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“Automated particle analysis of populations of silver halide microcrystals by electron probe microanalysis under cryogenic conditions”. Gregory CL, Nullens HA, Gijbels RH, van Espen PJ, Geuens I, de Keyzer R, Analytical chemistry 70, 2551 (1998). http://doi.org/10.1021/ac9710644
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT); Chemometrics (Mitac 3)
Impact Factor: 6.32
Times cited: 12
DOI: 10.1021/ac9710644
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“Fractal dimensional classification of aerosol particles by computer-controlled scanning electron microscopy”. Kindratenko VV, van Espen PJM, Treiger BA, Van Grieken RE, Environmental science and technology 28, 2197 (1994). http://doi.org/10.1021/ES00061A031
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation); Chemometrics (Mitac 3)
DOI: 10.1021/ES00061A031
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“Size-differentiated composition of aerosols in Khartoum, Sudan”. Eltayeb MAH, van Espen PJ, Cafmeyer J, Van Grieken RE, Maenhaut W, The science of the total environment 120, 281 (1992). http://doi.org/10.1016/0048-9697(92)90062-W
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation); Chemometrics (Mitac 3)
DOI: 10.1016/0048-9697(92)90062-W
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“Case specific prediction intervals for tri-PLS1 : the full local linearisation”. Serneels S, Faber K, Verdonck T, van Espen PJ, Chemometrics and intelligent laboratory systems 108, 93 (2011). http://doi.org/10.1016/J.CHEMOLAB.2011.05.002
Abstract: A new method to estimate case specific prediction uncertainty for univariate trilinear partial least squares (tri-PLS1) regression is introduced. This method is, from a theoretical point of view, the most exact finite sample approximation to true prediction uncertainty that has been reported up till now. Using the new method, different error sources can be propagated, which is an advantage that cannot be offered by data driven approaches such as the bootstrap. In a concise example, it is illustrated how the method can be applied. In the Appendix, efficient algorithms are presented to compute the estimates required.
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
DOI: 10.1016/J.CHEMOLAB.2011.05.002
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“Possibilities of energy-resolved X-ray radiography for the investigation of paintings”. Cabal Rodríguez AE, Leyva Pernia D, Schalm O, van Espen PJM, Analytical and bioanalytical chemistry 402, 1471 (2012). http://doi.org/10.1007/S00216-011-5230-X
Abstract: X-ray radiographic images of paintings often show little or no contrast. In order to increase the contrast in radiographic images we measured the X-ray spectrum of a low power X-ray tube, after passing through the painting, with a high energy-resolution SDD detector. To obtain images, the detector is collimated with a 400 mu m diameter pinhole and the painting was moved through the beam in the x and y-direction using a dwell time of a few seconds per pixel. The data obtained consists of a data cube of, typically, 200 x 200 pixels and a 512-channel X-ray spectrum for each pixel, spanning the energy range from 0 to 40 keV. Having the absorbance spectrum available for each pixel, we are able, a posteriori, to produce images by edge subtraction for any given element. In this way high contrast, element-specific, images can be obtained. Because of the high energy-resolution a much simpler edge subtraction algorithm can be applied. We also used principal-component imaging to obtain, in a more automated way, images with high contrast. Some of these images can easily be attributed to specific elements. It turns out that preprocessing of the spectral data is crucial for the success of the multivariate image processing.
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
DOI: 10.1007/S00216-011-5230-X
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