FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386465731> ?p ?o ?g. }

• W4386465731 endingPage "18" @default.
• W4386465731 startingPage "1" @default.
• W4386465731 abstract "Human-Like digital models have been around for quite some time. They significantly contributed to the increase of the accuracy of the whole-body-average specific absorption rate estimations. However, the anatomical and morphological diversity between human beings has not yet been embraced by the actual anthropomorphic models for several reasons such as financial costs, excessive exposure of volunteers to electromagnetic waves, and the required number of technical experts needed to build one voxelized model. Recently, machine learning has been used to reduce the complexity of certain tasks. Yet, at least, having an anthropomorphic model per nation is still far away to achieve. To reduce the building cost of new human-like models, we build on the success of anthropomorphic models and machine learning to derive mathematical equations that make it possible to predict the Whole-body-average SAR from low frequencies up to twice the resonance frequency without any cost and excessive electromagnetic exposure of new volunteers. The completely new machine learning based equations are applicable for any age, ethnic group, and for both genders. They depend only on the human body’s morphological (height and weight) and anatomical parameters (tissue weights). In this work, we first address the whole-body-average SAR peak and we present a set of two estimators. In second, we show that the resonance frequency is not only a function of the height of the human body, to end up with a third estimation for the resonance frequency. These completely new estimators are finally combined into a novel function that links the whole-body-average SAR to the frequency. It shows the accurate prediction for low frequencies (10 MHz) up to twice the resonance frequency. The derived estimators for the maximum WBASAR and the resonance frequencies showed better results for low frequency exposure." @default.
• W4386465731 created "2023-09-06" @default.
• W4386465731 creator A5015545213 @default.
• W4386465731 creator A5055158293 @default.
• W4386465731 creator A5066655985 @default.
• W4386465731 creator A5087448476 @default.
• W4386465731 date "2023-06-21" @default.
• W4386465731 modified "2023-09-27" @default.
• W4386465731 title "Modeling of the interaction between human body and electromagnetic waves near resonance using machine learning" @default.
• W4386465731 cites W1203341937 @default.
• W4386465731 cites W1509358020 @default.
• W4386465731 cites W1933505140 @default.
• W4386465731 cites W1978330980 @default.
• W4386465731 cites W1990433578 @default.
• W4386465731 cites W1994943748 @default.
• W4386465731 cites W2004473797 @default.
• W4386465731 cites W2006268511 @default.
• W4386465731 cites W2013399599 @default.
• W4386465731 cites W2014529612 @default.
• W4386465731 cites W2020439550 @default.
• W4386465731 cites W2034486907 @default.
• W4386465731 cites W2057952087 @default.
• W4386465731 cites W2062195888 @default.
• W4386465731 cites W2062975053 @default.
• W4386465731 cites W2106649881 @default.
• W4386465731 cites W2129623827 @default.
• W4386465731 cites W2140796340 @default.
• W4386465731 cites W2162501626 @default.
• W4386465731 cites W2170142412 @default.
• W4386465731 cites W2171847126 @default.
• W4386465731 cites W2791545016 @default.
• W4386465731 cites W2932579789 @default.
• W4386465731 cites W2963087265 @default.
• W4386465731 cites W2972491207 @default.
• W4386465731 cites W2996387548 @default.
• W4386465731 cites W3038119599 @default.
• W4386465731 cites W3108446452 @default.
• W4386465731 cites W3125238779 @default.
• W4386465731 cites W3202198480 @default.
• W4386465731 cites W4226046070 @default.
• W4386465731 doi "https://doi.org/10.3233/jae-230025" @default.
• W4386465731 hasPublicationYear "2023" @default.
• W4386465731 type Work @default.
• W4386465731 citedByCount "0" @default.
• W4386465731 crossrefType "journal-article" @default.
• W4386465731 hasAuthorship W4386465731A5015545213 @default.
• W4386465731 hasAuthorship W4386465731A5055158293 @default.
• W4386465731 hasAuthorship W4386465731A5066655985 @default.
• W4386465731 hasAuthorship W4386465731A5087448476 @default.
• W4386465731 hasConcept C105795698 @default.
• W4386465731 hasConcept C109214941 @default.
• W4386465731 hasConcept C11413529 @default.
• W4386465731 hasConcept C119857082 @default.
• W4386465731 hasConcept C121332964 @default.
• W4386465731 hasConcept C139210041 @default.
• W4386465731 hasConcept C14036430 @default.
• W4386465731 hasConcept C154945302 @default.
• W4386465731 hasConcept C177264268 @default.
• W4386465731 hasConcept C185429906 @default.
• W4386465731 hasConcept C199360897 @default.
• W4386465731 hasConcept C2781089380 @default.
• W4386465731 hasConcept C33923547 @default.
• W4386465731 hasConcept C41008148 @default.
• W4386465731 hasConcept C78458016 @default.
• W4386465731 hasConcept C86803240 @default.
• W4386465731 hasConceptScore W4386465731C105795698 @default.
• W4386465731 hasConceptScore W4386465731C109214941 @default.
• W4386465731 hasConceptScore W4386465731C11413529 @default.
• W4386465731 hasConceptScore W4386465731C119857082 @default.
• W4386465731 hasConceptScore W4386465731C121332964 @default.
• W4386465731 hasConceptScore W4386465731C139210041 @default.
• W4386465731 hasConceptScore W4386465731C14036430 @default.
• W4386465731 hasConceptScore W4386465731C154945302 @default.
• W4386465731 hasConceptScore W4386465731C177264268 @default.
• W4386465731 hasConceptScore W4386465731C185429906 @default.
• W4386465731 hasConceptScore W4386465731C199360897 @default.
• W4386465731 hasConceptScore W4386465731C2781089380 @default.
• W4386465731 hasConceptScore W4386465731C33923547 @default.
• W4386465731 hasConceptScore W4386465731C41008148 @default.
• W4386465731 hasConceptScore W4386465731C78458016 @default.
• W4386465731 hasConceptScore W4386465731C86803240 @default.
• W4386465731 hasLocation W43864657311 @default.
• W4386465731 hasOpenAccess W4386465731 @default.
• W4386465731 hasPrimaryLocation W43864657311 @default.
• W4386465731 hasRelatedWork W2961085424 @default.
• W4386465731 hasRelatedWork W3046775127 @default.
• W4386465731 hasRelatedWork W3170094116 @default.
• W4386465731 hasRelatedWork W4205958290 @default.
• W4386465731 hasRelatedWork W4285260836 @default.
• W4386465731 hasRelatedWork W4286629047 @default.
• W4386465731 hasRelatedWork W4306321456 @default.
• W4386465731 hasRelatedWork W4306674287 @default.
• W4386465731 hasRelatedWork W4386462264 @default.
• W4386465731 hasRelatedWork W4224009465 @default.
• W4386465731 isParatext "false" @default.
• W4386465731 isRetracted "false" @default.
• W4386465731 workType "article" @default.