Onno De Noord

Onno De Noord
Consultant

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61
Publications
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3,403
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Publications

Publications (61)
Data
Extended version of Table 1: overview of the paintings from which green and blue samples were taken and their compostions
Conference Paper
Full-text available
Jan Steen, a prolific Dutch 17th-century artist, has been the focus of a research project at the Mauritshuis since 2012. The aim of the research project is to shed light on the chronology of his works based on the materials he used. Samples of green and blue areas on 37 paintings were analysed using optical microscopy, SEM–EDX and synchrotron μ-XRD...
Article
The possibility of addressing the problem of process troubleshooting and understanding by modelling common and distinctive sources of variation (factors or components) underlying two sets of measurements was explored in a real‐world industrial case study. The used strategy includes a novel approach to systematically detect the number of common and...
Article
Full-text available
In-depth technical and art historical research into Jan Steen’s (ca. 1626–1679) oeuvre has been a focus at the Mauritshuis since 2012, as part of the Partners in Science collaboration with Shell. The aim of this project is to shed light on the chronology of Steen’s oeuvre based on the materials he used, since only 10% of his circa 450 works are dat...
Article
Selecting the correct number of factors in principal component analysis (PCA) is a critical step to achieve a reasonable data modelling, where the optimal strategy strictly depends on the objective PCA is applied for. In the last decades, much work has been devoted to methods like Kaiser's eigenvalue greater than 1 rule, Velicer's minimum average p...
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In the paradigm of virtual high throughput screening for materials, we have developed a semi-automated workflow or ‘recipe’ that can help a material scientist to start from a raw dataset of materials with their properties and descriptors, build predictive models, and draw insights into the governing mechanism. We demonstrate our recipe, which emplo...
Article
Full-text available
Calibration transfer between near-infrared (NIR) spectrometers is a subtle issue in chemometrics and process industry. In fact, as even very similar instruments may generate strongly different spectral responses, regression models developed on a first NIR system can rarely be used with spectra collected by a second apparatus. In this work, two nove...
Article
Three‐level versions of Multilevel Simultaneous Component Analysis (MLSCA) and Multilevel Partial Least Squares (MLPLS) were developed, which are capable of separating between‐plant, between‐run and within‐run process variation, and modeling these three levels in a multivariate way. In comparison to the two‐level versions they allow to discriminate...
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This article explores the potential of kernel-based techniques for discriminating on-specification and off-specification batch runs, combining kernel-partial least squares discriminant analysis and three common approaches to analyze batch data by means of bilinear models: landmark features extraction, batchwise unfolding, and variablewise unfolding...
Article
Batch synchronization has been widely misunderstood as being only needed when variable trajectories have uneven length. Batch data are actually considered not synchronized when the key process events do not occur at the same point of process evolution, irrespective of whether the batch duration is the same for all batches or not. Additionally, a si...
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There is a widespread assumption that batch synchronization is only required if the batch trajectories have different duration. This paper is devoted to demonstrate that synchronization is a critical and necessary preliminary step to bilinear batch process modeling, no matter whether batch trajectories have equal length or not. Another practical as...
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Batch process data contain between‐run and within‐run sources of variation, which complicates data analysis and process monitoring. Multilevel methods, such as multilevel simultaneous component analysis, greatly enhance the interpretation of large sets of batch process data by separating the between‐run and within‐run variation. Using a multilevel...
Article
Comprehensive two-dimensional gas chromatography (GCxGC) has proven to be an extremely powerful separation technique for the analysis of complex volatile mixtures. This separation power can be used to discriminate between highly similar samples. In this article we will describe the use of GCxGC for the discrimination of crude oils from different re...
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Principal component analysis (PCA) and partial least squares (PLS) are well-established techniques for analyzing multivariate process data. However, chemical processes often vary at different levels, due to, for instance, catalyst deactivation or fouling. In such cases, data from a time period that comprises multiple catalyst or fouling runs contai...
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The predictive ability of a PCR bilinear regression model is highly dependent on the number of latent variables selected. A non-optimal complexity is likely to result in a model yielding unsatisfactory predictions, due to a high bias or high variance of the coefficients of regression. The popular cross-validation methods such as leave-one-out cross...
