bluuebunny/crossref_metadata_2025_split huggingface dataset:
On unifying multiblock analysis with application to decentralized process monitoring
Authors: Qin S. Joe , Valle Sergio , Piovoso Michael J. 
Published: September 2002

AbstractWesterhuis et al. (J. Chemometrics 1998; 12: 301–321) show that the scores of consensus PCA and multiblock PLS (Westerhuis and Coenegracht, J. Chemometrics 1997; 11: 379–392) can be calculated directly from the regular PCA and PLS scores respectively. In this paper we show that both the loadings and scores of consensus PCA can be calculated directly from those of regular PCA, and the multiblock PLS loadings, weights and scores can be calculated directly from those of regular PLS. The orthogonal properties of four multiblock PCA and PLS algorithms are explored. The use of multiblock PCA and PLS for decentralized monitoring and diagnosis is derived in terms of regular PCA and PLS scores and residuals. While the multiblock analysis algorithms are basically equivalent to regular PCA and PLS, blocking of process variables in a large‐scale plant based on process knowledge helps to localize the root cause of the fault in a decentralized manner. New definitions of block and variable contributions to SPE and T 2 are proposed for decentralized monitoring. This decentralized monitoring method based on proper variable blocking is successfully applied to an industrial polyester film process. Copyright © 2001 John Wiley & Sons, Ltd.
Weighing schemes in multivariate data analysis
Authors: Höskuldsson Agnar 
Published: September 2002

AbstractA collection of methods will be presented, designed to reflect special purpose or features in data. Many chemometric methods can be viewed as an application of special weighing schemes of the type presented here. After a short review of the H‐principle of mathematical modelling, it will be applied to develop different weighing schemes and some simple ways to judge the quality or significance of a weighing scheme. Weighing schemes for two‐way data will be established. We shall show how a loading vector can be adapted to a given score vector in order to improve the possibilities of interpretation of the results. These results will be extended to multiway data. It will be shown how we can develop different weighing schemes for multiway data depending on the purpose or interpretability of the results. The importance of these weighing schemes is due to the fact that they yield or emphasize the part of data that is ‘in focus’ in relation to the task in question. Copyright © 2001 John Wiley & Sons, Ltd.
Rapid estimation of chemical kinetics by implicit calibration. I
Authors: Taavitsainen Veli‐Matti , Haario Heikki 
Published: September 2002

AbstractIn this study, methods for estimating kinetic parameters from on‐line measurements of batch reactions are developed. The basic idea is to combine non‐linear parameter estimation with implicit calibration between measured spectra and concentrations given by a known kinetic model. Several alternatives for the calibration step are discussed and the three most promising methods have been studied more closely. The basic ideas and identifiability questions are elucidated by simulation studies with simple kinetic models. The simulations show that the implicit calibration method works also with uncalibrated chromatograms. Two real esterification reactions with spectroscopic data are studied. In the first one, concentration data are available and our method gives results quite similar to those obtained in more traditional ways. The latter reaction, however, was a fast one and consequently off‐line calibration based on known mixtures failed. In contrast, our method gave almost identical parameter values to the ones obtained by an independent study on the same reaction based on a complicated on‐line chromatographic measurement system. In this case the results were compared with a new way of using pure component spectra and generalized ridge regression with stoichiometric constraints. Our studies show that the most important factors in obtaining reliable results are proper design of the batch experiments, proper weighting of the initial measurements of each batch and proper measure for goodness of fit. Copyright © 2001 John Wiley & Sons, Ltd.
Understanding the collinearity problem in regression and discriminant analysis
Authors: Næs Tormod , Mevik Bjørn‐Helge 
Published: September 2002

AbstractThis paper presents a discussion of the collinearity problem in regression and discriminant analysis. The paper describes reasons why the collinearity is a problem for the prediction ability and classification ability of the classical methods. The discussion is based on established formulae for prediction errors. Special emphasis is put on differences and similarities between regression and classification. Some typical ways of handling the collinearity problems based on PCA will be described. The theoretical discussion will be accompanied by empirical illustrations. Copyright © 2001 John Wiley & Sons, Ltd.
Hierarchical principal component analysis (PCA) and projection to latent structure (PLS) technique on spectroscopic data as a data pretreatment for calibration
Authors: Janné K. , Pettersen J. , Lindberg N.‐O. , Lundstedt T. 
Published: September 2002

