A Web-Based Application of TELOSB Sensor Network
Why this work is in the frame
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Bibliographic record
Abstract
Sensor network can be used in a numerous number of applications. However, implementing wireless sensor networks present new challenges compared with theoretical networks. In addition, implementing a sensor network might provide results different from that derived theoretically. Some routing protocols when implemented might fail to perform. In this paper, we implement three routing protocols, namely: Dynamic MANET on-demand, Collection Tree and Dissemination protocols. To compare the performance of these protocols, they are implemented using a Telosb sensor network. Several performance metrics are carried out to demonstrate the pros and cons of these protocols. A telemedicine application is tested in top of the implemented Telosb sensor network at King Fahd University of Petroleum and Minerals Clinic in Saudi Arabia, utilizing Alive ECG sensors.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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