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Multivariate regression models are valid only for prediction of samples that are within the range of calibration data. Prediction of dependent variables for samples carrying new sources of variance requires updating of the model. A simple and convenient way to extend the model is to re-calibrate it using new incoming samples. However, it may be dif...
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This work is part of a more general research aiming at comparing the performance of multivariate calibration methods. In the first and second parts of the study, the performances of multivariate calibration methods were compared in situations of interpolation and extrapolation, respectively. This third part of the study deals with robustness of cal...
Article
To increase the power and the robustness of spectroscopic process analyzers, methods are needed that suppress the spectral variation that is not related to the property of interest in the process stream. An approach for the selection of a suitable method is presented. The approach uses the net analyte signal (NAS) to analyze the situation and to se...
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The Delaunay triangulation (DT) method is proposed as a new local multivariate calibration method. DT was developed within computational geometry, and it is shown that it has potential for applications in analytical chemistry, such as multivariate calibration. The study compares the performance of the DT method with the global methods principal com...
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If a prediction sample is different from the calibration samples, it can be considered as an outlier in prediction. In this work, two techniques, the use of the uncertainty estimation and convex hull method are studied to detect such prediction outliers. Classical techniques (Mahalanobis distance and X-residuals), potential functions and robust tec...
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The present study compares the performance of different multivariate calibration techniques when new samples to be predicted can fall outside the calibration domain. Results of the calibration methods are investigated for extrapolation of different types and various levels. The calibration methods are applied to five near-IR data sets including dif...
Article
When in-line or on-line spectroscopy is performed on a process, different types of variations are present in the measured spectrum. The variation due to the chemistry of the process is the wanted variation, which should be used for monitoring the process. Also unwanted variation is present in the measured spectrum. One example is variation due to c...
Article
The effects of a Direct Orthogonalization before applying PCR and PLS are studied for several data sets. In all cases the number of PLS factors needed to obtain the optimal model decreases but the number of PLS and DO factors together is the same as when PLS alone is used. However, the quality of the calibration model (measured as RMSECV) is usuall...
Article
The influence of external physical variation such as temperature fluctuations on near-infrared (NIR) spectra and their effect on the predictive power of calibration models such as PLS have been studied. Different methods to correct for the temperature effect by explicitly including the temperature in a calibration model have been tested. The result...
Article
In process analytical applications it is not always possible to keep the measurement conditions constant. However, fluctuations in external variables such as temperature can have a strong influence on measurement results. For example, nonlinear temperature effects on near-infrared (NIR) spectra may lead to a strongly biased prediction result from m...
Article
When spectral variation caused by factors different from the parameter to be predicted (e.g. external variations in temperature) is present in calibration data, a common approach is to include this variation in the calibration model. For this purpose, the calibration sample spectra measured under standard conditions and the spectra of a smaller set...
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Abstract The present study compares the performance of different multivariate calibration techniques applied to four near-infrared data sets when test samples are well within the calibration domain. Three types of problems are discussed: the nonlinear calibration, the calibration using heterogeneous data sets, and the calibration in the presence o...
Article
Full-text available
Proper operation of a molecular sieve process for the separation of iso- and cyclo-alkanes from normal alkanes requires the fast online detection of normal alkanes breaking through the column. The feasibility of using near-infrared (NIR) spectroscopy for this application was investigated. Alkane mixtures were prepared according to an experim ental...
Article
Full-text available
The tutorial explains how to develop a calibration model for spectroscopic data analysis by Principal Component Regression (PCR), PCR basically consists of Principal Component Analysis (PCA) followed by a Multiple Linear Regression (MLR) step. Different diagnostics must however be implemented to detect outliers, clustering tendency or nonlinearitie...
Article
After a multivariate calibration model is built and validated, it is ready to be used for the prediction of the characteristic to be determined in the new samples. Before prediction, one should make sure that the new samples are similar to the calibration samples. If not, such samples are called prediction outliers, which can be of two types, namel...
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The present study categorises and compares several graphical and numerical methods to detect the presence of nonlinearity in multivariate calibration. The focus is on (quadratic) nonlinearity in the relationship between the property of interest (e.g. concentration) and the set of instrumental (e.g. absorbance) measurements. The explored techniques...
