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Record W2891339566 · doi:10.7716/aem.v7i4.883

New Compact Microstrip Filters Based on Quasi Fractal Resonator

2018· article· en· W2891339566 on OpenAlexaff
Yaqeen S. Mezaal, Hassan Saleh, Hussam Al‐Saedi

Bibliographic record

VenueAdvanced Electromagnetics · 2018
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBand-pass filterMicrostripPrototype filterElectronic engineeringm-derived filterBand-stop filterFractalAcousticsResonatorBandwidth (computing)Filter (signal processing)BroadbandMaterials scienceLow-pass filterComputer scienceOptoelectronicsPhysicsTelecommunicationsElectrical engineeringEngineeringMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

This paper presents new microstrip devices as single band bandpass and multi band bandstop filters. The proposed filters use slotted patch microstrip resonator based on quasi fractal geometry, simulated by AWR12 software package. Both filters have quasi elliptic frequency response, designed at centre frequency of 2.437 GHz for bandpass filter and at band frequencies of 2.434, 4.032, 4.976 and 5.638 GHz GHz respectively, for multi bandstop filter. All filters are employed using RT/Duroid 6010.8 LM substrate of dielectric constant and 1.27 mm dielectric thickness. Simulation results show that the designed quasi fractal bandpass filter has very narrow fractional bandwidth of 0.38 % which is very rare in microstrip filter design. On the other hand, the projected bandstop filter offers multi narrow rejection bands that is useful in broadband wireless schemes influencing from fixed interferences. Both filters present satisfactory S11 and S21 responses besides smallness properties that stand for interesting features of the newest wireless applications. The simulated and measured frequency responses for both designed filters are in good agreement.

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)0.000
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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.212
Teacher spread0.208 · 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

Citations36
Published2018
Admission routes1
Has abstractyes

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