Relaxation Frequency and Relaxation Time Estimation for Phantom Modeling by Proposed Fitting Linear Models
This study aims to investigate the effect of quantity of sugar to the relaxation time needed for a mixture to accomplish steady state. Fitting linear models were proposed for fitting and extrapolating the incomplete permittivity graph due to the lacking of Vector Network Analyzer (VNA) machine unabl...
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my.unimas.ir.458952024-08-30T02:49:42Z http://ir.unimas.my/id/eprint/45895/ Relaxation Frequency and Relaxation Time Estimation for Phantom Modeling by Proposed Fitting Linear Models Chew, Kim Mey Rubita, Sudirman Norhudah, Seman Yong, Ching Yee QA75 Electronic computers. Computer science This study aims to investigate the effect of quantity of sugar to the relaxation time needed for a mixture to accomplish steady state. Fitting linear models were proposed for fitting and extrapolating the incomplete permittivity graph due to the lacking of Vector Network Analyzer (VNA) machine unable to operate at frequency higher than 20GHz. The proposed models gave an adequate internal consistency of relaxation time calculation for the four mixtures. Result shows that the quantity of element sugar is the main reason of affecting the permittivity and relaxation time of the mixture. This findings enable contribute to related field researchers due to the effect of sugar that may influence the relaxation time for a mixture model. 2013-04-15 Proceeding PeerReviewed text en http://ir.unimas.my/id/eprint/45895/1/P10.%20Relaxation%20Frequency%20and%20Relaxation%20Time%20Estimation%20for%20Phantom%20Modeling%20by%20Proposed%20Fitting%20Linear%20Models%20%28IEEE%29.pdf Chew, Kim Mey and Rubita, Sudirman and Norhudah, Seman and Yong, Ching Yee (2013) Relaxation Frequency and Relaxation Time Estimation for Phantom Modeling by Proposed Fitting Linear Models. In: 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, 17-19 December 2012, Langkawi, Malaysia. https://ieeexplore.ieee.org/document/6498180 |
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QA75 Electronic computers. Computer science Chew, Kim Mey Rubita, Sudirman Norhudah, Seman Yong, Ching Yee Relaxation Frequency and Relaxation Time Estimation for Phantom Modeling by Proposed Fitting Linear Models |
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This study aims to investigate the effect of quantity of sugar to the relaxation time needed for a mixture to accomplish steady state. Fitting linear models were proposed for fitting and extrapolating the incomplete permittivity graph due to the lacking of Vector Network Analyzer (VNA) machine unable to operate at frequency higher than 20GHz. The proposed models gave an adequate internal consistency of relaxation time calculation for the four mixtures. Result shows that the quantity of element sugar is the main reason of affecting the permittivity and relaxation time of the mixture. This findings enable contribute to related field researchers due to the effect of sugar that may influence the relaxation time for a mixture model. |
format |
Proceeding |
author |
Chew, Kim Mey Rubita, Sudirman Norhudah, Seman Yong, Ching Yee |
author_facet |
Chew, Kim Mey Rubita, Sudirman Norhudah, Seman Yong, Ching Yee |
author_sort |
Chew, Kim Mey |
title |
Relaxation Frequency and Relaxation Time Estimation for Phantom Modeling by Proposed Fitting Linear Models |
title_short |
Relaxation Frequency and Relaxation Time Estimation for Phantom Modeling by Proposed Fitting Linear Models |
title_full |
Relaxation Frequency and Relaxation Time Estimation for Phantom Modeling by Proposed Fitting Linear Models |
title_fullStr |
Relaxation Frequency and Relaxation Time Estimation for Phantom Modeling by Proposed Fitting Linear Models |
title_full_unstemmed |
Relaxation Frequency and Relaxation Time Estimation for Phantom Modeling by Proposed Fitting Linear Models |
title_sort |
relaxation frequency and relaxation time estimation for phantom modeling by proposed fitting linear models |
publishDate |
2013 |
url |
http://ir.unimas.my/id/eprint/45895/1/P10.%20Relaxation%20Frequency%20and%20Relaxation%20Time%20Estimation%20for%20Phantom%20Modeling%20by%20Proposed%20Fitting%20Linear%20Models%20%28IEEE%29.pdf http://ir.unimas.my/id/eprint/45895/ https://ieeexplore.ieee.org/document/6498180 |
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13.19449 |