References of "Maternova, J"
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See detailSolvent detection in indoor air with a sensor array
Maternova, J.; Romain, Anne-Claude ULg; Nicolas, Jacques ULg

in Proceedings of the 8th conference Eurodeur (2001, June)

Air composition in dwellings and public buildings is studied by means of gas chromatography and a sensor micro array 01D28 (MICROSENS, Swiss). Only benzene and its alkyl-derivatives are quantified. The ... [more ▼]

Air composition in dwellings and public buildings is studied by means of gas chromatography and a sensor micro array 01D28 (MICROSENS, Swiss). Only benzene and its alkyl-derivatives are quantified. The micro array 01D28 is composed of six metal oxide gas sensors (SnO2 doped by Pd) equipped with standard or inter-digited electrodes. Isothermal working mode (500oC for all sensors) is applied. Conductivities after 10 minutes of signal acquisition in the studied air are considered as characterizing its chemical composition. Discriminant Function Analysis (DFA) and different linear regression techniques (Inverse Least Squares, Principal Components Regression and Partial Least Squares) are applied to find a relation between the sensors signals and the indoor air composition as determined by the gas chromatography. The presented results suggest that the monitoring of aromatics substances in the indoor air by means of a micro-array of metal oxide gas sensors is possible. The array distinguishes polluted and non-polluted air and it can even evaluate the concentration of the benzene and the toluene. [less ▲]

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See detailIdentification of several environmental odours with tin oxide sensor array : three years later
Romain, Anne-Claude ULg; Nicolas, Jacques ULg; Maternova, J.

Poster (2001)

The paper discusses the ability of recognition models to classify malodours in the environment three years after their calibration, with the same sources releasing odours. Two methodologies applicable ... [more ▼]

The paper discusses the ability of recognition models to classify malodours in the environment three years after their calibration, with the same sources releasing odours. Two methodologies applicable either in the lab or in the field are used. The effect of the long term drift of the sensors is highlighted on the results of principal component analysis and of discriminant function analysis. The paper examines also the applicability of some drift counteraction methods proposed in the literature. Handled with some care, a correction based on the drift direction in the principal components subspace should be applicable to the classification of real odorous sources in the field. [less ▲]

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See detailChemometrics methods for the identification and the monitoring of an odour in the environement with an electronic nose
Nicolas, Jacques ULg; Romain, Anne-Claude ULg; Maternova, J.

in Ramirez-Silva, Maria Theresa (Ed.) Sensors and chemometrics (2001)

The purpose of the paper is to briefly review some researches regarding the adaptation of the electronic nose principle to recognise some malodour sources in the environment, if possible directly in the ... [more ▼]

The purpose of the paper is to briefly review some researches regarding the adaptation of the electronic nose principle to recognise some malodour sources in the environment, if possible directly in the field, and to monitor the odour intensity continuously. Research aims at improving the portability and the user-friendliness of the instrument, together with testing what kind of signal may be used to monitor the odour. A laboratory-made electronic nose, constituted of an array of tin-oxide sensors, is used in different configurations. The ambient air is either sampled around environmental sources (landfill, urban waste composting facilities, …), or directly transferred into the sensor chamber in the field. Two main options are considered : firstly, identifying the source of odour in the background and among interfering odours and, secondly, when the malodour is recognised, trying to monitor it continuously in order, for example, to assess the nuisance or to control an odour abatement system. Chemometrics methods are generally used for both purposes. They provide quick answers and allow to evaluate the relationships between variables and between observations at a glance. They are applied on the sensor signals, eventually preprocessed by a suitable algorithm. Non-supervised analyses, such as Principal Component Analysis (PCA), provide basically a performance evaluation of the system during the development phase. On the contrary, supervised analyses, such as Discriminant Analysis (DA), or some Neural Networks algorithms are quite appropriate to make a reliable recognition in real time, when the system is developed. To predict the odour intensity, different techniques are tested : either using only one of the sensor elements, or applying different chemometrics techniques, such as Multilinear Regression (MLR) on the original measured sensor signals, Principal Component Regression (PCR), or Partial Least Squares regression (PLS). The latter seems to be the most adapted model for the intensity prediction. [less ▲]

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See detailFirst trends towards a field odour detector for environmental applications
Nicolas, Jacques ULg; Romain, Anne-Claude ULg; Wiertz, V. et al

in Weimar, Udo (Ed.) Proceedings of ISOEN 99 (1999)

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