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Record W2003557253 · doi:10.1117/12.684717

A micro-optical electromechanical system (MOEMS) for high-precision displacement sensor design using ring resonator array

2006· article· en· W2003557253 on OpenAlexaff
Ali Rostami, Ashkan Ghanbari, Farrokh Janabi‐Sharifi

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsResonatorDisplacement (psychology)Ring (chemistry)Split-ring resonatorOpticsSensitivity (control systems)Transfer functionSystem of measurementOptical ring resonatorsRefractive indexMaterials scienceAcousticsPhysicsElectronic engineeringEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

An efficient method for high precision displacement measurement based on micro scale ring resonator and MOEMS is presented. The proposed structure can be used as discrete and integrated sensor in engineering applications. Photo-elastic effect is used to convert the physical displacement to the index of refraction variation in the ring resonator array. Analytical relation for description of system transfer function is derived. Single and multiple ring resonators are examined for increase of the system sensitivity. It is shown that an array of multiple ring resonators (array) is better than single ring case. Effects of optical and geometrical parameters of the proposed structure on sensitivity are studied.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.220
Teacher spread0.209 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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