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Record W4302282759 · doi:10.32920/ryerson.14668443.v1

FPCB Actuator Driven Micromirror Based Availability Indicator and Laser Pattern Pointer

2022· preprint· en· W4302282759 on OpenAlexaff
Hui Zuo

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsLaser pointerActuatorLaserMicroelectromechanical systemsOpticsComputer scienceMaterials scienceOptoelectronicsPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

The thesis presents a FPCB (Flexible Printed Circuit Board) actuator driven micromirror and the laser pattern generating technology for availability indicator and laser pattern pointer. The FPCB micromirror consists of a FPCB electrostatic parallel plate actuator and a bonded silicon mirror plate. It has the advantages of much larger aperture size, higher surface quality and lower cost than conventional MEMs micromirrors. The FPCB micromirror resonates at its first bending mode. Two FPCB micromirrors are positioned orthogonally to reflect a laser beam. By controlling the vibration frequency and magnitude of these two micromirrors, laser patterns of rotating ellipse or static circle, horizontal or vertical line can be generated and projected to a remote surface, e.g., a translucent or a presentation screen. Based on the FPCB micromirror, an availability indicator is developed, which can solve the wiring problem plaguing existing availability indicators. A laser pattern pointer is also developed which has much better visibility than conventional laser pointers with highlighting functions.

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)0.001
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.225
Teacher spread0.212 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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