ECD++ a DEVS based real-time simulator for embedded systems
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.
Bibliographic record
Abstract
In this paper we will present an M&S-driven framework to develop embedded systems based on the DEVS (Discrete Event systems Specification) formalism. DEVS provides a formal foundation to M&S that proved to be successful in different complex systems. This approach combines the advantages of a simulation -based approach with the rigor of a formal methodology. Another advantage of using DEVS is that different existing techniques (Bond Graphs, Cellular Automata, Partial Differential Equations, Queuing models, etc.) have been successfully transformed into DEVS models. CD++ is a software environment that implements DEVS theory with extensions to support real-time model execution in embedded systems. CD++ was used as the base for our development, building on previous research focused on real-time applications with hardware-in -the-loop. Embedded CD++ (ECD++) has been developed based on this tool to accomplish this aim. A small robocart has been built and tested with ECD++. The robocart uses sonar and touch sensor to detect obstacles on its way. At the end, ECD++ program has been compiled for the target and run using telnet connection on the board.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it