Mental workload associated with operating an agricultural sprayer in response to GPS navigation aids
Bibliographic record
Abstract
The first of the four objectives of the present study was to conduct a complete task analysis in order to document the tasks and associated workload as experienced by the operator of an agricultural sprayer equipped with a lightbar navigation device.Task analysis result showed that, on average, an operator sprays on different terrains for 15 h in a day which includes day, dusk, and night illumination.Moreover, lightbar and aiming cues were important sources of guidance information.The second objective investigated the change in mental workload while guiding a sprayer in response to a GpS lightbar under day and night illumination, low and high task difficulty, and three task levels (driving only, monitoring only, and dual task).Sixteen male university students were trained to drive a fixed-base agricultural driving simulator.Mental workload was measured by performance measures, physiological measures, and subjective rating scales.All the performance measures, the P300 latency, and subjective rating scales showed that mental workload increased significantly with the change in illumination from day to night, task difficulty from low to high, and task types from single to dual.Under night illumination, participants spent more time looking at the lightbar for guidance information.The third objective investigated the sensitivity and diagnosticity of three different variants of NASA-TLX and five different variants of simplified SWAT scale to assess the mental workload associated with agricultural spraying.The discrete variants of SSWAT showed highest sensitivity and diagnosticity, but also higher between-subject variability.The continuous variants of both scales had less sensitivity and diagnosticity, but also lower between-subject variability.Thus, the selection of a scale was a function of sensitivity, diagnosticity or between subject variability.The fourth objective evaluated i ABSTRACT the mental workload associated with operating an agricultural sprayer in response to a commercial GPS lightbar(LBR), a mapping display (MAp), and an integrated display (tNT).The performance and physiological measures showed that the LBR display induced less mental workload followed by INT and MAP.Subjective rating scale showed an opposite trend due to the differential task engagement with various displays.Therefore, the MAP display should not be used as the sole guidance aid.Ph.D. is a long journey and sometimes it becomes very difficult to find away out.But, this journey is beautiful if one gets illuminated with the knowledge and precise guidance of their'guru'.I would like to thank my 'guru', Dr. Danny Mann for his infinite support, able guidance, constructive criticism, and patience throughout this journey.My journey
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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 | 0.004 |
| 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) | 0.001 | 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 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".