Bibliographic record
Abstract
We investigate FTTX (Fiber-to-the Home/Premises/Curb) Passive Optical Networks (PON) for the deployment of broadband access networks such that the opportunities of optical fiber enabled technologies as well as of passive switching equipment can be exploited. We focus on designing the best possible architectures of hybrid FTTX PONs, which embraces both TDM and WDM technology. Advantages of hybrid PONs are twofold: they can (i) offer increased data rate to each user by employing WDM technology, (ii) provide flexible bandwidth utilization by employing TDM technology. We propose a novel network design optimization scheme for greenfield deployment of a set of hybrid PONs. For a given geographical location of an optical line terminal (OLT), a set of optical network units (ONUs) and their corresponding aggregated traffic demand, our proposed optimization scheme determines the design and dimensioning of the most economical set of hybrid PON networks while satisfying unicast/multicast traffic demands and taking into account the signal attenuation constraints. Computational experiments have been conducted on a set of up to 512 ONUs in order to evaluate the performance of the proposed scheme.
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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 | 0.000 | 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".