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Record W2147580486 · doi:10.1109/tmech.2010.2057440

A Nonlinear Program for Angular-Velocity Estimation From Centripetal-Acceleration Measurements

2010· article· en· W2147580486 on OpenAlexaff
Philippe Cardou, Guillaume Fournier, Philippe Gagnon

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2010
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAccelerometerCentripetal forceGyroscopeAngular accelerationAccelerationInertial measurement unitAngular velocityRigid bodyInertial frame of referenceNonlinear systemComputer sciencePhysicsControl theory (sociology)AcousticsEngineeringMechanicsClassical mechanicsAerospace engineeringComputer visionArtificial intelligence

Abstract

fetched live from OpenAlex

Measuring the trajectory of a rigid body in space is commonly done using an inertial measurement unit composed of one triaxial accelerometer and one triaxial gyroscope. When the rigid body undergoes high accelerations, it is often preferable to resort to an array of accelerometers rather than the traditional accelerometer-gyroscope combination, an approach that is now common in crashworthiness and other biomechanics applications. In this paper, we present an algorithm for the estimation of the rigid-body angular velocity from the centripetal components of the accelerations measured by the array of accelerometers. The proposed algorithm and the others available in the literature were benchmarked using the accelerometer array octahedral constellation of twelve accelerometers. In the reported testing conditions, the proposed method is slightly more robust than any other based on centripetal-acceleration measurements.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.738
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.039
GPT teacher head0.316
Teacher spread0.277 · 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
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

Citations22
Published2010
Admission routes1
Has abstractyes

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