JQOS: a QoS-based Internet videoconferencing system using the Java media framework (JMF)
Bibliographic record
Abstract
The heterogeneity feature of the Internet makes it hard for a single real-time multicast stream with unique or static quality of service (QoS) support to provide good service to all receivers. Applying network-level QoS guarantees or application-level QoS adaptations are often considered effective solutions to this issue. However, the current proposed protocols or schemes have problems in scalability and implementation. This paper proposes a simple but efficient application-level dynamic QoS control mechanism and demonstrates it via implementing a QoS-based Internet videoconferencing system using Sun Microsystems' Java media framework (JMF). The dynamic QoS self-adaptation model has achieved the goal in receiving clear audio and visually useful video. The intelligent QoS request-handling algorithm may adjust the source transmission to satisfy most of, if not all, session receivers' requests. The receiver's QoS self-adaptation ability allows session receivers to apply their individual interests on the receiving 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 | 0.000 |
| 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 | 0.000 |
| 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".