Please use this identifier to cite or link to this item: http://dspace2020.uniten.edu.my:8080/handle/123456789/6771
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dc.contributor.authorIsmail, A.F.
dc.contributor.authorMohd Ramli, H.A.
dc.contributor.authorSidek, N.I.
dc.contributor.authorHashim, W.
dc.date.accessioned2017-12-08T10:10:22Z-
dc.date.available2017-12-08T10:10:22Z-
dc.date.issued2012
dc.identifier.urihttp://dspace.uniten.edu.my/jspui/handle/123456789/6771-
dc.description.abstractIn the recent years, microwave Base Stations (BS) are deployed closer and closer to houses and public buildings. The situation has become a reason for growing concerns to the general population. Scientists and researchers worldwide are indeed very concerned about the potential health risks associated with the increasing numbers of BS installation. Small adverse effects on health could have major public health implications. Radio Frequency (RF) is an abstract subject and is not easily understood by most people. The term 'radiation' itself projects fears and to some extent the term Radio Frequency Radiation (RFR), commonly referred as 'electromagnetic (EM) pollution' gives an impression that RFR is hazardous and can cause immediate health impacts. Thus there is a need to develop an RFR prediction tool, where its database contains not only data on BS locations, the service area maps and their respective frequency allocations, but also their implicit radiation levels. A simple prediction tool that is capable of estimating the RFR levels accurately can be rather useful, practical and facilitate the pre-processing measurement steps, especially when there are too many sites to be assessed simultaneously. © 2012 IEEE.
dc.titleDevelopment of Radio Frequency radiation (RFR) prediction tool
item.fulltextNo Fulltext-
item.grantfulltextnone-
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