Sven Serneels unpaid staff

Research Sven Serneels

Research team

Extension of robust chemometrical methods to two and three way data with missing elements. 01/10/2006 - 31/12/2006

Abstract

Researcher(s)

Research team(s)

    Project type(s)

    • Research Project

    Quantitaive analysis of rolling emulsions by means of infrared spectrometry and partial least squares regression. 01/10/2004 - 30/09/2006

    Abstract

    The composition of rolling emulsions varies throughout the production process. Since the exact composition at a certain time is unknown, it is nearly impossible to provide standard solutions in the laboratory. Hence, in this work, emulsions emerging from the process stream are quantified by dint of the generalized standard additions method (GSAM). These solutions are then used as standards for calibration, which is being done by means of partial least squares regression (PLS). Albeit this technique has become a standard routine in many a laboratory, its theoretical aspects remain mostly unknown. In this work, these theoretical aspects are investigated and elucidated, which leads to the construction of more realistic sample specific prediction intervals, as well as to a more robust method.

    Researcher(s)

    Research team(s)

      Project type(s)

      • Research Project

      Quantitaive analysis of rolling emulsions by means of infrared spectrometry and partial least squares regression 01/10/2002 - 30/09/2004

      Abstract

      The composition of rolling emulsions varies throughout the production process. Since the exact composition at a certain time is unknown, it is nearly impossible to provide standard solutions in the laboratory. Hence, in this work, emulsions emerging from the process stream are quantified by dint of the generalized standard additions method (GSAM). These solutions are then used as standards for calibration, which is being done by means of partial least squares regression (PLS). Albeit this technique has become a standard routine in many a laboratory, its theoretical aspects remain mostly unknown. In this work, these theoretical aspects are investigated and elucidated, which leads to the construction of more realistic sample specific prediction intervals, as well as to a more robust method.

      Researcher(s)

      Research team(s)

        Project type(s)

        • Research Project