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Record W2007930697 · doi:10.1109/have.2007.4371595

ALPHAN: Application Layer Protocol for HAptic Networking

2007· article· en· W2007930697 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
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of OttawaCommunications Research Centre Canada
Fundersnot available
KeywordsHaptic technologyComputer scienceProtocol (science)Application layerComputer networkLayer (electronics)User Datagram ProtocolCommunications protocolTransmission (telecommunications)XMLResource Reservation ProtocolInternet protocol suiteDistributed computingSimulationOperating systemThe InternetTelecommunicationsSoftware

Abstract

fetched live from OpenAlex

The transmission of haptic information over the network has recently received significant attention. The wide spectrum of haptic applications makes it difficult to capture the widely varying requirements of these applications into one generic protocol. In this paper, we introduce ALPHAN (Application Layer Protocolfor Haptic Networking), a novel application layer protocol for haptic communication. The distinguished features of this protocol are the followings. first, being an application layer protocol, it can easily be customized according to the application requirements and needs; second, the protocol utilizes an XML-based description to define its networking parameters; and third the protocol supports multi-buffering where priorities are attributed to different buffers in collaborative haptic environments. The implementation and preliminary evaluation of the protocol showed a satisfactory performance. We also present our immediate future development and possible research avenues.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.886
Threshold uncertainty score0.232

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 head0.033
GPT teacher head0.306
Teacher spread0.273 · 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

Citations29
Published2007
Admission routes1
Has abstractyes

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