Design, Fabrication, and Testing of a Novel Design for Flexible Light-Emitting Diode Signage Modules
Bibliographic record
Abstract
Abstract This paper presents a new design architecture for mechanically flexible light-emitting diode (LED) signage modules for applications in digital advertising on curved surfaces. The new design comprises an array of commonly used rigid printed circuit boards (PCBs) but of smaller size with some spacing between them, which is encapsulated by a flexible substrate or potting material, instead of a large single rigid PCB in the entire LED module as in the case of conventional LED signage modules. Commonly used through-hole type red-green-blue (RGB) LEDs are considered. To demonstrate the design, manufacturing, and mechanical flexibility of the design, a prototype LED signage module with a typical industry standard size of 304 mm × 304 mm × 10 mm was designed and fabricated. Experimental testing and finite element simulations were conducted to analyze mechanical flexibility and internal stresses in the module. The results demonstrate that the new design provides flexible LED modules, without altering the conventional LED control system. It is shown that maximum stress occurs in the spacing between the PCBs and is small even for large module deflection. As the curvature of module deflection was decreased, the maximum stress increased, indicating an important design parameter for the module deflection. The proposed design architecture will enable both indoor and outdoor digital advertising using billboards on a wide range of curved surfaces.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 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".