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Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors
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Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors
Journal
Sensors
ISSN
14248220
Date Issued
2010-10-01
Author(s)
Ammar Zakaria
Universiti Malaysia Perlis
Ali Yeon Md Shakaff
Universiti Malaysia Perlis
Abdul Hamid Adom
Universiti Malaysia Perlis
Mohd Noor Ahmad
Maz Jamilah Masnan
Institute of Engineering Mathematics
Abdul Hallis Abdul Aziz
Universiti Malaysia Perlis
Fikri N.
Abu Hassan Abdullah
Universiti Malaysia Perlis
Latifah Munirah Kamarudin
Universiti Malaysia Perlis
DOI
10.3390/s101008782
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. © 2010 by the authors.
Subjects
Data fusion | Electro...
File(s)
Research repository notification.pdf (4.4 MB)
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4
Acquisition Date
Nov 19, 2024
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