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Record W2587573263 · doi:10.1515/freq-2016-0205

Radiation Bandwidth Improvement of Electromagnetic Band Gap Cavity Antenna

2017· article· en· W2587573263 on OpenAlexaff
Abdelhalim Chaabane, F. Djahli, Hussein Attia, Tayeb A. Denidni

Bibliographic record

VenueFrequenz · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsAntenna measurementRadiation patternAntenna factorOpticsAntenna efficiencyBandwidth (computing)Antenna gainMicrostrip antennaPhysicsOptoelectronicsAntenna (radio)AcousticsMaterials scienceElectrical engineeringComputer scienceEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Abstract In this paper, an electromagnetic band gap cavity antenna with improved radiation and impedance bandwidths is presented. The proposed antenna is constructed by placing a triple-layer heterogeneous printed-unprinted partially reflective surface (PRS) above a primary aperture-coupled patch antenna. The PRS unit-cell provides a positive gradient reflection phase behavior over the desired frequency range. A prototype antenna is fabricated and measured that highlighted its ability to achieve 3-dB gain bandwidth of about 35.9 %, from 7.93 GHz to 11.4 GHz, with a peak gain of 14.25 dBi at 8.5 GHz. In addition, the impedance bandwidth is 40.32 %, from 7.9 GHz to 11.89 GHz. Thus, the designed antenna outperforms many other competitors for improving the radiation bandwidth of planar antennas with the same presented concept.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 science0.0000.000
Research integrity0.0010.000
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 head0.015
GPT teacher head0.241
Teacher spread0.226 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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