Evaluation of PCA in herbs identification

Many of the existing herbs species on the earth are still unknown. Each herb species has unique odor which differs from each other. This odor parameter is used to differentiate the type of herbs species by using gas sensor array. The response of electrical signal is generated when the gas sensor arr...

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Main Authors: Mohamad Radzi, Nur Fadzilah, Che Soh, Azura, Mohamad Yusof, Umi Kalsom, Ishak, Asnor Juraiza, Hassan, Mohd Khair, Ahmad, Siti Anom, Khamis, Shamsul
Format: Conference or Workshop Item
Language:English
Published: Faculty of Computer Science and Information Technology, Universiti Putra Malaysia 2015
Online Access:http://psasir.upm.edu.my/id/eprint/77134/
http://psasir.upm.edu.my/id/eprint/77134/1/saes2015-7.pdf
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author Mohamad Radzi, Nur Fadzilah
Che Soh, Azura
Mohamad Yusof, Umi Kalsom
Ishak, Asnor Juraiza
Hassan, Mohd Khair
Ahmad, Siti Anom
Khamis, Shamsul
author_facet Mohamad Radzi, Nur Fadzilah
Che Soh, Azura
Mohamad Yusof, Umi Kalsom
Ishak, Asnor Juraiza
Hassan, Mohd Khair
Ahmad, Siti Anom
Khamis, Shamsul
author_sort Mohamad Radzi, Nur Fadzilah
building UPM Institutional Repository
collection Online Access
description Many of the existing herbs species on the earth are still unknown. Each herb species has unique odor which differs from each other. This odor parameter is used to differentiate the type of herbs species by using gas sensor array. The response of electrical signal is generated when the gas sensor array detect the odor of herb species. This paper presents a pattern analysis of electrical signal data by using principle component analysis method. 4 different herb species with same group family (Family Lauraceae) were investigated. The result shows the discrimination between herb species is possible.
first_indexed 2025-11-15T12:09:05Z
format Conference or Workshop Item
id upm-77134
institution Universiti Putra Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T12:09:05Z
publishDate 2015
publisher Faculty of Computer Science and Information Technology, Universiti Putra Malaysia
recordtype eprints
repository_type Digital Repository
spelling upm-771342020-03-03T10:44:01Z http://psasir.upm.edu.my/id/eprint/77134/ Evaluation of PCA in herbs identification Mohamad Radzi, Nur Fadzilah Che Soh, Azura Mohamad Yusof, Umi Kalsom Ishak, Asnor Juraiza Hassan, Mohd Khair Ahmad, Siti Anom Khamis, Shamsul Many of the existing herbs species on the earth are still unknown. Each herb species has unique odor which differs from each other. This odor parameter is used to differentiate the type of herbs species by using gas sensor array. The response of electrical signal is generated when the gas sensor array detect the odor of herb species. This paper presents a pattern analysis of electrical signal data by using principle component analysis method. 4 different herb species with same group family (Family Lauraceae) were investigated. The result shows the discrimination between herb species is possible. Faculty of Computer Science and Information Technology, Universiti Putra Malaysia 2015 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/77134/1/saes2015-7.pdf Mohamad Radzi, Nur Fadzilah and Che Soh, Azura and Mohamad Yusof, Umi Kalsom and Ishak, Asnor Juraiza and Hassan, Mohd Khair and Ahmad, Siti Anom and Khamis, Shamsul (2015) Evaluation of PCA in herbs identification. In: 3rd International Symposium on Applied Engineering and Sciences (SAES2015), 23-24 Nov. 2015, Universiti Putra Malaysia. (pp. 15-18).
spellingShingle Mohamad Radzi, Nur Fadzilah
Che Soh, Azura
Mohamad Yusof, Umi Kalsom
Ishak, Asnor Juraiza
Hassan, Mohd Khair
Ahmad, Siti Anom
Khamis, Shamsul
Evaluation of PCA in herbs identification
title Evaluation of PCA in herbs identification
title_full Evaluation of PCA in herbs identification
title_fullStr Evaluation of PCA in herbs identification
title_full_unstemmed Evaluation of PCA in herbs identification
title_short Evaluation of PCA in herbs identification
title_sort evaluation of pca in herbs identification
url http://psasir.upm.edu.my/id/eprint/77134/
http://psasir.upm.edu.my/id/eprint/77134/1/saes2015-7.pdf