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Record W2176668561 · doi:10.1109/whc.2005.95

Motion Synchronization in Virtual Environments with Shared Haptics and Large Time Delays

2005· preprint· en· W2176668561 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsArtificial Intelligence in Medicine (Canada)
FundersKorea Science and Engineering Foundation
KeywordsSynchronization (alternating current)Computer scienceHaptic technologyControl theory (sociology)Controller (irrigation)Focus (optics)Stability (learning theory)Scheme (mathematics)Consistency (knowledge bases)Feedback controllerControl (management)SimulationMathematicsComputer networkArtificial intelligence

Abstract

fetched live from OpenAlex

This paper deals with a synchronization scheme to achieve a high level of consistency in peer-to-peer based virtual environments (VEs) for shared haptics with large time delays. We mainly focus on the VEs with dynamic objects that show physically realistic behaviors. The synchronization scheme utilizes an advanced feedback controller to compensate for the state error between geographically separated sites. Using feedback control theory of time delay systems, the controller is shown to result in closed loop stability and robust to perturbations in the time delay. The maximum allowable delay is determined using stability analysis, which indicates the allowable bound on the communication delay for the system.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.822
Threshold uncertainty score0.698

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 head0.005
GPT teacher head0.177
Teacher spread0.172 · 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

Quick stats

Citations38
Published2005
Admission routes1
Has abstractyes

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