Eco-Innovation: Applying the Woven Fabric from Dendrocalamus asper Fibers to Textile Product Design
Bibliographic record
Abstract
The objectives of this research were 1) to test the properties of the woven fabric from Dendrocalamus asper (D.asper) fiber blended with recycled polyester(r-PET), and 2) to study the design factors and evaluate the satisfaction with the new textile products.This is a mixed method research study, the results of which indicated that the physical properties of the developed textile fabric were assessed in accordance with textile testing standards, tensile strength, tear strength, fabric density, fabric weight, fabric thickness, abrasion resistance, and pilling resistance.The obtained fabric contained the unique textures of D.asper fiber blended with recycled polyester fibers.The population consisted of 3,012 visitors to Crafts Bangkok 2024 Thailand.The sample consisted of 353 visitors to Crafts Bangkok 2024 Thailand with an interest in textile products, obtained by simple random sampling with a 95% confidence level.Structured questionnaires with good quality (Cronbach's alpha = 0.919) were used as the research instrument.According to the exploratory factor analysis (EFA), there were four factors affecting consumers, i.e., 1) local materials, 2) green products, 3) healthiness, and 4) sustainability.Consumers had high levels of satisfaction with the new textile products (x̄ = 4.235; S.D = 0.472).All four factors significantly affected consumer satisfaction (p < .01)and could predict the dependent variable at 84.7%, with the standardized regression equation: 𝑍 = .196(𝑋 1 ) + .394(𝑋 2 ) + .244(𝑋 3 ) + .307(𝑋 4 ).The new textile products can therefore encourage the use of the abundantly available bamboo fibers in communities through sustainable development that helps increase economic value with eco-friendly qualities.
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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 | 0.000 |
| 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 | 0.001 | 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".