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Record W3127169807 · doi:10.17762/msea.v70i1.6

Mathematical Quad Cross-Stub Stepped Impedance Resonator Application

2021· article· en· W3127169807 on OpenAlexaff
Viviana Lori

Bibliographic record

VenueMathematical Statistician and Engineering Applications · 2021
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsStub (electronics)ResonatorMaterials scienceFractional bandwidthElectrical impedanceMicrostripFabricationBand-pass filterWidebandAcousticsOptoelectronicsElectronic engineeringPhysicsOpticsEngineering

Abstract

fetched live from OpenAlex

This simulation study involved the use of a QC-SSIR (quad cross-tub stepped impedance resonator) to examine the behavior and performance of the MW-BPF (multi-wideband band pass filter). To evaluate the performance of the proposed model, it was compared to the case of the conventional resonator. In the results, MW-BPF was found o exhibit a superior performance in terms of the ease of fabrication, good transmission coefficients, and a wider fractional bandwidth. For the filter structure analysis, this study incorporated the ABCD matrix, with the design of the MW-BPF also based on the FR4 microstrip. The experimental conditions and parameters were set in such a way that for the substrate, tan = 0.0265, thickness = 1.6 mm, and r = 4.4, and thickness h = 1.6 mm. at 2.58GHz, 1.71 GHz, and 0.81 GHz, the proposed QC-SSIR-based MW-BPF achieved transmission coefficients/fractional bandwidths of 1.93dB/13.9%, 1.49dB/18.7%, and 0.60dB/49.3%, respectively. Relative to the filter size reduction, the FQC-SSIR (folded quad cross-tub impedance resonator) was incorporated. The resultant observations indicated a possibility of BPF size reduction up to 46%. Also, the proposed framework was found to yield (at 2.62, 1.80, and 0.82 GHz) 1.76dB/12.5%, 1.21dB/17.7%, and 0.57dB/49.6% transmission coefficient/fractional bandwidths, respectively. It is also worth indicating that the filter employed LTE2600, WCDMA1800, and GSM800.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.899
Threshold uncertainty score1.000

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 head0.239
Teacher spread0.232 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations1
Published2021
Admission routes1
Has abstractyes

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