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Record W3147274174 · doi:10.1109/wsc.2006.323163

A Simulation Algorithm for Dynamic Structure DEVS Modeling

2006· article· en· W3147274174 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
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsCarleton University
Fundersnot available
KeywordsDEVSRotation formalisms in three dimensionsCorrectnessComputer scienceFormalism (music)AlgorithmModeling and simulationAdaptation (eye)Distributed computingObject-oriented modelingProgramming languageSoftwareSimulationMathematics

Abstract

fetched live from OpenAlex

Real-time system (RTS) correctness and timeliness are critical. Modeling and simulation techniques have been widely used for testing particular conditions on these systems. Recently, the DEVS formalism has been successfully used as a framework for RTS validation. Nevertheless, we need to address dynamic adaptation to dynamic changes in the environment. Dynamic structure DEVS focuses on the possibility to change system structure dynamically according to the system real requirements, which is useful for RTS (in which sometimes it is impossible to interfere with the running of the system, and auto-adaptation is needed). We present a new algorithm derived from the DSDE and the dynDEVS formalisms. We use the DSDE formal specifications, and parts of the dynDEVS simulation algorithms

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 score0.728
Threshold uncertainty score0.257

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 head0.076
GPT teacher head0.432
Teacher spread0.356 · 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

Citations12
Published2006
Admission routes1
Has abstractyes

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