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Record W2290591992 · doi:10.1109/lawp.2015.2457832

SIW Hybrid Feeding Network-Integrated 2-D DRA Array: Simulations and Experiments

2015· article· en· W2290591992 on OpenAlexaff
Wael M. Abdel‐Wahab, Ying Wang, Safieddin Safavi‐Naeini

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2015
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsOntario Tech UniversityUniversity of Waterloo
Fundersnot available
KeywordsReflection coefficientAntenna arrayDielectric resonator antennaBandwidth (computing)Materials scienceExtremely high frequencyAntenna (radio)OpticsResonatorElectrical impedanceDielectricOptoelectronicsPhysicsEngineeringElectrical engineeringTelecommunications

Abstract

fetched live from OpenAlex

Simulation and experimental results of substrate integrated waveguide (SIW)-integrated 2-D dielectric resonator antenna (DRA) array operating at millimeter-wave frequency band are presented. The antenna array consists of 64 elements arranged in 8 ×8. Hybrid feeding network combining series-fed and corporate-fed is used to provide a uniform power distribution over the entire aperture of the array. The antenna array is fabricated and tested. The measured reflection coefficient shows an impedance bandwidth ( S11 ≤ - 10 dB) of 2 GHz and a measured gain of 21.60 dB over the operating frequency band 35-37 GHz. A very good correlation between the measured results and simulated results is observed.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
Threshold uncertainty score0.751

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 head0.018
GPT teacher head0.220
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 designSimulation or modeling
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

Citations31
Published2015
Admission routes1
Has abstractyes

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