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Record W3015452373 · doi:10.1109/access.2020.2986328

Dual-Band High-Gain Planar Corrugated Antennas With Integrated Feeding Structure

2020· article· en· W3015452373 on OpenAlexafffund
Mohammad Mahdi Honari, Kamal Sarabandi, Pedram Mousavi

Bibliographic record

VenueIEEE Access · 2020
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBroadsideMulti-band devicePlanarAntenna (radio)Center frequencyOpticsAcousticsPhysicsComputer scienceTelecommunicationsBand-pass filter

Abstract

fetched live from OpenAlex

In this paper, a dual-band high-gain planar corrugated antenna is presented for applications in space and satellite communications. An analytic method based on the unit-cell analysis of a corrugated structure is presented to estimate the resonant frequency of the corrugated antenna where the maximum broadside gain happens. Therefore, the design of periodic corrugated antenna structures, which is very time-consuming due to the large size of the structure, is reduced to the design of a unit-cell of the structure which is very fast. A 2D corrugated (bull's-eye) antenna structure is then parametrically studied to find the parameters which affect the resonant frequency of the corrugated structures. A dual-band bull's-eye antenna with an integrated feeder structure at center is designed for the center frequencies of 9.7 GHz and 13.85 GHz. The dual-band operation is enabled using two different corrugations realized on two laminate boards. A prototype is fabricated and measured maximum broadside realized gains of 15. 8 and 17.5 dBi are achieved for the first and second bands, respectively.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score0.759

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 head0.017
GPT teacher head0.219
Teacher spread0.202 · 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
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

Citations5
Published2020
Admission routes2
Has abstractyes

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