AbstractSpectroscopic data consists of several hundred to some thousand variables, wherein most of the variables are autocorrelated. When PCA and PLS techniques are used for the interpretation of these kinds of data, the loading plots are usually complex due to the covariation in the spectrum, and therefore difficult to correlate to the corresponding score plot. One of the standard methods used to decrease the influence of light scatter or shifts of the spectra is the multiplicative scatter correction technique. Another technique is the hierarchical multiblock segmentation technique, where new variables are created from the original data by blocking the spectra into sub spectra, and then projecting the sub spectra by PCA. These new variables are then used in the coming PCA or PLS calculations. These techniques reduce the random and non‐wanted signals from e.g. light scatter, but still conserve all systematic information in the signals, but the greatest advantage is that the technique gives an easier interpretation of the correlation between scores and the loadings. Two examples are presented; the attenuated total reflection (ATR) and NIR, which show the advantages as well as the implementation of the method. Copyright © 2001 John Wiley & Sons, Ltd.
Multivariate process monitoring of a newsprint mill. Application to modelling and predicting COD load resulting from de‐inking of recycled paper
Authors: Eriksson Lennart , Hagberg Peggy , Johansson Erik , Rännar Stefan , Whelehan Oliver , Åström Anders , Lindgren Torbjörn 
Published: September 2002

AbstractMultivariate process monitoring was applied to understand the influence of numerous production parameters on the release of organic matter into the effluent of a newsprint mill. The release was characterized by measuring the chemical oxygen demand (COD). The relationships between over 50 process variables and the COD load were investigated using PLS regression and time series analysis. The results showed that variations in COD could be predicted accurately. Furthermore, model interpretation identified the most influential process parameters. Copyright © 2001 John Wiley & Sons, Ltd.
The GIFI approach to non‐linear PLS modeling
Authors: Berglund Anders , Kettaneh Nouna , Uppgård Lise‐Lott , Wold Svante , Bendwell Nancy , Cameron Dave R. 
Published: September 2002

AbstractThe GIFI approach to non‐linear modeling involves the transformation of quantitative variables to a set of 1/0 dummies in a similar manner to the way qualitative variables are coded. This is followed by analyzing the sets of 1/0 dummies by principal component analysis, multiple regression or, as discussed here, PLS. The patterns of the resulting coefficients indicate the nature of the non‐linearities in the data. Here the potential uses and limitations of PLS regression, in combination with four variants of GIFI coding, are investigated using both simulated and empirical data sets. Copyright © 2001 John Wiley & Sons, Ltd.
Interpretation of regression coefficients under a latent variable regression model
Authors: Burnham Alison J. , MacGregor John F. , Viveros Roman 
Published: September 2002

AbstractIn standard linear regression where the predictor matrix X is of full rank, the regression coefficients are clearly defined as the parameters B appearing in the linear regression model. In latent variable models there is no direct relationship between the predictor variables and response variables. Rather they are both related to an underlying reduced‐rank set of latent variables. Recent papers have proposed different methods for obtaining approximate covariance matrices for the estimates of the regression coefficients from methods such as partial least squares (PLS) and for using them to determine ‘confidence intervals’, for variable selection and for judging variable importance. However, in the latent variable model a matrix of regression coefficients, B, does not even appear as a parameter matrix. In the situation where the data follow such a model, it is therefore uncertain how the regression coefficients and, by extension, any covariance matrices and ‘confidence intervals’ should be interpreted. In this paper we show that any inference is critically dependent upon how one defines these regression coefficients. Two definitions for the regression coefficients are given that are consistent with the latent variable model. Which of these definitions is more relevant is shown to be highly dependent on the goals of the analysis. Therefore one must be clear on the definition one is using for these coefficients when building predictive models, when screening variables based on them or when using them to make interpretations about the system. Under standard normality assumptions, different estimation methods such as ordinary least squares (OLS) and PLS are shown to provide very different distributions for the regression coefficient estimates when the data follow a latent variable model. This is shown to be not just a matter of the PLS coefficients being biased or the OLS estimates having large variance, but of more complex differences implied by the structure of the model parameters in the latent variable model. How the distributions for these estimates relate to the definitions given in this paper is explored here. It is shown for a simple case that the relative size of the PLS estimates, on average, tends to reflect the latent variable loadings, whereas the relative size of the OLS estimates, on average, is a function not only of the loadings but also of the error variances for the predictor variables. Thus in this particular case it appears that the relative size of the B parameters from PLS reflects the underlying latent structure, whereas those from OLS also reflect the error structure of the predictor variables. Copyright © 2001 John Wiley & Sons, Ltd.
2D wavelet analysis and compression of on‐line industrial process data
Authors: Trygg Johan , Kettaneh‐Wold Nouna , Wallbäcks Lars 
Published: September 2002

