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Record W4246329759 · doi:10.32920/ryerson.14657130

Development of micromirror-based laser line generator

2021· preprint· en· W4246329759 on OpenAlexaff
Farzad Hossein Nia

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSurface Roughness and Optical Measurements
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsGenerator (circuit theory)ZemaxLaserOpticsLine (geometry)BrightnessSoftwareComputer sciencePhysicsPower (physics)Mathematics

Abstract

fetched live from OpenAlex

A laser line generator projects a straight line on an object and is widely used for alignment, identification, barcode reading, etc. Conventional laser line generators make use of cylindrical and Powell lenses that convert a laser beam spot into a line. Because of a fixed fan angle, however, the length and brightness of the generated line depends on the working distance between the laser module and object. In this project, using the optical system design software Zemax and engineering CAD software Solidworks, a micromirror based laser line generator is designed and fabricated. The performance of the fabricated micromirror based laser line generator is tested and compared with the performance of a conventional laser line generator. The results show that the length and brightness of image line can be kept constant by the designed generator.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.908

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)0.0010.000

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 head0.045
GPT teacher head0.244
Teacher spread0.199 · 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 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
Published2021
Admission routes1
Has abstractyes

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