Accelerated genetic algorithm for bandwidth allocation in view of EMI for wireless healthcare
Why this work is in the frame
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Bibliographic record
Abstract
To enhance the capacity of patients supported by wireless in-hospital monitoring systems, a bandwidth allocation scheme for the transmission of medical data in the wireless local area network (WLAN) is proposed. The problem of bandwidth allocation, subject to limited wireless bandwidth, quality of service (QoS) requirements of medical data transmission, as well as electromagnetic interference, is modeled as a non-polynomial (NP) optimization problem. To save the computation time of this NP problem, we propose an accelerated genetic algorithm by dynamically adjusting both the inheritance probability and the mutation probability, and then compare it with other off-the-shelf genetic algorithms. Our study shows that our proposed algorithm can save computation time and attain the same result of bandwidth allocation in comparison with other algorithms.
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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 it