Wireless mesh access point routing for efficient communication in underground mine
Bibliographic record
Abstract
The reliability and survivability of conventional communications systems in harsh mining environments has always been a problem. The extreme conditions such as falling rock, collapsing tunnels, fires, explosions and flooding, during which communications are needed most, can also render them inoperable. An emergency underground communication system needs to be very robust with respect to these and other potential hazards. This paper deals with wireless backbone positioning for mesh wireless local area (WLAN) network. The routing problem is simulated to define the best position to place the wireless access point in mine galleries. The optimization strategy applied to the network design problem is the genetic algorithm. From various criteria such as the power profile through the mining gallery and the average SNIR level, the genetic algorithm treats all the possible positions and determines the optimal one for an effective communication. Optimization results considering density effect and other parameters such as the range, the hop number, the received power variation, the connection quality between access points are present
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 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".