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Record W2112271096 · doi:10.1109/tap.2011.2158946

Millimeter-Wave High Radiation Efficiency Planar Waveguide Series-Fed Dielectric Resonator Antenna (DRA) Array: Analysis, Design, and Measurements

2011· article· en· W2112271096 on OpenAlexaff
Wael M. Abdel‐Wahab, Dan Busuioc, Safieddin Safavi‐Naeini

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2011
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOpticsDielectric resonator antennaHFSSRadiation patternAntenna efficiencyPlanar arrayAntenna gainReflection coefficientAntenna (radio)Extremely high frequencyAntenna arrayRadiationMaterials scienceResonatorPhysicsMicrostrip antennaComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

A low cost general architecture for a substrate integrated waveguide (SIW) series-fed dielectric resonator antenna (DRA) array, formed by two different slot polarizations, is proposed. In addition, a novel, simple, and generic transmission line (T.L.) circuit model, along with a fast and generic formulation for the new linear array antenna, is developed. The model can be used for reflection coefficient and radiation pattern (gain) calculations. The experimental data from two linear array modules, operating at the millimeter-wave band, are used to verify the simulated results of HFSS and the proposed model results. The measured radiation pattern for a 4 × 1 SIW-DRA array demonstrates a broadside beam with a radiated gain of 11.70 dB over an operating impedance bandwidth of 4.70%. Moreover, the simulated radiation efficiency is more than 90%.

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)0.001
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.203
Teacher spread0.172 · 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
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

Citations94
Published2011
Admission routes1
Has abstractyes

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