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Record W2018018900 · doi:10.1109/tmtt.2009.2034310

Quad-mode and dual-mode dielectric resonator filters

2009· article· en· W2018018900 on OpenAlexafffund
Mohammad Memarian, Raafat R. Mansour

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2009
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsResonatorDielectric resonator antennaHelical resonatorDielectric resonatorWaveguide filterFilter (signal processing)DielectricElectronic engineeringMaterials scienceDual modePrototype filterCoupling coefficient of resonatorsOptoelectronicsAcousticsOpticsEngineeringPhysicsElectrical engineeringFilter design

Abstract

fetched live from OpenAlex

This paper introduces for the first time a quad-mode dielectric resonator filter, using a simple cylinder resonator. A four-pole single cavity filter is designed, simulated, and fabricated based on this quadruple mode resonator. Additionally, a new type of dual-mode dielectric resonator filters is introduced, using the same cylindrical resonator cut in half along its axis. Center frequency control, intra/inter/input-coupling mechanisms, tuning, and spurious improvement methods are discussed, showing versatility of the proposed structures to realize different filtering functions and specifications. Measured results are presented for practical filters, employing the proposed quad-mode and dual-mode resonators. The dielectric resonator filters presented in this paper offer a significant size and mass reduction in comparison with conventional dielectric resonator filters. They promise to be useful for both wireless and satellite applications.

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)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.001

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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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

Citations87
Published2009
Admission routes2
Has abstractyes

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