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Record W3213058712 · doi:10.1049/ell2.12348

Wearable Metasurface Antenna based on Electrically‐small Ring Resonators for WBAN Applications

2021· article· en· W3213058712 on OpenAlexaff
Youcef Braham Chaouche, Mourad Nedil, Melad M. Olaimat, Mohamed El Badawe, Omar M. Ramahi

Bibliographic record

VenueElectronics Letters · 2021
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueUniversity of Waterloo
Fundersnot available
KeywordsWearable computerSplit-ring resonatorResonatorAntenna (radio)Wearable technologyMetamaterialElectrical engineeringOptoelectronicsBody area networkRing (chemistry)Materials scienceWirelessElectronic engineeringComputer scienceTelecommunicationsEngineeringEmbedded system

Abstract

fetched live from OpenAlex

Abstract This letter proposes a novel wearable metasurface antenna (MSA) based on electric ring resonators (ERR) for 5.8 GHz wireless body area network (WBAN) applications. All substrates of the proposed design are made from the semi‐flexible Rogers RT5880 material. To achieve size miniaturization, 6 × 8 ERR elements are placed on a flat surface connected through a corporate‐feed network. The total dimensions of the proposed MSA are 120 × 90 × 1.574 mm 3 (2.2 λ 0 × 1.69 λ 0 × 0.029 λ 0 ). Furthermore, an average efficiency of 79.9%, and a peak gain of 12.82 dBi with a stable radiation pattern have been realized in the operating band. The performance of the proposed MSA is analyzed in close proximity to the human body tissue. The experimental results show good agreement with the numerical data. With all these features, the proposed design is a good candidate for wearable WBAN applications.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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 teacher head, not a consensus.

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

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

Citations12
Published2021
Admission routes1
Has abstractyes

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