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Record W1979718410 · doi:10.1109/cjece.2003.1426069

Analysis of dielectric-loaded annular slot array antenna

2003· article· en· W1979718410 on OpenAlexaffvenue
Sima Noghanian, L. Shafai

Bibliographic record

VenueCanadian Journal of Electrical and Computer Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsDirectivityAntenna (radio)DielectricSlot antennaComputationBoundary value problemFourier seriesOpticsAcousticsMaterials scienceMathematical analysisPhysicsMathematicsDipole antennaComputer scienceTelecommunicationsAlgorithmOptoelectronics

Abstract

fetched live from OpenAlex

A method is established for the analysis of annular slot array antennas loaded with dielectric layers and fed by either radial waveguide or cavity. The analysis is based on the boundary value method. The Greens functions for each region are obtained, and then the induced magnetic current over the slots is expanded into Fourier series with unknown coefficients. Boundary conditions are applied, and a matrix equation for these unknown coefficients is obtained. For narrow slots the number of unknowns equals the number of annular slots, and an extremely rapid solution is obtained. The far-field formulation is derived using the magnetic current on the dielectric layer. The method is confirmed numerically by comparing the simulation results for sample small antennas with a commercial numerical tool (IE3D), and good agreement is achieved. It is shown that adding the dielectric layers can improve the antenna directivity. In comparison with other methods, the proposed method is very efficient, and its computation efforts depend on the number of annular slots and not the size of the antenna. As an example, for a single-slot antenna the number of unknowns to be determined is only one, while in IE3D it is more than 300.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.679
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.005
GPT teacher head0.160
Teacher spread0.156 · 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

Citations2
Published2003
Admission routes2
Has abstractyes

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