Creating Islamic art with interactive geometry software
Bibliographic record
Abstract
The production of images, in particular figurative art is discouraged in Islam on the basis that it could lead to idolatry. For the Muslims there is no divinity other than the Almighty God and this means that no any form of creations can be projected to His attributes. In this way, muslim artists express their works in creating patterns of complex geometric designs as well as intricate patterns of vegetative ornament. These masterpieces have covered the surfaces of buildings especially mosques, palaces and other public places in replace to human figures as established in the non-Muslim culture. From the mathematical perspective, the distinctive Islamic art has cleverly combined the use of common geometric shapes such as circles, points and lines together with some geometric principles such as symmetry, similarity and transformation, namely translation, rotation, reflection and scaling. With the present software technology, the creation of this art can be made easier using interactive geometry software (IGS) which is also known as dynamic geometry software (DGS). IGS are computer programs which allow their users to interactively create, manipulate and explore geometric constructions using points, lines, circles and geometric principles. Activities involving students to create Islamic art with IGS will help them to appreciate mathematics as an art that is enjoyable and fun besides realizing that its development is greatly influenced by values and cultures. This paper will describe how some basic designs can be constructed using KDE interactive geometry (KIG) which is available as free open source software (FOSS). Some samples of creative students ' work will also be shared.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.176 | 0.028 |
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".