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Record W2097866586 · doi:10.1002/dac.567

A novel delineation mechanism for the ATM adaptation layer 2 over wireless ATM networks

2002· article· en· W2097866586 on OpenAlex
Luis Villaseñor-González, Luis Orozco–Barbosa, Louise Lamont

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

VenueInternational Journal of Communication Systems · 2002
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsCommunications Research Centre CanadaUniversity of Ottawa
Fundersnot available
KeywordsATM adaptation layerComputer scienceComputer networkAsynchronous Transfer ModeNetwork packetPayload (computing)

Abstract

fetched live from OpenAlex

Abstract The ATM adaptation layer 2 (AAL2) has been standardized by the ITU‐T for the support of low data rate and delay‐sensitive applications, such as voice, over ATM networks. One of the main characteristics of the AAL2 standard is the support for multiplexing information at the expense of introducing a new frame structure inside the payload of the ATM cells. The AAL2 standard introduces a mechanism for the delineation of the AAL2 packets and it has been found that the delineation mechanism reduces the performance of AAL2 in the presence of channels with high bit error rates. In this paper, a novel delineation mechanism is proposed for AAL2 to be used over highly error‐prone channels, such as wireless links. The proposed mechanism improves the performance (i.e. reduces packet loss) of the AAL2 standard in the presence of bit errors and in some cases reduces the overhead required for the delineation of the AAL2 packets. Copyright © 2002 John Wiley & Sons, Ltd.

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: Methods · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score0.502

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 communication0.0000.001
Open science0.0010.000
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 head0.039
GPT teacher head0.264
Teacher spread0.226 · 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