A scheduling scheme for multiplexing extra streaming data into digital TV programs
Bibliographic record
Abstract
In digital TV systems, variable bitrate encoding is usually used to improve the bandwidth usage efficiency. Since the transmission channel has a fixed bandwidth, this leaves some portions of the bandwidth unoccupied. This free space can be used to transmit extra data to enhance the TV content, which can be either discrete, like text, or streaming, like video and audio. We address the problem of adding time-sensitive streaming data to a TV program. The crucial part of this problem is a scheduling algorithm that guarantees the on-time delivery of the incidental data to the decoder. We present a sophisticated time-sensitive scheduling algorithm for off-line multiplexing of TV programs and incidental streaming data. The two important features of our algorithm are: 1) it minimizes the presentation delay for incidental and main streams; 2) it minimizes the required decoder buffer size for incidental data. Comparing the experimental results of our algorithm with existing scheduling methods shows that our algorithm significantly reduces the presentation delay and the decoder buffer size for the incidental streams.
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How this classification was reachedexpand
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 | 0.002 |
| 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".