Design and semantics of form and movement 5:DeSForM 2009, October 26-27, 2009, Taipei
Bibliographic record
Abstract
Whenever there is perception of form, there is fraud.When you think you know something, you actually do not know it, for you are seized by the form of knowing something.When you feel you are not knowing anything, you begin to know something.In the ivLab (Image and Vision Lab) at National Taiwan University, we try to utilize multimedia technology to bring out the user's consciousness of form and void, and to guide the user back to oneness and peace, or at least to the pathway leading to oneness and peace.In our recent work "I am," we used a gaze tracking device to record and analyze the intent of a participant when he or she was browsing a colorful cabinet, and then suddenly displayed a digitized self portrait between the user and the cabinet.This was done to invite the participants to contemplate their volition and consciousness.In another interactive work, "Breathing between Present and Past,"we made it possible for museum visitors to revive a famous rusty artifact by touching a virtual display of the artifact.The visitor could only be successful, however, if he or she had breathed slowly and deeply in sync with the breathing of the artifact (rendered with computer simulation) for a certain period of time.It was hoped that breathing could function as a bridge between form and void, and could help to build a good connection between the museum visitors and the museum artifacts.In our current project "i-m-Space," which is an Interactive Multimedia-enhanced Space for the rehabilitation of post-surgery breast cancer patients, we again use breathing and touching as the interaction elements for relaxation and rehabilitation.Some of our other related works will be introduced in this talk, including virtual touch panel, 3D magic crystal ball, eFovea, i-m-Top, and i-m-Tube.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.078 | 0.013 |
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".