AbstractIn recent years the wavelet transform (WT) has interested a large number of scientists from many different fields. Pattern recognition, signal processing, signal compression, process monitoring and control, and image analysis are some areas where wavelets have shown promising results. In this paper, 2D wavelet analysis and compression of near‐infrared spectra for on‐line monitoring of wood chips is reviewed. We introduce a new parameter for outlier detection, distance to model in wavelet space (DModW), which is analogous to the residual parameter (DModX) used in principal component analysis (PCA) and partial least squares analysis (PLS). Additionally, we describe the wavelet power spectrum (WPS), the wavelet analogue of the power spectrum. The WPS gives an overview of the time–frequency content in a signal. In the example given, wavelets improved the detection of spectral shift and compressed data 1000‐fold without degrading the quality of the 2D wavelet‐compressed PCA model. The example concerned an industrial process‐monitoring situation where near‐infrared spectra are measured on‐line on top of a conveyer belt filled with wood chips at a Swedish pulp plant. Copyright © 2001 John Wiley & Sons, Ltd.
Feasibility of EMF‐induced pipeline wall friction reduction by PLS2 intercalibration of acoustic chemometrics and reference laser velocimetry
Authors: Esbensen Kim H. , Waskaas Magne , Matveyev Inger Hedvig , Wolden Kjell Erik , Lode Jan Gunnar , Lied Thorbjørn T. , Halstensen Maths 
Published: September 2002

AbstractVarious applied physics lines of research on the interactions between electromagnetics and flowing water have led to the suggestion that it might be possible to reduce pipeline wall friction by applying a transverse electromagnetic field (EMF). We here conduct a feasibility study of the shape and magnitude of internal fluid flow velocity profiles of hydropower turbine inlet pipelines, with and without an EMF. The flow velocity profile itself can only be measured in transparent pipeline sections with the aid of refined laser velocimetric equipment, which can never be employed in realistic hydropower settings however. The objective of the present studies is therefore to use a much simpler alternative, i.e. an acoustic chemometric approach, relying on ‘clamp‐on’ acoustic sensors applied directly to the outer wall of the pipeline. Our results show that it is fully possible to verify the ‘on/off’ status of the applied EMF using either of the alternative modalities, laser velocimetry and acoustic chemometrics, i.e. to verify an increased water flux when the EMF is ‘on’. The interactions between this feature and realistic changing temperatures (15–27  °C) as well as varying overall water velocities (1–4 m s−1) are explored. It is concluded that the temperature sensitivities of both modalities can be compensated for and, furthermore, that the temperature‐compensated modelling is velocity‐invariant. This opens up an interesting avenue for field on‐line EMF‐induced wall friction reduction monitoring and control. Our final feasibility demonstration concerns direct PLS2 intercalibration of the acoustic chemometric monitoring data (X) with the laser velocimetric reference profiles (Y). This translates into a new acoustic chemometric possibility for ‘seeing’ the effects of the EMF‐modified velocity profiles directly from the suitably calibrated acoustic signals alone. We find that a 42‐Y‐variable PLS2 model can be validated as X, Y: 30%, 70% respectively, fully satisfactory for prediction purposes of the velocity in an outer (near‐wall) 5–6 mm annular flow regimen. With this we have positive proof that acoustic chemometric monitoring can be used for predicting the effects of the EMF. Upscaling to field‐scale pipelines remains. Copyright © 2001 John Wiley & Sons, Ltd.
The price paid for the second‐order advantage when using the generalized rank annihilation method (GRAM)
Authors: Faber Nicolaas (Klaas) M. 
Published: September 2002

