Program > Pre-conference courses

We are pleased to host 4 pre-conference short courses taught by international experts. Courses will be offered on Sunday in half-day sessions.
Course fee is 150 euros per course for each half-day, materials and coffee break included.

Chemometrics in Process Monitoring and Control
Brian Rohrback, PhD (Infometrix, Inc.), Sunday 13.30 – 16.30

The manufacturing sector is the largest source of structured data being collected today.  These data relate directly and indirectly to decisions that impact profitable operation, product quality, and plant safety. 
Chemometrics is applicable to many data analysis activities important to this decision making and range from signal processing (improving the fidelity of the data) to interpretation (mostly classification and quantitation).  In contrast with academic work, process chemometrics must function reliably even in the hands of those unversed in our favorite science. 

This session will provide a discussion of chemometrics and its applications to three important sources of process information: sensors, chromatographs, and optical spectrometers.

Introduction to Hyperspectral/Multivariate Image Analysis
Barry Wise, PhD (Eigenvector Research), Sunday 13.30 – 16.30

Hyperspectral images are becoming increasingly common in analytical chemistry and remote sensing applications. They are based on several types of spectroscopy and spectrometry including Raman, IR and SIMS.

Introduction to Hyperspectral/Multivariate Image Analysis (MIA) starts with a brief review of sources of multivariate images and tools for viewing and investigating them.
Practical image analysis with Principal Components Analysis (PCA) demonstrates how information from hyperspectral images can be compressed and displayed, and how classification tools such as SIMCA and PLS-DA can be used to identify similar areas.
The course concludes with some examples of Multivariate Curve Resolution (MCR) on images and demonstrates how it can be used to create chemical maps.

The course includes hands-on computer time for participants to work example problems using PLS_Toolbox and MIA_Toolbox, or Solo+MIA.

Multivariate cure resolution
R. Tauler, J. Jaumot PhD (CSIC), Sunday 9.30 – 12.30

This course is dedicated to presenting the theoretical aspects of the MCR method and to its practical applications. Procedures are described for exploring the structure of the data, generation of initial estimates, choosing appropriate constraints, and to the application of MCR to data sets arranged in a table or matrix or to data multisets arranged in multiple data tables, data matrices, data cubes or data hypercubes with multiple directions or ways (three-way, multi-way data).

Theoretical aspects will be accompanied with various selected examples. Ways to handle and ascertain the presence of uncertainties in MCR results due to rotation ambiguities or to noise propagation will be described. Extensions of the MCR-ALS method to the analysis of kinetic reaction data will be also introduced.

1) The PCA and MCR bilinear model. The MCR-ALS method. Number of components, initial estimates and constraints (non-negativity, unimodality, mass balance, selectivity / local rank, etc).
2) MCR application to the study of a) chemical reactions and processes, b) hyphenated chromatography, c) hyperspectral imaging, d) environmental data; e) metabolomics/lipìdomics data.
3) MCR for multiset and multiway data analysis.  Multilinear models and implementation of constraints (trilinear, quadrilineal, interaction ...). MCR for multidimensional spectroscopy and chromatography.
4) MCR Quantitative. MCR ambiguity: MCR-BANDS. Handling data uncertainties: MLPCA-MCR-ALS. MCR hard and soft modelling analysis of kinetic data

Deep learning with applications in spectroscopy and imaging
David Rousseau (Okina), Sunday 9.30 – 12.30

 Course description to be added


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