Article
A rapid assessment of product quality can often be made using a combination of near-infrared spectroscopy (NIR) and multivariate calibration. The robustness of such a method is determined by the sensitivity of the multivariate calibration model to variations in the spectral data. An approach is described that uses a combination of experimental desi...
Article
An approach for extracting the relevant features for multivariate calibration of the hydroxyl number in a polyol from a near-infrared (NIR) spectroscopic data set by using the Fourier transform, is presented. It is carried out in the frequency domain starting from the first 50 power-spectra (PS) coefficients as the input to a genetic algorithm (GA)...
Article
An approach aiming at extracting the relevant component for multivariate calibration is introduced, and its performance is compared with the "uninformative variable elimination" approach and with the standard PLS method for the modeling of near-infrared data. The extraction of the relevant component is carried out in the wavelet domain. The PLS res...
Article
The importance of the validation step in multiple linear regression of near-infrared spectroscopic data, after selection of wavelengths by a genetic algorithm, is investigated with the use of random variables. It is shown that in spite of a careful validation procedure, the GA can still select irrelevant variables. The effect is greatly reduced by...
Article
A new method for the elimination of uninformative variables in multivariate data sets is proposed. To achieve this, artificial (noise) variables are added and a closed form of the PLS or PCR model is obtained for the data set containing the experimental and the artificial variables. The experimental variables that do not have more importance than t...
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Methods for the detection of outliers and clusters in data sets for multivariate calibration are discussed in this study. Replicate as well as sample outliers have been investigated. The Cochran test applied to the sum of absorbances is shown to identify outlying replicates. Sample outliers were detected on latent variables (PCs) or by using Rao's...
Article
A comparison of multiple linear regression (MLR) with partial least-squares (PLS) regression is presented, for the multivariate modeling of hydroxyl number in a certain polymer of a heterogeneous near-IR spectroscopic data set. The MLR model was performed by selecting the variables with a genetic algorithm. A good model could be obtained with both...
Article
Multivariate calibration models are usually based on data from a large number of training set samples which have been collected over a long period of time. These models are meant to be used for an extended period. There are, however, a number of situations in which a multivariate calibration model may become invalid, for instance when the instrumen...
Article
Multivariate techniques such as partial least squares and principal component regression have a high modelling power, but the model complexity increases rapidly upon inclusion of non-relevant sources of variance and non-linearities. Proper data preprocessing can eliminate these effects beforehand, which results in more parsimonious models. In terms...
Article
The quality of bioanalytical methods is often determined by the quality of sample preparation. Using a robot for sample treatment may give better results than manual sample preparation, since the robot lacks human behaviour and incidental errors that are part of it. The use of a laboratory robot has the additional advantage of giving each sample th...
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1. The influence of alpha-interferon (Roferon-A) on the pharmacokinetics and metabolism of theophylline was studied in healthy adults. Roferon-A was administered as an intra-muscular injection (3 x 10(6) iu) once-a-day over 3 days. One week prior to and immediately after this course a single 20 min aminophylline infusion (4 mg kg-1) was given. 2. B...
Article
1. The pharmacokinetic interaction of terbutaline and theophylline and chronopharmacokinetics of both drugs were studied in a three-way crossover study with repeated administration of terbutaline (Bricanyl Depot) 7.5 mg twice daily, theophylline (Theo-Dur) 300 mg twice daily alone or the combination of both for 7 days to 12 healthy volunteers (six...
Article
In a multiple dose cross-over experiment in 18 healthy male volunteers the sustained release properties and relative bioavailability of new once daily Euphylong 375 mg capsules (= A) were studied using twice daily Theo-Dur (= B) as reference. Theophylline was given over a period of 8 days: A once daily as a 750 mg dose at 20.00 h (with placebo at 0...
Article
Repeated exponentially decreasing influsions have been used to administer theophylline and enprofylline to show whether it would be feasible to create consecutive plasma concentration plateaus within a few hours. The infusions were carried out on two separate days in 8 stable asthmatics. Before the infusion experiments, the pharmacokinetics of the...
Article
Two g cefodizime i.v. administration at 00:00, 06:00, 12:00 and 18:00 respectively, to 8 male and 8 female, young healthy volunteers, has shown: 1. a sex-related difference in both plasma (AUC) and total cumulative excretion of the agent with larger values in females than in males; 2. a dosing time-related difference in plasma (AUC) with the larges...

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