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Record W2156625519 · doi:10.1109/have.2006.283780

MPEG-7 Description of Haptic Applications Using HAML

2006· article· en· W2156625519 on OpenAlexaff
Mohamad Eid, Atif Alamri, Abdulmotaleb El Saddik

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHaptic technologyComputer scienceReuseXMLCompatibility (geochemistry)Human–computer interactionSoftwarePlug-inMultimediaSoftware engineeringSimulationWorld Wide WebProgramming languageEngineering

Abstract

fetched live from OpenAlex

The continuous evolution of computer haptics, as well as the emergence of a wide range of haptic interfaces has recently boosted the haptics domain. Even though efficient tools that support the developer's work exist, little attention is paid to the reuse and compatibility of haptic application constituents. In response to these issues, we propose an XML-based description language, namely Haptic Application Meta Language - HAML. HAML is designed to provide a technology-neutral description of haptic models. It contains ergonomic requirements and specifications for haptic hardware and software interactions. The envisioned goal is to allow for the creation of plug-and-play environments in which a wide array of supported haptic devices can be used in a multitude of virtual environments, with the compatibility issues being handled by automated engines instead of programmatically by the user. As per implementation, MPEG-7 standard has been used to instantiate HAML schema through the use of description schemes (DS). Our preliminary experimentation demonstrates the suitability of HAML for solving the compatibility issue

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: none
Teacher disagreement score0.838
Threshold uncertainty score0.180

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 head0.020
GPT teacher head0.208
Teacher spread0.188 · 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

Citations17
Published2006
Admission routes1
Has abstractyes

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