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Record W109025939 · doi:10.1115/imece2014-37692

Performance Decomposition and Integration of a Five-Degrees-of-Freedom Compliant Hybrid Parallel Micromanipulator

2014· article· en· W109025939 on OpenAlexafffund
Zhen Gao, Dan Zhang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPiezoelectric Actuators and Control
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMicromanipulatorComputer scienceDegrees of freedom (physics and chemistry)VisualizationProcess (computing)DecompositionMacroFinite element methodControl engineeringArtificial intelligenceEngineeringStructural engineering

Abstract

fetched live from OpenAlex

The research and development of parallel manipulators generally has two major streams, i.e. the macro/meso stream and the micro/nano stream, in which the former one has been thoroughly investigated in recent decades, while the latter one still remains many performance related open issues that significantly affect their application potentials in critical situations such as high-precision automated cell manipulation. This research is to develop a novel methodology called performance decomposition and integration for governing the design optimization process of complicated micromanipulator. A new five degrees-of-freedom (DOF) compliant hybrid parallel micromanipulator which is configured with five identical PSS limbs and one constraining UPU limb is proposed as a case study. The performance visualization, finite element analysis, and dimensional optimization are implemented. The proposed methodology is generic and feasible for the design improvement of different kinds of compliant/parallel 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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.290

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)0.0000.000

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 head0.008
GPT teacher head0.204
Teacher spread0.196 · 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 designSimulation or modeling
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

Citations0
Published2014
Admission routes2
Has abstractyes

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