Performance analysis of TBCD protocol over Wireless Body channel
Bibliographic record
Abstract
The improvements in implantable medical devices combined with wireless sensor networks are set to revolutionize the healthcare industry by providing real-time, low-cost health monitoring for the patients. The new field called Implantable Wireless Body Sensor Networks (IWBSN) has become a hot research topic because of the energy constraints and the circuit complexity. A novel protocol called Time-Based Coded Data (TBCD) has been proposed in an attempt to reduce the energy consumption in IWBSNs. In this work, TBCD protocol has been modeled and analyzed in MATLAB/SIMULINK with realistic body channel. The goal is to find the optimum transmit power, sensitivity of the transceiver for TBCD protocol to work efficiently for an optimal distance between sensor nodes and the base-station. In addition, it has been proved that the life time of the battery (20 mAhr /3.3V Battery) of a sensor node using TBCD protocol can be prolonged to 2500 days when compared to the state-of-art Zigbee protocol.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".