responses taken at different times, different excitation conditions, and of different targets.

Calibration method for spectroscopic systems

DOEpatents

Sandison, D.R.

1998-11-17

Calibration spots of optically-characterized material placed in the field of view of a spectroscopic system allow calibration of the spectroscopic system. Response from the calibration spots is measured and used to calibrate for varying spectroscopic system operating parameters. The accurate calibration achieved allows quantitative spectroscopic analysis of responses taken at different times, different excitation conditions, and of different targets. 3 figs.

Bayesian Treed Calibration: An Application to Carbon Capture With AX Sorbent

DOE Office of Scientific and Technical Information (OSTI.GOV)

Konomi, Bledar A.; Karagiannis, Georgios; Lai, Kevin

2017-01-02

In cases where field or experimental measurements are not available, computer models can model real physical or engineering systems to reproduce their outcomes. They are usually calibrated in light of experimental data to create a better representation of the real system. Statistical methods, based on Gaussian processes, for calibration and prediction have been especially important when the computer models are expensive and experimental data limited. In this paper, we develop the Bayesian treed calibration (BTC) as an extension of standard Gaussian process calibration methods to deal with non-stationarity computer models and/or their discrepancy from the field (or experimental) data. Ourmore » proposed method partitions both the calibration and observable input space, based on a binary tree partitioning, into sub-regions where existing model calibration methods can be applied to connect a computer model with the real system. The estimation of the parameters in the proposed model is carried out using Markov chain Monte Carlo (MCMC) computational techniques. Different strategies have been applied to improve mixing. We illustrate our method in two artificial examples and a real application that concerns the capture of carbon dioxide with AX amine based sorbents. The source code and the examples analyzed in this paper are available as part of the supplementary materials.« less

In-Situ Transfer Standard and Coincident-View Intercomparisons for Sensor Cross-Calibration

NASA Technical Reports Server (NTRS)

Thome, Kurt; McCorkel, Joel; Czapla-Myers, Jeff

2013-01-01

There exist numerous methods for accomplishing on-orbit calibration. Methods include the reflectance-based approach relying on measurements of surface and atmospheric properties at the time of a sensor overpass as well as invariant scene approaches relying on knowledge of the temporal characteristics of the site. The current work examines typical cross-calibration methods and discusses the expected uncertainties of the methods. Data from the Advanced Land Imager (ALI), Advanced Spaceborne Thermal Emission and Reflection and Radiometer (ASTER), Enhanced Thematic Mapper Plus (ETM+), Moderate Resolution Imaging Spectroradiometer (MODIS), and Thematic Mapper (TM) are used to demonstrate the limits of relative sensor-to-sensor calibration as applied to current sensors while Landsat-5 TM and Landsat-7 ETM+ are used to evaluate the limits of in situ site characterizations for SI-traceable cross calibration. The current work examines the difficulties in trending of results from cross-calibration approaches taking into account sampling issues, site-to-site variability, and accuracy of the method. Special attention is given to the differences caused in the cross-comparison of sensors in radiance space as opposed to reflectance space. The results show that cross calibrations with absolute uncertainties lesser than 1.5 percent (1 sigma) are currently achievable even for sensors without coincident views.

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

A GPS-Based Pitot-Static Calibration Method Using Global Output-Error Optimization

NASA Technical Reports Server (NTRS)

Foster, John V.; Cunningham, Kevin

2010-01-01

Pressure-based airspeed and altitude measurements for aircraft typically require calibration of the installed system to account for pressure sensing errors such as those due to local flow field effects. In some cases, calibration is used to meet requirements such as those specified in Federal Aviation Regulation Part 25. Several methods are used for in-flight pitot-static calibration including tower fly-by, pacer aircraft, and trailing cone methods. In the 1990 s, the introduction of satellite-based positioning systems to the civilian market enabled new inflight calibration methods based on accurate ground speed measurements provided by Global Positioning Systems (GPS). Use of GPS for airspeed calibration has many advantages such as accuracy, ease of portability (e.g. hand-held) and the flexibility of operating in airspace without the limitations of test range boundaries or ground telemetry support. The current research was motivated by the need for a rapid and statistically accurate method for in-flight calibration of pitot-static systems for remotely piloted, dynamically-scaled research aircraft. Current calibration methods were deemed not practical for this application because of confined test range size and limited flight time available for each sortie. A method was developed that uses high data rate measurements of static and total pressure, and GPSbased ground speed measurements to compute the pressure errors over a range of airspeed. The novel application of this approach is the use of system identification methods that rapidly compute optimal pressure error models with defined confidence intervals in nearreal time. This method has been demonstrated in flight tests and has shown 2- bounds of approximately 0.2 kts with an order of magnitude reduction in test time over other methods. As part of this experiment, a unique database of wind measurements was acquired concurrently with the flight experiments, for the purpose of experimental validation of the optimization method. This paper describes the GPS-based pitot-static calibration method developed for the AirSTAR research test-bed operated as part of the Integrated Resilient Aircraft Controls (IRAC) project in the NASA Aviation Safety Program (AvSP). A description of the method will be provided and results from recent flight tests will be shown to illustrate the performance and advantages of this approach. Discussion of maneuver requirements and data reduction will be included as well as potential applications.

