Reliability modeling for wireless Ultra Wideband biomedical radar sensing network
Bibliographic record
Abstract
Impulse Radio Ultra Wideband technology is a newly emerged technology suitable for low-power, low-complex, and low-cost biomedical radar sensing network. Fault tolerance and reliability, and power-saving perform a critical role in the operation of the IR-UWB human bio-sensing network designed for real-time human body health monitoring. In this paper, an IR-UWB bio-sensing network is proposed and the continuous Markov process is applied to model the proposed UWB bio-sensor network. Two different models are investigated, one is sensor with three transmitting power levels, and the other is sensor with six power levels. Both of them consume same total amount of power. The radar sensor and the sink node Markov model with repair rates taken into account are modeled as well. The paper is a contributing effort to develop an analytical model and explore the trade-offs in wireless IR-UWB bio-sensor network in terms of predicted reliability, operation time (MTTF), and power consumption.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 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".