Development of a Head-up Display System for Automotive Applications Using A Repulsive-force Electrostatic Actuated Micromirror
Bibliographic record
Abstract
This thesis focuses on developing a comprehensive HUD system for automotive applications based on the laser-scanning display (LSD) utilizing a repulsive-force electrostatic actuated micromirror. Key system components of the automotive HUD system are: the micromirror, the optical array, and the optical film. The current micromirror design is reinforced to better perform under driving conditions without compromising the structural durability. The optical array is developed for enhancing the magnification and the resolution of the LSD virtual and real images. The optical film is designed to reflect the LSD virtual image and diffuse the LSD real image without hindering the driving field of view. Two real-time control methods are introduced and a flickering static image is achieved at 32 fps by the time variable control method. The HUD prototype successfully displays both of the LSD virtual image (10 cm x 10 cm formed at 3.30 m away from the driver) and the LSD real image (8 cm x 8 cm formed on the windshield).
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".