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Record W2891869238 · doi:10.1109/tap.2018.2869228

2-D Scanning Magnetoelectric Dipole Antenna Array Fed by RGW Butler Matrix

2018· article· en· W2891869238 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2018
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia University
Fundersnot available
KeywordsBandwidth (computing)Dipole antennaRadiation patternOpticsDipoleBroadsidePhysicsComputer scienceAntenna (radio)Telecommunications

Abstract

fetched live from OpenAlex

In this paper, a 2-D scanning magnetoelectric (ME) dipole antenna array fed by printed ridge gap waveguide (PRGW) Butler matrix is proposed. The ME dipole antenna is designed to achieve a bandwidth wider than 20% at 30 GHz and stable gain of 6.5 ± 0.8 dB over the operating frequency bandwidth. A 4 × 4 planar PRGW Butler matrix is designed and constructed using a four PRGW hybrid couplers having a wide bandwidth performance. The overall performance of the Butler matrix exhibits about 5° phase error over the operating frequency bandwidth. The integration of ME dipole antennas with the designed Butler matrix results in four fixed beams, one in each quadrant at an elevation angle of 35° from the broadside to the array axis. The proposed passive beam switching network (BSN) has a wide bandwidth of 20% with radiation efficiency higher than 84% over the operating bandwidth. The proposed BSN shows a stable radiation pattern with a stable gain of 10.3 ± 0.2 dB, where the sidelobe level is less than -15 dB over the whole operating frequency band. The fabricated prototype of the proposed BSN is tested, where the measured and simulated results show an excellent agreement.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score0.783

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 head0.007
GPT teacher head0.212
Teacher spread0.205 · 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