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Record W2015216146 · doi:10.1049/iet-cta.2013.0908

Stability of sampled‐data, delayed haptic interaction under passive or active operator

2014· article· en· W2015216146 on OpenAlexaff
Noushin Miandashti, Mahdi Tavakoli

Bibliographic record

VenueIET Control Theory and Applications · 2014
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHaptic technologyControl theory (sociology)Operator (biology)Stability (learning theory)Computer scienceArtificial intelligenceControl (management)ChemistryMachine learning

Abstract

fetched live from OpenAlex

This study studies the absolute stability of a sampled‐data, m ‐user haptic virtual environment (HVE) system based on the discrete‐time circle criterion. Depending on the task being performed by an operator, the passivity of the operator is influenced. The authors provide a framework for the system stability analysis, in which the operator is allowed to exhibit passive or active behaviour. In this study, the well‐known Colgate's stability condition for a 1‐user haptic system with a passive operator is reproduced and then extended to the m ‐user case while allowing each or all of the operators to behave passively or actively. Another extension to Colgate's condition comes by allowing communication delays to exist in the system. Simulations and experiments confirm the validity of the proposed conditions for stability of sampled‐data, delayed m ‐user HVE systems.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score0.321

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 head0.019
GPT teacher head0.263
Teacher spread0.244 · 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 designTheoretical or conceptual
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

Citations8
Published2014
Admission routes1
Has abstractyes

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