Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors
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2011
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my.unimap-113002011-03-14T05:21:24Z Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors Ammar, Zakaria Ali Yeon, Md. Shakaff, Prof. Dr. Abdul Hamid, Adom, Assoc. Prof. Dr. Mohd Noor, Ahmad Maz Jamilah, Masnan Abdul Hallis, Abd Aziz Nazifah, Ahmad Fikri Abu Hassan, Abdullah Latifah Munirah, Kamarudin aliyeon@unimap.edu.my abdhamid@unimap.edu.my mohdnoor@unimap.edu.my mazjamilah@unimap.edu.my abdulhallis@unimap.edu.my naffe_five@yahoo.com abuhassan@unimap.edu.my munirahkamarudin@gmail.com Data fusion Electronic nose Electronic tongue Linear Discriminant Analysis (LDA) Orthosiphon stamineus Principal Component Analysis (PCA) Link to publisher's homepage at http://www.mdpi.com/ An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together. 2011-03-14T05:21:24Z 2011-03-14T05:21:24Z 2010-09-28 Article Sensors, vol. 10(10), 2010, pages 8782-8796 1424-8220 http://www.mdpi.com/1424-8220/10/10/8782/ http://hdl.handle.net/123456789/11300 en MDPI Publishing |
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English |
| topic |
Data fusion Electronic nose Electronic tongue Linear Discriminant Analysis (LDA) Orthosiphon stamineus Principal Component Analysis (PCA) |
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Data fusion Electronic nose Electronic tongue Linear Discriminant Analysis (LDA) Orthosiphon stamineus Principal Component Analysis (PCA) Ammar, Zakaria Ali Yeon, Md. Shakaff, Prof. Dr. Abdul Hamid, Adom, Assoc. Prof. Dr. Mohd Noor, Ahmad Maz Jamilah, Masnan Abdul Hallis, Abd Aziz Nazifah, Ahmad Fikri Abu Hassan, Abdullah Latifah Munirah, Kamarudin Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors |
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Link to publisher's homepage at http://www.mdpi.com/ |
| author2 |
aliyeon@unimap.edu.my |
| author_facet |
aliyeon@unimap.edu.my Ammar, Zakaria Ali Yeon, Md. Shakaff, Prof. Dr. Abdul Hamid, Adom, Assoc. Prof. Dr. Mohd Noor, Ahmad Maz Jamilah, Masnan Abdul Hallis, Abd Aziz Nazifah, Ahmad Fikri Abu Hassan, Abdullah Latifah Munirah, Kamarudin |
| format |
Article |
| author |
Ammar, Zakaria Ali Yeon, Md. Shakaff, Prof. Dr. Abdul Hamid, Adom, Assoc. Prof. Dr. Mohd Noor, Ahmad Maz Jamilah, Masnan Abdul Hallis, Abd Aziz Nazifah, Ahmad Fikri Abu Hassan, Abdullah Latifah Munirah, Kamarudin |
| author_sort |
Ammar, Zakaria |
| title |
Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors |
| title_short |
Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors |
| title_full |
Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors |
| title_fullStr |
Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors |
| title_full_unstemmed |
Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors |
| title_sort |
improved classification of orthosiphon stamineus by data fusion of electronic nose and tongue sensors |
| publisher |
MDPI Publishing |
| publishDate |
2011 |
| url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/11300 |
| _version_ |
1643790112936427520 |
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13.214268 |