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Slot Antenna Array with Compact Feed based on a Substrate Integrated Fabry-Perot Cavity

2023· article· en· W4397000717 on OpenAlexaff
Zahra Tavasolisirat, Bilel Mnasri, Alireza Ghayekhloo, Halim Boutayeb, Larbi Talbi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsMicrostripAntenna (radio)Coplanar waveguideSlot antennaFabry–Pérot interferometerImpedance matchingOptoelectronicsPrinted circuit boardAntenna arrayMaterials scienceMicrostrip antennaOpticsElectrical impedanceAcousticsElectronic engineeringElectrical engineeringWavelengthComputer sciencePhysicsEngineeringTelecommunicationsMicrowave

Abstract

fetched live from OpenAlex

This work presents a new technique for designing the feeding circuit of a slot antenna array. The radiating slots are arrayed on one side of a single layer printed circuit board. The array is excited via a compact substrate integrated Fabry-Perot cavity (FPC). At the resonance of the cavity, the outgoing field is quasi-uniform and permits a transverse electromagnetic traveling-wave mode through the array at 8 GHz frequency. The FPC is fed by a microstrip line using a transition made of a metallic via and a coplanar-waveguide (CPW) line. Based on this design principle, the array is optimized. This design offers a simplified and smaller feeding circuit than conventional antennas that use multiple dividers or combiners. Simulated results validate the proposed approach. These results illustrate acceptable impedance matching, and an 18 dB gain. This technique demonstrates a feasibility step in antenna engineering.

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 score0.511
Threshold uncertainty score0.740

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.230
Teacher spread0.210 · 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
Published2023
Admission routes1
Has abstractyes

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