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Record W4401691693 · doi:10.1016/j.ijadr.2024.07.002

Effects of color temperature and time gradients on visual fatigue recovery in closed cabin

2024· article· en· W4401691693 on OpenAlexaff
Mingjiu Yu, Jing Chen, Jun Qian, Quanjingzi Yuan, Hao Fan, Gongbing Shan

Bibliographic record

VenueAdvanced Design Research · 2024
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsEnvironmental scienceMaterials science

Abstract

fetched live from OpenAlex

The working environment of a closed cabin is particularly prone to inducing visual fatigue among visual display terminal (VDT) operators. Once visual fatigue symptoms set in, the limited space of the closed cabin and its monotonous visual environment make it challenging to alleviate visual fatigue by disregarding the fatigue. Fifteen healthy male participants aged 20–25 years were recruited for the study, and the results were statistically significant. The fatigue recovery degrees under three lighting color temperatures (3000 ​K, 4500 ​K, and 6000 ​K) and three recovery durations (5 ​min, 10 ​min, and 15 ​min) in a closed cabin were studied. The visual fatigue scale and the Karolinska Sleepiness Scale were employed to collect subjective fatigue data from the participants, while objective visual fatigue data were obtained using an eye tracker. After 5 ​min of rest, the rate of change in pupil diameter at low temperatures was significantly greater than that at high temperatures ( P ​= ​0.033). The results indicated that recovery under the 3000 ​K light environment was beneficial for alleviating and eliminating visual fatigue, while a 6000 ​K light environment helped improve the alertness of VDT operators. Recovery time significantly impacted the recovery degree of visual fatigue, with the recovery degree increasing as recovery time increased. Color temperature and recovery time interacted significantly ( P ​= ​0.011), and the light environment parameters showed a significant impact only at short recovery times. This paper also introduced a visual fatigue recovery index to measure the degree of visual fatigue recovery, and the index was used to verify the experimental results. The research holds significant reference value for selecting ambient lighting color temperatures in resting rooms. • Investigating effects of 3000K, 4500K, 6000K & 5, 10, 15 ​min rest on visual fatigue recovery. • 3000K lighting beneficial for alleviating visual fatigue; 6000K improves alertness. • Proposing new integrated visual fatigue recovery index using subjective & objective metrics. • Provides guidance for rest area lighting in confined cabins to promote faster recovery. • Offering solutions to alleviate visual fatigue for closed cabin operators.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.398
Teacher spread0.366 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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