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Sensors 2010, 10(10), 8782-8796; doi:10.3390/s101008782
Article

Improved Classification of Orthosiphon stamineus by Data Fusion of Electronic Nose and Tongue Sensors

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Received: 31 July 2010 / Revised: 22 August 2010 / Accepted: 2 September 2010 / Published: 28 September 2010
(This article belongs to the Section Physical Sensors)
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Abstract

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.
Keywords: electronic nose; electronic tongue; data fusion; PCA; LDA; Orthosiphon stamineus electronic nose; electronic tongue; data fusion; PCA; LDA; Orthosiphon stamineus
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Zakaria, A.; Shakaff, A.Y.M.; Adom, A.H.; Ahmad, M.; Masnan, M.J.; Aziz, A.H.A.; Fikri, N.A.; Abdullah, A.H.; Kamarudin, L.M. Improved Classification of Orthosiphon stamineus by Data Fusion of Electronic Nose and Tongue Sensors. Sensors 2010, 10, 8782-8796.

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