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Record W2166910565 · doi:10.1109/aero.2001.931258

Modeling a complex antenna on a handheld telephone close to human tissue

2002· article· en· W2166910565 on OpenAlexaff
K. Caputa, M.A. Stuchly

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHandsetAntenna (radio)Finite-difference time-domain methodHuman headComputer scienceAcousticsRadiation patternElectronic engineeringAntenna measurementElectrical impedanceDipole antennaElectrical engineeringEngineeringOpticsTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

Design-development and performance evaluation of antennas on handheld telephones can be done experimentally or numerically. Numerical modeling approach or a combination of experiment and numerical modeling, offer many advantages compared with purely experimental approach, which has been often used till now. However, modeling poses many challenges and in order to be considered reliable has to be verified. In this work, modeling of an antenna consisting of two helices is verified by a comparison with measurements made in the laboratory of the handset manufacturer, and by use of two different computer codes. The numerical method used in this investigation is the finite difference time domain (FDTD). A comparison of the measured (in manufacturer's laboratory) electric and magnetic field in four planes at distances 1-4 cm from the antenna with the computed values shows agreement within 15% (which corresponds to the uncertainty in measurements). This agreement is for two operational positions of the antenna in free space. Performance of the handset antenna in the vicinity of the user's head is evaluated. Investigations include the input impedance, far-field radiation pattern and power deposited in the human tissue. The influences of the ear shape and various positions of the handset with respect to the user's head have been evaluated.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.246
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

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