AbstractIn a ground‐breaking paper, Linder and Sundberg developed a statistical framework for the calibration of bilinear data (Chemometrics Intell. Lab. Syst. 1998; 42: 159–178). Within this framework they formulated three different predictor construction methods (J. Chemometrics accepted), namely a so‐called naive method, a least squares (LS) method and a refined version of the latter that takes account of the calibration uncertainty. They showed that the naive method is statistically less efficient than the others under the assumption of white noise. In the current work a close relationship is established between the generalized rank annihilation method (GRAM) and the naive method by comparing expressions for prediction variance. The main conclusion is that the relatively poor efficiency of GRAM is the price one pays for obtaining the second‐order advantage with a single calibration sample. Copyright © 2001 John Wiley & Sons, Ltd.
Application of PARAFAC2 to fault detection and diagnosis in semiconductor etch
Authors: Wise Barry M. , Gallagher Neal B. , Martin Elaine B. 
Published: September 2002

AbstractMonitoring and fault detection of batch chemical processes are complicated by stretching of the time axis, resulting in batches of different length. This paper offers an approach to the unequal time axis problem using the parallel factor analysis 2 (PARAFAC2) model. Unlike PARAFAC, the PARAFAC2 model does not assume parallel proportional profiles, but only that the matrix of profiles preserves its ‘inner product structure’ from sample to sample. PARAFAC2 also allows each matrix in the multiway array to have a different number of rows. It has previously been demonstrated how the PARAFAC2 model can be used to model chromatographic data with retention time shifts. Fault detection and, to a lesser extent, diagnosis in a semiconductor etch process are considered in this paper. It is demonstrated that PARAFAC2 can effectively model batch process data from semiconductor manufacture with unequal dimension in one of the orders, such as the unequal batch length problem. It is shown that the PARAFAC2 model has approximately the same sensitivity to faults as other competing methods, including principal component analysis (PCA), unfold PCA (often referred to as multiway PCA), trilinear decomposition (TLD) and conventional PARAFAC. The advantage of PARAFAC2 is that it is easier to apply than MPCA, TLD and PARAFAC, because unequal batch lengths can be handled directly rather than through preprocessing methods. It also provides additional diagnostic information: the recovered batch profiles. It is likely, however, that it is less sensitive to faults than conventional PARAFAC. Copyright © 2001 John Wiley & Sons, Ltd.
Distribution of thyrotropin‐releasing hormone (TRH) immunoreactivity in the brain of the zebrafish (Danio rerio)
Authors: Díaz María Luz , Becerra Manuela , Manso María Jesús , Anadón Ramón 
Published: September 2002

