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Record W2536454359 · doi:10.17706/jsw.11.10.1040-1053

Time-Triggered Ethernet Metamodel: Design and Application

2016· article· en· W2536454359 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Software · 2016
Typearticle
Languageen
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsPolytechnique MontréalÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of CanadaConsortium de Recherche et d’innovation en Aérospatiale au Québec
KeywordsMetamodelingAvionicsIntegrated modular avionicsComputer scienceEthernetModular designSoftware engineeringModeling languageKey (lock)Embedded systemSystems engineeringOperating systemEngineeringSoftware

Abstract

fetched live from OpenAlex

The combination of the SAE Time Triggered Ethernet (TTEthernet) standard with the Integrated Modular Avionics (IMA) architectures supports the design, deployment and integration of mixed-critical avionic applications. In order to cope with the complexity of these tasks, we advocate for a model-driven engineering methodology. The key element of such methodology is the modeling language, which enables producing relevant models of the system. In this paper, we present a metamodel, which captures the main features and concepts defined in the SAE TTEthernet standard. We discuss how a combination of the TTEthernet metamodel with an IMA metamodel can be used to extend the AADL modeling language to model avionic applications deployed a TTEthernet-networked IMA platform. Finally, we present a case study to illustrate our approach.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.985
Threshold uncertainty score0.195

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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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