Calibrating the orientation between a microlens array and a sensor based on projective geometry

NASA Astrophysics Data System (ADS)

Su, Lijuan; Yan, Qiangqiang; Cao, Jun; Yuan, Yan

2016-07-01

We demonstrate a method for calibrating a microlens array (MLA) with a sensor component by building a plenoptic camera with a conventional prime lens. This calibration method includes a geometric model, a setup to adjust the distance (L) between the prime lens and the MLA, a calibration procedure for determining the subimage centers, and an optimization algorithm. The geometric model introduces nine unknown parameters regarding the centers of the microlenses and their images, whereas the distance adjustment setup provides an initial guess for the distance L. The simulation results verify the effectiveness and accuracy of the proposed method. The experimental results demonstrate the calibration process can be performed with a commercial prime lens and the proposed method can be used to quantitatively evaluate whether a MLA and a sensor is assembled properly for plenoptic systems.

Wavelength selection-based nonlinear calibration for transcutaneous blood glucose sensing using Raman spectroscopy

PubMed Central

Dingari, Narahara Chari; Barman, Ishan; Kang, Jeon Woong; Kong, Chae-Ryon; Dasari, Ramachandra R.; Feld, Michael S.

2011-01-01

While Raman spectroscopy provides a powerful tool for noninvasive and real time diagnostics of biological samples, its translation to the clinical setting has been impeded by the lack of robustness of spectroscopic calibration models and the size and cumbersome nature of conventional laboratory Raman systems. Linear multivariate calibration models employing full spectrum analysis are often misled by spurious correlations, such as system drift and covariations among constituents. In addition, such calibration schemes are prone to overfitting, especially in the presence of external interferences that may create nonlinearities in the spectra-concentration relationship. To address both of these issues we incorporate residue error plot-based wavelength selection and nonlinear support vector regression (SVR). Wavelength selection is used to eliminate uninformative regions of the spectrum, while SVR is used to model the curved effects such as those created by tissue turbidity and temperature fluctuations. Using glucose detection in tissue phantoms as a representative example, we show that even a substantial reduction in the number of wavelengths analyzed using SVR lead to calibration models of equivalent prediction accuracy as linear full spectrum analysis. Further, with clinical datasets obtained from human subject studies, we also demonstrate the prospective applicability of the selected wavelength subsets without sacrificing prediction accuracy, which has extensive implications for calibration maintenance and transfer. Additionally, such wavelength selection could substantially reduce the collection time of serial Raman acquisition systems. Given the reduced footprint of serial Raman systems in relation to conventional dispersive Raman spectrometers, we anticipate that the incorporation of wavelength selection in such hardware designs will enhance the possibility of miniaturized clinical systems for disease diagnosis in the near future. PMID:21895336

Photometric calibration of the COMBO-17 survey with the Softassign Procrustes Matching method

NASA Astrophysics Data System (ADS)

Sheikhbahaee, Z.; Nakajima, R.; Erben, T.; Schneider, P.; Hildebrandt, H.; Becker, A. C.

2017-11-01

Accurate photometric calibration of optical data is crucial for photometric redshift estimation. We present the Softassign Procrustes Matching (SPM) method to improve the colour calibration upon the commonly used Stellar Locus Regression (SLR) method for the COMBO-17 survey. Our colour calibration approach can be categorised as a point-set matching method, which is frequently used in medical imaging and pattern recognition. We attain a photometric redshift precision Δz/(1 + zs) of better than 2 per cent. Our method is based on aligning the stellar locus of the uncalibrated stars to that of a spectroscopic sample of the Sloan Digital Sky Survey standard stars. We achieve our goal by finding a correspondence matrix between the two point-sets and applying the matrix to estimate the appropriate translations in multidimensional colour space. The SPM method is able to find the translation between two point-sets, despite the existence of noise and incompleteness of the common structures in the sets, as long as there is a distinct structure in at least one of the colour-colour pairs. We demonstrate the precision of our colour calibration method with a mock catalogue. The SPM colour calibration code is publicly available at https://neuronphysics@bitbucket.org/neuronphysics/spm.git.

Hair sterol signatures coupled to multivariate data analysis reveal an increased 7β-hydroxycholesterol production in cognitive impairment.

