Identification of Text and Symbols on a Liquid Crystal Display Part III: The Effect of Ambient Light, Colour and Size
Bibliographic record
Abstract
This study aimed to identify the minimum font size that supports fast and accurate identification of text and symbols displayed on an LCD under ambient lighting conditions similar to those in naval ships' operations rooms. A series of letters, numbers and combat symbols were displayed on an LCD for either 106 ms or 173 ms. Participants were asked to identify each stimulus and the certainty of their decision. Letters and numbers were presented in white, red, green and cyan, and symbols were either white or colour-coded. The stimulus heights subtended angles of between 8 minutes and 20 minutes. The study identified the minimum height at which accuracy and certainty were not significantly reduced. Two experiments were performed: one on a land-based sample, and one using Canadian Defence Force personnel during a sea trial in an attempt to identify the potential affects of ships motion and fatigue. Colour significantly improved the identification accuracy and certainty of symbols. Red numbers and letters were identified with significantly lower confidence than white, green or cyan. Some performance degradation was observed during the sea trial, and it is suggested that text and symbols ideally have a height of 16 min or greater, but that a height of 12.5 min or greater is acceptable. A height of less than 12.5 min must not be used for text or symbols that need to be rapidly identified.
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 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 | 0.001 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".