Maz Jamilah Masnan
Thumbnail Image
Preferred name
Maz Jamilah Masnan
Official Name
Masnan, Maz Jamilah
Main Affiliation

Research Output

Filters

2 2
2
2
Reset filters

Settings
Now showing 1 - 2 of 2
No Thumbnail Available
Publication

Improved classification of orthosiphon stamineus by data fusion of electronic nose and tongue sensors

2010 , Ammar Zakaria , Ali Yeon Md Shakaff , Abdul Hamid Adom , Mohd Noor Ahmad , Masnan, Maz Jamilah , Abdul Hallis Abdul Aziz , Nazifah Ahmad Fikri , Abu Hassan Abdullah , Latifah Munirah Kamarudin

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.

View
No Thumbnail Available
Publication

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

2010 , Ammar Zakaria , Ali Yeon Md Shakaff , Abdul Hamid Adom , Mohd Noor Ahmad , Masnan, Maz Jamilah , Abdul Hallis Abdul Aziz , Nazifah Ahmad Fikri , Abu Hassan Abdullah , Latifah Munirah Kamarudin

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.

View