Chemometrics analogy

As explained in Section 33.2.1, one can prefer to consider each class separately and to perform outlier tests to decide whether a new object belongs to a certain class or not. The earliest approaches, introduced in chemometrics, were called SIMCA (soft independent modelling of class analogy) [27] and UNEQ [28]. 

We will go so far as to make an analogy with Chemistry itself. The alchemists of old had an enormous empirical knowledge base, and from that could do all manner of useful things. But we do not consider alchemy a science, and it did not become a science until the underlying principles and phenomena were discovered and codified in a way that all could use. The current state of Chemometrics is more nearly akin to alchemy than Chemistry we can do all manner of useful things with it, but it is all empirical and there are still many areas where even the most expert and prominent practitioners treat it as a black box and make no attempt to understand the inner workings of that black box. 

Wold, S., Sjostrom, M. in Kowalski, B. R. (Ed.), Chemometrics Theory and Application, ACS Symp. Ser. 52, Vol. 52, American Chemical Society, Washington, DC, 1977, pp. 243-282. SIMCA A method for analyzing chemical data in terms of similarity and analogy. 

Multidimensional Data Intercomparisons. Estimation of reliable uncertainty intervals becomes quite complex for non-linear operations and for some of the more sophisticated multidimensional models. For this reason, "chemometric" validation, using common, carefully-constructed test data sets, is of increasing importance. Data evaluation intercomparison exercises are thus analogous to Standard Reference Material (SRM) laboratory intercomparisons, except that the final, data evaluation step of the chemical measurement process is being tested. 

The full-scale industrial experiment demonstrated the feasibility of a convenient, nonintrusive aconstic chemometric facility for reliable ammonia concentration prediction. The training experimental design spanned the industrial concentration range of interest (0-8%). Two-segment cross-validation (test set switch) showed good accnracy (slope 0.96) combined with a satisfactory RMSEP. It is fully possible to further develop this pilot study calibration basis nntil a fnll industrial model has been achieved. There wonld appear to be several types of analogous chemical analytes in other process technological contexts, which may be similarly approached by acoustic chemometrics. 

Chemometrics, as defined by Kowalski (1), includes the application of multivariate statistical methods to the study of chemical problems. SIMCA (Soft Independent Method of Class Analogy) and other multivariate statistical methods have been used as tools in chemometric investigations. SIMCA, based on principal components, is a multivariate chemometric method that has been applied to a variety of chemical problems of varying complexity. The SIMCA-3B program is suitable for use with 8- and 16-bit microcomputers. 

In a related paper Herrador and Gonzalez [144] described the application of PCA and CA and of two supervised techniques, LDA and back-propagated ANN on Al, Ba, Ca, Cu, K, Mg, Mn, and Zn data obtained from commercial Spanish tea samples. A minitorch ICP-AES instrument was used for the determinations. The characterization of three classes of tea was achieved. In a paper that expands previous research described in reference [47], trace metal concentrations measured by ICP-AES and ICP-MS were employed by Moreda-Pineiro et al. [145] for a more elaborated chemometric treatment on 85 samples of tea of Asian, African, commercial, and unknown origin. Seventeen elements (Al, Ba, Ca, Cd, Co, Cr, Cu, Cs, Mg, Mn, Ni, Pb, Rb, Sr, Ti, V, and Zn) were determined. In addition to the techniques employed in the already mentioned papers (PCA, CA, LDA), soft independent modeling (SIM) of class analogy was also applied. The latter method resulted in the totally correct (100 percent) classification of Chinese teas. 

Wold S, Kettaneh N, Friden H, Holmberg A, Modelling and diagnostics of batch processes and analogous kinetic experiments, Chemometrics and Intelligent Laboratory Systems, 1998,44,331-340. 

The application of chemometric procedures coupled with derivative spectroscopy permits achievement of higher selectivity in determination of P-lactam antibiotics. Currently, chemometric procedures based on the estimated ratio of spectra derivative for the selective determination of P-lactam analogs are the most common. It was proved that the application of the ratio of different-order spectra derivatives permitted the separation of binary and tertiary mixtures of P-lactam antibiotics [22]. During the determination of concentrations of three components (e.g., penicillin-G sodium, penicillin-G procain and dihydrostreptomycin sulphate salts) in a mixture the equation describing the ratio spectra derivative spetrophotometry is as follows ... 

Depjending on chemometric procedure, the selective determination of following analogs was possible ... 

Acoustic emission power spectra are similar in many respects to optical spectra and are amenable to chemometric processing (multivariate analysis). Principal component analysis, partial least squares (PLS), neural networks, and qualitative techniques such as SIMCA (soft independent modeling of class analogy a pattern recognition technique) have been employed... 

S. Wold and M. Sjostrom, SIMCA A Method for Analysing Chemical Data in Terms of Similarity and Analogy, in Symposium on Chemometrics, Theory and Application, B. R. Kowalski (ed.), Washington, DC American Chemical Society, 1977, vol. 52, p. 243. 

Chemometrics is a convenient mathematical tool for developing QSRR or scaling laws that can be embedded in process models. It is somewhat analogous to Wei and Kuo s treatment in that it contracts system dimensions through a projective transformation. Each lump is a linear combination of all original variables. The widely used principal component analysis (PCA) and partial least squares (PLS) are two examples of chemometric modeling. 

Mass spectrometry and chemometric methods cover very diverse fields Different origin of enzymes can be disclosed with LC-MS and multivariate analysis [45], Pyrolysis mass spectrometry and chemometrics have been applied for quality control of paints [46] and food analysis [47], Olive oils can be classified by analyzing volatile organic hydrocarbons (of benzene type) with headspace-mass spectrometry and CA as well as PC A [48], Differentiation and classification of wines can similarly be solved with headspace-mass spectrometry using unsupervised and supervised principal component analyses (SIMCA = soft independent modeling of class analogy) [49], Early prediction of wheat quality is possible using mass spectrometry and multivariate data analysis [50],... 

An electronic nose can be useful for analyzing volatile compoimds. It works in a way analogous to the way a hmnan nose functions and does not require previous separation of individual volatile compoimds. The system provides a pattern of volatile compoimds present in the samples. For data analysis chemometrics methods are necessary. 

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