Testbed and experiments for mobile TV (DVB-H) networks
Bibliographic record
Abstract
We present a complete, running, testbed for mobile TV networks that employ the Digital Video Broadcast - Handheld (DVB-H) open standard. DVB-H based networks have been deployed in several countries around the world and currently being pilot-tested in many others. Nevertheless, there exists no open-source testbed in the literature to enable researchers to analyze and optimize the performance of such networks; most testbeds are proprietary. Our testbed implements the complete stack of the DVB-H standard and it streams real videos to actual handheld devices. It integrates several off-the-shelf hardware components and devices with software components. Some of the software components are developed by us and others are leveraged (after bug fixes and modifications) from open-source projects. In addition, we present several experiments to: (i) evaluate and compare multiple energy-saving techniques recently proposed for mobile TV networks, and (ii) demonstrate a new method to reduce the channel switching delay.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".