Abstract
This project investigates the effectiveness of anti-radiation shield in reducing mobile phone emissions using resonant field imaging system (RFI) and artificial neural network (ANN). The RFI frequency counter was used to capture the human frequency of 30 students including male and female students before and after using mobile phone with and without the anti-radiation shield. ANN was then used to further classify between samples using the mobile phone; with and without the anti-radiation shield. Based on the results presented, it can be concluded that the anti-radiation shield electromagnetic wave is effective in filtering off the harmful electromagnetic waves emitted from the ear piece of mobile phone. It is also observed that classification of samples with and without the anti-radiation shield is possible using the characteristics of human bioenergy.
Metadata
Item Type: | Thesis (Degree) |
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Creators: | Creators Email / ID Num. A. Rahman, Azizah UNSPECIFIED |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Abdul Rahman, Husna UNSPECIFIED |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering |
Programme: | Bachelor of Electrical Engineering (lions.) |
Keywords: | anti radiation, mobile phone, ANN |
Date: | 2009 |
URI: | https://ir.uitm.edu.my/id/eprint/81510 |
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