PubMed

Son, Hyun-Hwa; Lee, Do-Yup; Seo, Hong Seog; Jeong, Jihyeon; Moon, Ju-Yeon; Lee, Jung-Eun; Chung, Bong Chul; Kim, Eosu; Choi, Man Ho

2016-01-01

Altered cholesterol metabolism could be associated with cognitive impairment. The quantitative profiling of 19 hair sterols was developed using gas chromatography-mass spectrometry coupled to multivariate data analysis. The limit of quantification of all sterols ranged from 5 to 20 ng/g, while the calibration linearity was higher than 0.98. The precision (% CV) and accuracy (% bias) ranged from 3.2% to 9.8% and from 83.2% to 119.4%, respectively. Among the sterols examined, 8 were quantitatively detected from two strands of 3-cm-long scalp hair samples of female participants, including mild cognitive impairment (MCI, n=15), Alzheimer's disease (AD, n=31), and healthy controls (HC, n=36). The cognitive impairment (MCI or AD) was correlated with a higher metabolic rate than that of HCs based on 7β-hydroxycholesterol (P<0.005). Significant negative correlations (r=-0.822) were detected between Mini-Mental State Examination (MMSE) scores and hair sample metabolic ratios of 7β-hydroxycholesterol to cholesterol, which is an accepted, sensitive, and specific tool for discriminating HCs from individuals with MCI or AD. In conclusion, improved diagnostic values can be obtained using hair sterol signatures coupled with MMSE scores. This method may prove useful for predictive diagnosis in population screening of cognitive impairment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Clinical validation of robot simulation of toothbrushing - comparative plaque removal efficacy

PubMed Central

2014-01-01

Background Clinical validation of laboratory toothbrushing tests has important advantages. It was, therefore, the aim to demonstrate correlation of tooth cleaning efficiency of a new robot brushing simulation technique with clinical plaque removal. Methods Clinical programme: 27 subjects received dental cleaning prior to 3-day-plaque-regrowth-interval. Plaque was stained, photographically documented and scored using planimetrical index. Subjects brushed teeth 33–47 with three techniques (horizontal, rotating, vertical), each for 20s buccally and for 20s orally in 3 consecutive intervals. The force was calibrated, the brushing technique was video supported. Two different brushes were randomly assigned to the subject. Robot programme: Clinical brushing programmes were transfered to a 6-axis-robot. Artificial teeth 33–47 were covered with plaque-simulating substrate. All brushing techniques were repeated 7 times, results were scored according to clinical planimetry. All data underwent statistical analysis by t-test, U-test and multivariate analysis. Results The individual clinical cleaning patterns are well reproduced by the robot programmes. Differences in plaque removal are statistically significant for the two brushes, reproduced in clinical and robot data. Multivariate analysis confirms the higher cleaning efficiency for anterior teeth and for the buccal sites. Conclusions The robot tooth brushing simulation programme showed good correlation with clinically standardized tooth brushing. This new robot brushing simulation programme can be used for rapid, reproducible laboratory testing of tooth cleaning. PMID:24996973

A formulation of tissue- and water-equivalent materials using the stoichiometric analysis method for CT-number calibration in radiotherapy treatment planning.

PubMed

Yohannes, Indra; Kolditz, Daniel; Langner, Oliver; Kalender, Willi A

2012-03-07

Tissue- and water-equivalent materials (TEMs) are widely used in quality assurance and calibration procedures, both in radiodiagnostics and radiotherapy. In radiotherapy, particularly, the TEMs are often used for computed tomography (CT) number calibration in treatment planning systems. However, currently available TEMs may not be very accurate in the determination of the calibration curves due to their limitation in mimicking radiation characteristics of the corresponding real tissues in both low- and high-energy ranges. Therefore, we are proposing a new formulation of TEMs using a stoichiometric analysis method to obtain TEMs for the calibration purposes. We combined the stoichiometric calibration and the basic data method to compose base materials to develop TEMs matching standard real tissues from ICRU Report 44 and 46. First, the CT numbers of six materials with known elemental compositions were measured to get constants for the stoichiometric calibration. The results of the stoichiometric calibration were used together with the basic data method to formulate new TEMs. These new TEMs were scanned to validate their CT numbers. The electron density and the stopping power calibration curves were also generated. The absolute differences of the measured CT numbers of the new TEMs were less than 4 HU for the soft tissues and less than 22 HU for the bone compared to the ICRU real tissues. Furthermore, the calculated relative electron density and electron and proton stopping powers of the new TEMs differed by less than 2% from the corresponding ICRU real tissues. The new TEMs which were formulated using the proposed technique increase the simplicity of the calibration process and preserve the accuracy of the stoichiometric calibration simultaneously.

Integrated calibration sphere and calibration step fixture for improved coordinate measurement machine calibration

DOEpatents

Clifford, Harry J [Los Alamos, NM

2011-03-22

A method and apparatus for mounting a calibration sphere to a calibration fixture for Coordinate Measurement Machine (CMM) calibration and qualification is described, decreasing the time required for such qualification, thus allowing the CMM to be used more productively. A number of embodiments are disclosed that allow for new and retrofit manufacture to perform as integrated calibration sphere and calibration fixture devices. This invention renders unnecessary the removal of a calibration sphere prior to CMM measurement of calibration features on calibration fixtures, thereby greatly reducing the time spent qualifying a CMM.