AbstractThe distribution of thyrotropin‐releasing hormone (TRH) in the brain of the adult zebrafish was studied with immunohistochemical techniques. In the telencephalon, abundant TRH‐immunoreactive (TRHir) neurons were observed in the central, ventral, and supra‐ and postcommissural regions of the ventral telencephalic area. In the diencephalon, TRHir neurons were observed in the anterior parvocellular preoptic nucleus, the suprachiasmatic nucleus, the lateral hypothalamic nucleus, the rostral parts of the anterior tuberal nucleus and torus lateralis, and the posterior tuberal nucleus. Some TRHir neurons were also observed in the central posterior thalamic nucleus and in the habenula. The mesencephalon contained TRHir cells in the rostrodorsal tegmentum, the Edinger‐Westphal nucleus, the torus semicircularis, and the nucleus of the lateral lemniscus. Further TRHir neurons were observed in the interpeduncular nucleus. In the rhombencephalon, TRHir cells were observed in the nucleus isthmi and the locus coeruleus, rostrally, and in the vagal lobe and vagal motor nucleus, caudally. In the forebrain, TRHir fibers were abundant in several regions, including the medial and caudodorsal parts of the dorsal telencephalic area, the ventral and commissural parts of the ventral telencephalic area, the preoptic area, the posterior tubercle, the anterior tuberal nucleus, and the posterior hypothalamic lobe. The dorsal thalamus exhibited moderate TRHir innervation. In the mesencephalon, the optic tectum received a rich TRHir innervation between the periventricular gray zone and the stratum griseum centrale. A conspicuous TRHir longitudinal tract traversed the tegmentum and extended to the rhombencephalon. The medial and lateral mesencephalic reticular areas and the interpeduncular nucleus were richly innervated by TRHir fibers. In the rhombencephalon, the secondary gustatory nucleus received abundant TRHir fibers. TRHir fibers moderately innervated the ventrolateral and ventromedial reticular area and richly innervated the vagal lobe and Cajal's commissural nucleus. Some TRHir fibers coursed in the lateral funiculus of the spinal cord. Some TRHir amacrine cells were observed in the retina. The wide distribution of TRHir neurons and fibers observed in the zebrafish brain suggests that TRH plays different roles. These results in the adult zebrafish reveal a number of differences with respect to the TRHir systems reported in other adult teleosts but were similar to those found during late developmental stages of trout (Díaz et al., 2001). J. Comp. Neurol. 450:45–60, 2002. © 2002 Wiley‐Liss, Inc.
Effect of boundary element details on the seismic deformation capacity of structural walls
Authors: Oh Young‐Hun , Han Sang Whan , Lee Li‐Hyung 
Published: September 2002

AbstractThe objective of this study is to investigate the effect of boundary element details of structural walls on their deformation capacities. Structural walls considered in this study have different sectional shapes and/or transverse reinforcement content at the boundaries of the walls (called boundary element details hereafter). Four full‐scale wall specimens (3000mm (hw)×1500mm (lw)×200mm (T)) were fabricated and tested. Three specimens are rectangular in section and the other specimen has a barbell‐shaped cross‐section (a wall with boundary columns). The rectangular wall specimens are reinforced according to the common practice used for reinforced concrete residence buildings in Korea and Chile. In this study, the primary variable for these rectangular specimens is the content of transverse reinforcement to confine the boundary elements of a wall. The barbell‐shaped specimen was designed in compliance with ACI 318‐95. The response of the barbell‐shaped specimen is compared with those of other rectangular specimens. The effective aspect ratio of the specimens is set to two in this study. Based on the experimental results, it is found that the deformation capacities of walls, which are represented by displacement ductility, drift ratio and energy dissipation capacities, are affected by the boundary element details. Copyright © 2002 John Wiley & Sons, Ltd.
Improved control algorithm for real‐time substructure testing
Authors: Darby A. P. , Blakeborough A. , Williams M. S. 
Published: September 2002

AbstractReal‐time substructure testing is a novel method of testing structures under dynamic loading. The complete structure is separated into two substructures, one of which is tested physically at large scale and in real time, so that time‐dependent non‐linear behaviour of the substructure is realistically represented. The second substructure represents the surrounding structure, which is modelled numerically. In the current formulation this numerical substructure is assumed to remain linear. The two substructures interact in real‐time so that the response of the complete structure, incorporating the non‐linear behaviour of the physical substructure, is accurately represented. This paper presents several improvements to the linear numerical modelling of substructures for use in explicit time‐stepping routines for real‐time substructure testing. An extrapolation of a first‐order‐hold discretization is used which increases the accuracy of the numerical model over more direct explicit methods. Additionally, an integral form of the equation of motion is used in order to reduce the effects of noise and to take into account variations of the input over a time‐step. In order to take advantage of this integral form, interpolation of the model output is performed in order to smooth the output. The improvements are demonstrated using a series of substructure tests on a simple portal frame. While the testing approach is suitable for cases in which the physical substructure behaves non‐linearly, the results presented here are for fully linear systems. This enables comparisons to be made with analytical solutions, as well as with the results of tests based on the central difference method. Copyright © 2001 John Wiley & Sons, Ltd.