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Record W2095885287 · doi:10.1109/glocom.1989.64276

Turbo-Loop: a rate-adaptive digital subscriber loop (RA-DSL) for advanced ISDN access applications

2003· article· en· W2095885287 on OpenAlexaff
W.E. Grover, Witold A. Krzymień, T. Fong, Aiguo Shen, J. Dubuc

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Line Communications and Noise
Canadian institutionsAlberta Energy
FundersAdvanced Technology Research Council
KeywordsDigital subscriber lineComputer scienceTurboLoop (graph theory)Integrated Services Digital NetworkBandwidth (computing)Bridging (networking)SoftwareTransmission (telecommunications)Computer networkEmbedded systemTelecommunicationsOperating systemEngineering

Abstract

fetched live from OpenAlex

The authors report the implementation of prototype hardware and control protocols which will automatically maximize the transmission rate of individual subscriber loops. The result is a rate-adaptive digital subscriber loop (RA-DSL) technology called Turbo-Loop, which makes possible new applications such as a simple form of bandwidth-on-demand and a strategy for increased utilization of existing copper, while bridging the gap to having fiber in the loop. Results predict that Turbo-Loop can deliver 1.5 Mb/s up to 2 km, reaching subscribers to 10 km and 80 kb/s, and can provide a potential increase of 400% to 600% in the total utilization of existing copper access networks. The authors describe the hardware and software design of the RA-DSL prototype and report results of adaptive transmission rate experiments on actual copper loops. Also described are simulation studies which predict the ultimate performance of a fully developed design based on the Turbo-Loop principle.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score0.690

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 science0.0000.000
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 head0.024
GPT teacher head0.270
Teacher spread0.245 · 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 designNot applicable
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

Citations1
Published2003
Admission routes1
Has abstractyes

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