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Ultra-Wideband Dielectric Resonator Antenna with Integrated Fabry–Perot Cavity

2023· article· en· W4408717131 on OpenAlexaff
Mohamed Sedigh Bizan, Peyman PourMohammadi, Hassan Naseri, Amjad Iqbal, Tayeb A. Denidni

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité du Québec à Montréal
Fundersnot available
KeywordsFabry–Pérot interferometerDielectric resonator antennaWidebandDielectric resonatorResonatorDielectricMaterials scienceAntenna (radio)OptoelectronicsOpticsAcousticsPhysicsTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

In this paper, a new dielectric resonator antenna is introduced for 5G wireless communication systems at mm-wave bands. The proposed antenna consists of a cylinder dielectric resonator with an integrated Fabry-Perot cavity and is fed using an L-probe to match its characteristic impedance. The antenna is designed so that high efficiency and gain are simultaneously achieved. Using this, approach, the obtained results show an impedance bandwidth of 56.4%, ranging from 25.9 GHz to 46.2 GHz. The antenna provides a peak realized gain of 10.3 dBi at 30 GHz and radiation efficiency of 95% across the entire operating band. The antenna radiation patterns in both the E- and H-planes are stable across the entire operating band, making it a good candidate for 5G applications at mm-wave bands.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.010
GPT teacher head0.198
Teacher spread0.189 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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