Thai Traditional Hanging Garland Decoration to the Pattern Design Adapted on Suan Sunandha Rajabhat University Souvenir
Bibliographic record
Abstract
The study aimed to analyze the Thai traditional hanging garland decoration for modeling in the pattern design adapted on a souvenir item, as well as to evaluate the souvenir pattern design result. In regard to the research process, the researcher initially applied the mixed method in learning and investigating information by using qualitative research. Additionally, the researcher used quantitative research in souvenir pattern design assessment. The area delimitation of this study was a souvenir shop in Suan Sunandha Rajabhat University, as well as Suan Sunandha royal residence where Thai traditional hanging flower decoration models were gathered. Another delimiting factor was the sample which consisted of 3 design experts (post evaluation), 10 souvenir shopkeepers (post evaluation), and 100 consumers (pre- and post-questioning) using the accidental sampling method at the souvenir shop in order to evaluate the satisfaction towards souvenir design. Furthermore, the research instruments consisted of a literature review, in-depth interviews, questionnaires and evaluation formats.The research result elucidates that 10 Thai traditional suspended garland decoration motifs were collected; however, only the first motif was selected to be adapted in the pattern design since it was an original and the most-found figure. According to the pattern design development, 10 patterns were created which included: Kledgardenia net, Kra-Bueang gardenia net, Si-Dok-Si-Karn gardenia net, Jan-Krueng-Seek gardenia net, Kaew-Ching-Duang gardenia net, Daw-Kra-Jai gardenia net, Oak-Mang-Mum gardenia net, Hok-Karn-Hok-Dok gardenia net, Daw-Lom-Deaun gardenia net, as well as Lai gardenia net. Moreover, the recreated souvenir which the consumers purchase the most was a coffee mug.The evaluation result of adapting the patterns on the coffee-mug souvenirs illustrated that there was a high level of satisfaction on the beauty involving color and pattern, there was a high level of satisfaction on size and usage, and the highest level of satisfaction regarding the product was towards marketing in selling itself, as well as representing the place identity.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".