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Record W2121613936 · doi:10.2528/pierl14091003

A FLEXIBLE BROADBAND ANTENNA AND TRANSMISSION LINE NETWORK FOR A WEARABLE MICROWAVE BREAST CANCER DETECTION SYSTEM

2014· article· en· W2121613936 on OpenAlexfundno aff
Emily Porter, Gregory Walls, Yahe Zhou, Milica Popović, Joshua D. Schwartz

Bibliographic record

VenueProgress In Electromagnetics Research Letters · 2014
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBroadbandWearable computerMicrowaveAntenna (radio)Transmission (telecommunications)Transmission lineBreast cancerComputer scienceTelecommunicationsElectronic engineeringElectrical engineeringEngineeringMedicineCancerEmbedded systemInternal medicine

Abstract

fetched live from OpenAlex

First, we report on the design, simulation and measurement of a 2-4 GHz conformable antenna optimized for skin contact and implemented on a flexible printed circuit for integration into a wearable device. Second, we experimentally verify the suitability of appropriately long (~10 cm) microstrip traces for the wearable system signal distribution network, which features varying radii of curvature. Consequently, the contribution of the here reported work is two-fold. First, the experimental results obtained both with breast phantoms and on-body measurements, demonstrate a return loss below -10 dB in the desired frequency band. Phantom results also show a through-breast transmission coefficient of above -40 dB at the centre frequency of 3 GHz. Second, and essential for signal integrity in our target application, the results show that the longitudinal curvature of such a microstrip does not increase transmission line losses.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.272
Teacher spread0.259 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations15
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueProgress In Electromagnetics Research LettersSame topicWireless Body Area NetworksFrench-language works237,207