Influence of Drying Conditions on the Effective Moisture Diffusivity and Energy Requirements of Ginger Slices
Bibliographic record
Abstract
The thin layer drying behaviour of ginger slices in a laboratory dryer was examined. The slices of 5 mm, 10 mm and 15 mm thicknesses were dried using heated ambient air at temperatures from 40 to 70 ºC and air velocity of 1.5 m/s. The effects of drying air temperature and slice thickness on the drying characteristics, drying time and energy requirement of drying process was determined. The results have shown that an increase in the drying air temperature causes shorter drying times. Thinner slices also causes a shorter drying time. The effective moisture diffusivity values increased from 3.36814 × 10-10 m2/s to 5.82524 × 10-9 m2/s while the activation energy values for different slice thickness of ginger varied from 196.15 to 198.79 kJ/mol. The total needed energy varied from 735.3 to 868.5 kWh while the value of specific energy requirement varied from 3676.6 to 4342.4 kWh/kg respectively.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".