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Record W2102918418 · doi:10.2528/pier04062901

ON IMPROVING IMPEDANCE MATCHING OF A CPW FED LOW PERMITTIVITY DIELECTRIC RESONATOR ANTENNA

2005· article· en· W2102918418 on OpenAlexaff
Qinjiang Rao, Tayeb A. Denidni, A. Sebak, R.H. Johnston

Bibliographic record

VenueElectromagnetic waves · 2005
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of CalgaryConcordia UniversityInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsCoplanar waveguideImpedance matchingMaterials scienceAntenna (radio)Dielectric resonator antennaPermittivityElectrical impedanceOptoelectronicsResonatorDielectric resonatorDielectricAcousticsOpticsComputer scienceElectrical engineeringPhysicsEngineeringTelecommunicationsMicrowave

Abstract

fetched live from OpenAlex

In this paper, a new coplanar waveguide (CPW) feed structure is proposed to improve impedance matching of lowpermittivity dielectric resonator antennas (LPDRAs).The structure is studied experimentally for a two element-rectangular LPDRA array.In the proposed structure, a horizontal strip is centrally connected at the center strip of the CPW and symmetrically added to a coplanar rectangular coupled slot.The dielectric radiators are fed by the CPW through the slot.Based on the above design concept, several antenna prototypes have been successfully designed, fabricated and tested.The measured results show that the proposed antenna exhibits unique and attractive features in terms of impedance matching, gain and the realization of an array.

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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.004
GPT teacher head0.191
Teacher spread0.188 · 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
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

Citations30
Published2005
Admission routes1
Has abstractyes

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