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Record W2972855835

Millimeter-Wave Dielectric Resonator Antenna With Enhanced Gain Using Ridge-Gap Waveguide

2019· article· en· W2972855835 on OpenAlexaff
Mohamad Mantash, Zhenjiang Zhao, Huan Li, Tayeb A. Denidni

Bibliographic record

VenueEuropean Conference on Antennas and Propagation · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsDielectric resonator antennaAntenna gainExtremely high frequencyAntenna efficiencyDielectric resonatorDielectricBandwidth (computing)Materials scienceAntenna measurementResonatorOptoelectronicsOpticsAntenna (radio)Electrical engineeringRadiation patternPhysicsTelecommunicationsComputer scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

This paper proposes a dielectric resonator antenna (DRA) with ridge-gap waveguide (RGW) feeding, that operates at 30.24 GHz. The RGW presents very low losses rendering high gain and high efficiency to the antenna. To demonstrate the validity of the proposed structure, simulations are performed and they show a bandwidth of 3.5 GHz, high realized gain of 9.76 dBi, total efficiency of 95.17% and side-lobe level of -13 dB at 30.24 GHz. From the results presented, the proposed dielectric resonator antenna can be used for different applications starting from commercial, up to important defense needs, especially for 5G wireless 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.028
GPT teacher head0.214
Teacher spread0.185 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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