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Record W2111329600 · doi:10.1109/ism.2010.40

Bridging the Gap between Virtual and Real World by Bringing an Interpersonal Haptic Communication System in Second Life

2010· article· en· W2111329600 on OpenAlexaff
A. Rahman, SK Alamgir Hossain, Abdulmotaleb El Saddik

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHaptic technologyVirtual worldComputer scienceHuman–computer interactionVirtual realityMetaverseLeverage (statistics)Bridging (networking)MultimediaInterpersonal communicationBridge (graph theory)Human communicationVirtual machinePsychologySimulationCommunicationArtificial intelligenceComputer security

Abstract

fetched live from OpenAlex

The sense of touch has much importance in technology-mediated human emotion communication and interaction. Many researchers around the world are aiming to leverage the sense of touch in the communication medium between multi-user 3D virtual world and real environment. Driven by the motivation, we explored the possibilities of integrating haptic interactions with Linden Lab’s multi-user online virtual world, Second Life. We enhanced the open source Second Life viewer client in order to facilitate the communications of emotional feedbacks such as human touch, encouraging pat and comforting hug to the participating users through real-world haptic stimulation. These emotional feedbacks that are fundamental to physical and emotional development in turn can enhance the users interactive and immersive experiences with the virtual social communities in the Second Life. In this paper, we describe the development of a prototype that realizes the aforementioned virtual-real communication through a haptic-jacket system. Some of the potential applications of the proposed approach includes distant lover’s communication, remote child caring, and stress recovery.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.025
GPT teacher head0.275
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations20
Published2010
Admission routes1
Has abstractyes

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