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Record W1991020622 · doi:10.7227/ijmee.35.2.6

Software Demonstration of Disc Cam Mechanisms for Mechanical Engineering Education

2007· article· en· W1991020622 on OpenAlexaff
Mina Hoorfar, Homayoun Najjaran, William L. Cleghorn

Bibliographic record

VenueInternational Journal of Mechanical Engineering Education · 2007
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsUniversity of TorontoUniversity of New BrunswickUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsKinematicsSoftwareComputer scienceEngineering drawingSoftware engineeringEngineeringProgramming language

Abstract

fetched live from OpenAlex

This paper describes a software program for the kinematic analysis and design of disc cam mechanisms. It was mainly developed to enhance student learning in an undergraduate mechanisms course within a mechanical engineering curriculum. The software includes numerous combinations of follower types and motions, and provides graphical representations of the kinematics of the follower. The cam profile may be shown with or without the follower in a single position or animated. The software provides design tips in the form of error and warning messages when the user attempts to enter invalid values of input parameters. The software tool can also be used to design and test complicated cam mechanisms for industrial applications. Two examples are presented that demonstrate some important problems involved in the design of cam mechanisms.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.762
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.293
Teacher spread0.281 · 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.

Study designBench or experimental
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
Published2007
Admission routes1
Has abstractyes

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