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Record W4234161371 · doi:10.17683/ijomam/issue7.11

WIDEBAND BANDPASS FILTER DESIGN BASED ON RF-MEMS TECHNOLOGY

2020· article· en· W4234161371 on OpenAlexaff
Syed M. Sifat, Raj Savaj, Ion Stiharu, Ahmed A. Kishk

Bibliographic record

VenueInternational Journal of Mechatronics and Applied Mechanics · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia University
Fundersnot available
KeywordsBand-pass filterWidebandElectronic engineeringMicroelectromechanical systemsComputer scienceEngineeringElectrical engineeringMaterials scienceOptoelectronics

Abstract

fetched live from OpenAlex

In this paper, we shall present the design steps and analyze the performance of a wideband band pass filter based on RF MEMS technology. MEMS technology enables very accurate features, which enables the repeatability of the filter. The filter is configured as a parallel ledge coupled five-pole micro strip wideband band pass filter. The concept consists of using precisely sized cantilever beams to excite the filters, which that will act as a switch to feed the filter. The bimetallic switch uses a cantilever beam to perform the deflection based on temperature rise. The filter part is designed using CST Microwave Studio (Frequency Domain Solver), and the cantilever is amiss designee dosing AUTOCAD.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.978
Threshold uncertainty score0.629

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 head0.012
GPT teacher head0.200
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2020
Admission routes1
Has abstractyes

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