Packing scheme for layered coding MPEG-2 video transmission over ATM based networks
Bibliographic record
Abstract
In the transmission process of a video signal over ATM networks, cells are inevitably exposed to delays, errors and losses due to the statistical multiplexing used in these networks. These phenomena effect the quality of the video signal and without adequate measures to control the propagation of the impairments the quality of the service may fall below acceptable levels. In the first part of this paper, we present an adaptive data partitioning (ADP) scheme. This scheme splits a video stream into a high priority and low priory substreams. In the second part of the paper, we propose a novel hierarchical packing scheme for the transmission of the two video substreams over ATM. The proposed packing scheme overcomes the problem that when no provisions are taking to properly pack a hierarchical-encoded video stream, the loss of a high priority ATM cell will result in the complete loss of the group of cells. Results for different video sequences and different bitstream split levels are given, showing the efficiency of our schemes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".