Pierre J. Van Espen

IDAS : a Windows based software package for cluster analysis

Abstract This article is an electronic publication in Spectrochimica Acta Electronica (SAE), the electronic section of Spectrochimica Acta Part B (SAB). The hardcopy text, comprising the main article and one appendix, is accompanied by two installation diskettes with the software package and data files. The main article discusses the chemometric aspects of the package and explains its purpose. The IDAS software package combines three cluster analysis methods (hierarchical, non-hierarchical and fuzzy) and runs under MS Windows. Modified algorithms for non-hierarchical and fuzzy clusterings are described. The interpretation of the clustering results is facilitated by the extensive use of different types of graph. New approaches to the graphical representation of the results of fuzzy clustering are proposed. Two data sets, the Iris data by Fisher and a data set on the chemical composition of tea, are used to demonstrate the capabilities of the software.

Speciation analysis of oxides with static secondary ion mass spectrometry.

Speciation analysis of inorganic solids, without dissolution of the sample, aims at specific molecular information. Two potentially useful microanalytical techniques emerge, namely, laser microprobe mass spectrometry (LMMS) and static secondary ion mass spectrometry (S-SIMS). This paper focuses on the molecular characterisation of oxides by application of the S-SIMS method. For this purpose, mass spectra of pure oxides were acquired under static conditions. Analytical parameters such as repeatability, accuracy and resolution were assessed. Also, the peak patterns in the mass spectra are discussed in connection with the older Plog model, describing the relative ion yield as a function of the cluster size. Finally, a comparison is made with the mass spectra from a S-SIMS library and with those obtained by Fourier transform LMMS. Copyright 1999 John Wiley & Sons, Ltd.

An integrated system for quantitative EDXRF analysis based on fundamental parameters

Abstract A procedure for quantitative energy-dispersive X-ray fluorescence analysis is presented. It relies on the fundamental parameter equation and optionally uses the intensity of the scattered excitation radiation to estimate the composition and mass per unit area of the low-atomic-number part of the matrix. The procedure has been implemented as part of a larger software package, AXIL-QXAS, which includes spectrum-acquisition and spectrum-analysis programs and runs on a personal computer.

Methodology for spectrum evaluation in quantitative electron energy‐loss spectrometry using the Zeiss CEM902

The spectral energy‐loss intensities acquired with the Zeiss CEM902 do not follow a Poisson law. The intensities are normally distributed and their variances are non‐uniform. When fitting the inverse power law after logarithmic transformation, it is expected that the power law coefficients and their uncertainties will be biased. Due to the particular dependence of the variance on the intensity which is observed in our experiments, it appears that no bias is introduced when using unweighted least‐squares fitting after log‐log transformation. Because the sample variances are estimated with low degrees of freedom, the residual variance of the fit is proposed as a criterion rather than the X2 test to evaluate the optimum width of the fitting window. The optimal width for the integration window can be determined as the window where the signal‐to‐noise ratio is at a maximum. Critical limits for qualitative and quantitative analysis are proposed which are based on the variance of the net intensity. They can be used to test the analytical significance of the signals.

Robust Multivariate Methods: The Projection Pursuit Approach

Projection pursuit was originally introduced to identify structures in multivariate data clouds (Huber, 1985). The idea of projecting data to a low-dimensional subspace can also be applied to multivariate statistical methods. The robustness of the methods can be achieved by applying robust estimators to the lower-dimensional space. Robust estimation in high dimensions can thus be avoided which usually results in a faster computation. Moreover, flat data sets where the number of variables is much higher than the number of observations can be easier analyzed in a robust way.

Compositional Classification of Archaeological Pottery Based on INAA and SEM-EDX

Abstract The suitability of combining Instrumental Neutron Activation Analysis (INAA) and Electron Probe X-ray Microanalysis (SEM-EDX) for the classification of archaeological pottery based on their composition is illustrated with two examples of different nature and complexity: the study of Cuban aborigine pottery production and distribution and the classification of Majolica from the colonial period. The different scope and features of both techniques complement each other in achieving a more consistent and complete characterization of the composition and structure of the ceramic paste.

Characterisation of the Shape of Microparticles via Fractal and Fourier Analyses of Scanning Electron Microscope Images

Two different approaches based on Fourier and fractal analyses, are applied for particle shape characterisation. The advantages and limitations of both approaches as well as their fields of application are discussed. Examples of the application of these approaches for particles of various types are given.

Chemometrical approach to the determination of the fractal dimension(s) of real objects

Abstract Fractal dimension has been recognized for a long time as a useful parameter for shape characterisation. However, the use of the fractals concept requires the visual inspection of the Richardson plot which hampers the practical applications. In this paper a fully automatical method for the analysis of the Richardson plot is described. A clustering approach is adopted instead of the visual inspection of Richardson plot. Cases which explain the application of the method are examined.

Size-differentiated composition of aerosol in Khartoum, Sudan

Abstract Aerosol samples were collected in Khartoum, Sudan, using a 5-stage cascade impactor. The samples were analyzed for up to 29 elements by particle-induced X-ray emission (PIXE). The size distributions and enrichment factors indicated that most of the elements in the Khartoum aerosol originate from a soil dispersion source and that the anthropogenic contribution is important only for S, Cl, Br, and Pb and to a lesser extent for Cu and Zn. Comparison of the enrichment factors for the elements in the Khartoum aerosol with literature values indicated the lowest enrichment factors reported for these elements so far. Multivariate analysis of the data showed that the anthropogenic contribution was important in the small particle size range (0.25–0.5 μm) and that for the larger particles soil dispersion prevailed.

The partial robust M-approach

The PLS approach is a widely used technique to estimate path models relating various blocks of variables measured from the same population. It is frequently applied in the social sciences and in economics. In this type of applications, deviations from normality and outliers may occur, leading to an efficiency loss or even biased results. In the current paper, a robust path model estimation technique is being proposed, the partial robust M (PRM) approach. In an example its benefits are illustrated.