vPresent: A cloud based 3D virtual presentation environment for interactive product customization
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In modern society, many companies offer product customization services to their customers. There are two major issues in providing customized products. First, product manufacturers need to effectively present their products to the customers who may be located in any geographical area. Second, customers need to be able to provide their feedbacks on the product in real-time. However, the traditional presentation approaches cannot effectively convey sufficient information for the product or efficiently adjust product design according to customers’ real-time feedbacks. In order to address these issues, we propose vPresent , a cloud based 3D virtual presentation environment, in this paper. In vPresent, the product expert can show the 3D virtual product to the remote customers and dynamically customize the product based on customers’ feedbacks, while customers can provide their opinions in real time when they are viewing a vivid 3D visualization of the product. Since the proposed vPresent is a cloud based system, the customers are able to access the customized virtual products from anywhere at any time, via desktop, laptop, or even smart phone. The proposed vPresent is expected to effectively deliver 3D visual information to customers and provide an interactive design platform for the development of customized products.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it