Metodología de diseño sobre FPGA en un curso de sistemas digitales
Bibliographic record
Abstract
Se presenta en este trabajo una metodología para el diseño de sistemas digitales sobre FPGA (Field Programmable Gate Array). Esta metodología inicia con el análisis de requerimientos del cliente y abarca hasta la implementación final en un dispositivo programable. La propuesta metodológica ha sido aplicada y probada en los cursos del área de Técnicas Digitales en la Carrera de Ingeniería Electrónica de la Pontificia Universidad Javeriana – Bogotá, de acuerdo a un modelo de aprendizaje activo basado en proyectos (PBL, Project Based Learning) para lograr en los estudiantes un mayor conocimiento técnico significativo, aumentar su nivel de motivación hacia la ingeniería e incrementar su capacidad de comunicación, trabajo en equipo y capacidad de diseño. Todo esto es fruto del trabajo de investigación en educación en ingeniería que el grupo de profesores del área de Técnicas Digitales del Departamento de Electrónica de la Universidad, ha desarrollado en los últimos cuatro años.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".