Artificial Neural Networks (ANNs) are non-linear computational tools suitable to a great host of practical application due to their flexibility and adaptability. However, their application to the resolution of chemometric problems is relatively recent (early ‘90s). In this communication, different artificial neural networks architectures are presented and their application to different kinds of...

Abstract A short discussion is given of the convenience integrating electrochemistry and chemometrics in university degrees related to chemistry, some selected examples are presented illustrate possibilities combining both disciplines for solving (electro)chemical problems different nature.

This paper developed a rapid and nondestructive method for quantitative analysis of a cheaper adulterant (wheat flour) in oat flour by NIR spectroscopy and chemometrics. Reflectance FT-NIR spectra in the range of 4000 to 12000 cm(-1) of 300 oat flour objects adulterated with wheat flour were measured. The doping levels of wheat flour ranged from 5% to 50% (w/w). To ensure the generalization per...

Beef jerky samples immersed in brine or water, both with and without ultrasound treatment were dried at 60 °C for 30, 60, 90, 120, 150, 180, 210 240 min. Drying behaviour was evaluated using ten drying kinetic models hyperspectral imaging. All reached water activity values (Aw) < 0.85 during the first 90 min of drying. Moisture content (MC) beef predicted near infrared imaging chemometrics. Par...

An ever-increasing number of patients have to undergo regular renal dialysis to compensate for acute or chronic renal failure. The adequacy of the treatment has a profound effect on patients' morbidity and mortality. Therefore, it is necessary to assess the delivered dialysis dose. For the quantification of the dialysis dose, two parameters are most commonly used, namely the K(t)/V value (norma...

In Functional Data Analysis (FDA) multivariate data are considered as sampled functions. We propose a non-supervised method for finding a good function basis that is built on the data set. The basis consists of a set of Gaussian kernels that are optimized for an accurate fitting. The proposed methodology is experimented with two spectrometric data sets. The obtained weights are further scaled u...

Partial Least Squares (PLS) is a widely used technique in chemometrics, especially in the case where the number of independent variables is significantly larger than the number of data points. There are many articles on PLS [HTF01, GK86] but the mathematical details of PLS do not always come out clearly in these treatments. This paper is an attempt to describe PLS in precise and simple mathemat...

This article is the second in a series that lists four key explanatory or tutorial references for each of 29 chemometric methods previously described. The selected are particularly helpful to explain use method spectroscopic data. Also included common computer software platforms used chemometrics.

Why to read "yet another book" on statistical methods? This is a question that may arise among chemometricians, chemists, students or anyone using chemometric methods in their research or everyday routine work. However, this book is a very good contribution to a better understanding of statistics because it really captures the point of potential misunderstanding between chemists and mathematici...

The PARAFAC tensor decomposition has enjoyed an increasing success in exploratory multi-aspect data mining scenarios. A major challenge remains the estimation of the number of latent factors (i.e., the rank) of the decomposition, which yields high-quality, interpretable results. Previously, we have proposed an automated tensor mining method which leverages a well-known quality heuristic from th...