Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Kodogiannis, V.S.a; * | Wadge, E.a | Chountas, P.a | Petrounias, I.b
Affiliations: [a] Mechatronics Group, School of Computer, Science University of Westminster, London, HA1 3TP, UK | [b] School of Informations, University of Manchester, PO Box 88, Manchester M60 1QD, UK
Correspondence: [*] Corresponding author. E-mail: kodogiv@wmin.ac.uk.
Abstract: Sensorial analysis based on the utilisation of human senses, is one of the most important investigation methods in food and chemical analysis. Recently, the use of smell in clinical diagnosis has been rediscovered due to major advances in odour sensing technology and artificial intelligence. An array of gas sensors has been employed to identify in vivo urine samples from patients with suspected uncomplicated UTI who were scheduled for microbiological analysis in a UK Health Laboratory environment. An intelligent model consisting of an odour generation mechanism, rapid volatile delivery and recovery system, and a classifier system based on intelligent techniques has been developed. The implementation of an advanced neural network scheme and the concept of fusion of multiple classifiers dedicated to specific feature parameters have been adopted in this study. The experimental results confirm the validity of the presented methods. This study has shown the potential for early detection of microbial contaminants in urine samples using electronic nose technology.
Keywords: Neural networks, multiple classifiers, electronic noses, microbial analysis
DOI: 10.3233/JCM-2005-5402
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 5, no. 4, pp. 225-241, 2005
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl