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Indexing Odour by using electronic nose

Organized by National Cheng Kung University, 15th - 18th January 2006 at National Cheng Kung University, Taiwan.

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Bibliographic Details
Main Authors: Saiful Azhar, Saad, Mohd Noor, Ahmad, Ali Yeon, Md Shakaff, Suhardy, Daud, Farizul Hafiz, Kasim, Siti Nordiyana, Md. Salim, A.K.M. Shafiqul Islam
Format: Working Paper
Language:English
Published: National Cheng Kung University 2008
Subjects:
Odours
Air > Pollution
Gas detectors
Detectors
Chemical detectors
Olfactometry
Odour control
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/1944
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spelling my.unimap-19442009-04-16T03:32:27Z Indexing Odour by using electronic nose Saiful Azhar, Saad Mohd Noor, Ahmad Ali Yeon, Md Shakaff Suhardy, Daud Farizul Hafiz, Kasim Siti Nordiyana, Md. Salim A.K.M. Shafiqul Islam Odours Air -- Pollution Gas detectors Detectors Chemical detectors Olfactometry Odour control Organized by National Cheng Kung University, 15th - 18th January 2006 at National Cheng Kung University, Taiwan. Odour produced from landfill had become a serious problem in Malaysia as 70% of the complaints received by environmental regulators were about the odour. At present, Malaysia is still developing its odour standard permitted level as for haze and water. Currently, the accepted standard to provide odour concentration is olfactometry which relies on human panels. This method is labour-intensive, expensive and the equipment is bulky, also human panels are fatigue and unable to produced consistence results. Many studies had shown the application of the QCM sensors for odour detection. Among those are detection of organic vapour in the environment detection of odour emission from composting facility, etc. The aim of this work is to see if e-Nose could be used to measure odour concentration. The nose system comprises of an array of mass sensitive sensors (quartz crystal microbalance, QCM) as well as data acquisition and a pattern recognition tool namely principal components analysis (PCA). The performance of the sensor was further investigated using supervised pattern recognition techniques such as discriminate function analysis (DFA). This later data processing technique gives better classification of morning and evening air quality. 2008-09-04T06:17:42Z 2008-09-04T06:17:42Z 2006-01-18 Working Paper http://hdl.handle.net/123456789/1944 en 2nd International Meeting on Microsensors and Microsystems (IMµ2 2006) National Cheng Kung University
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Odours
Air -- Pollution
Gas detectors
Detectors
Chemical detectors
Olfactometry
Odour control
spellingShingle Odours
Air -- Pollution
Gas detectors
Detectors
Chemical detectors
Olfactometry
Odour control
Saiful Azhar, Saad
Mohd Noor, Ahmad
Ali Yeon, Md Shakaff
Suhardy, Daud
Farizul Hafiz, Kasim
Siti Nordiyana, Md. Salim
A.K.M. Shafiqul Islam
Indexing Odour by using electronic nose
description Organized by National Cheng Kung University, 15th - 18th January 2006 at National Cheng Kung University, Taiwan.
format Working Paper
author Saiful Azhar, Saad
Mohd Noor, Ahmad
Ali Yeon, Md Shakaff
Suhardy, Daud
Farizul Hafiz, Kasim
Siti Nordiyana, Md. Salim
A.K.M. Shafiqul Islam
author_facet Saiful Azhar, Saad
Mohd Noor, Ahmad
Ali Yeon, Md Shakaff
Suhardy, Daud
Farizul Hafiz, Kasim
Siti Nordiyana, Md. Salim
A.K.M. Shafiqul Islam
author_sort Saiful Azhar, Saad
title Indexing Odour by using electronic nose
title_short Indexing Odour by using electronic nose
title_full Indexing Odour by using electronic nose
title_fullStr Indexing Odour by using electronic nose
title_full_unstemmed Indexing Odour by using electronic nose
title_sort indexing odour by using electronic nose
publisher National Cheng Kung University
publishDate 2008
url http://dspace.unimap.edu.my/xmlui/handle/123456789/1944
_version_ 1643787500878036992
score 13.214268

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