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Record W2020687126 · doi:10.4271/2014-01-2159

SAE AS5643 and IEEE-1394 Flexible Deterministic Solution for Aerospace and Defense

2014· article· en· W2020687126 on OpenAlexaff
Richard Mourn

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2014
Typearticle
Languageen
FieldEngineering
TopicEngineering and Test Systems
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsAerospaceComputer scienceAeronauticsAerospace engineeringEngineering

Abstract

fetched live from OpenAlex

The paper provides an introduction into IEEE-1394, AS5643 and related documents. It then explores the I/O Technology Suitability Study criteria used to originally select IEEE-1394b (Beta) as the Vehicle System Data Bus for the F-35 Joint Strike Fighter and update each criterion with new information based on more than a decade of experience and use in not only the F-35 but several other programs. Based on the suitability study criteria, the reader gains insight into how and why programs like the F-35, which implements dozens of AS5643/IEEE-1394 devices per plane, utilize AS5643/IEEE-1394 for its vehicle system network. This unprecedented use of a high speed (491.52Mb/s) serial interface on an aircraft proves the capability of AS5643/1394, and opens the door for higher bandwidth communication between the Control Computer and remote nodes. While I/O bandwidth is important, system level deterministic behavior is required for most vehicle system networks and AS5643 coupled with 1394 provides the required deterministic behavior. The criteria explored is: deterministic behavior, fault tolerance, weight, power, volume, latency, software impact, hardware development risk, Failure Modes and Effects Analysis (FMEA) risk assessment, tech refresh path, both non-recurring and re-occurring costs and, finally, customer acceptance.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0280.009

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 head0.011
GPT teacher head0.225
Teacher spread0.213 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2014
Admission routes1
Has abstractyes

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