Process of 3D wireless decentralized sensor deployment using parsing crossover scheme
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A Wireless Sensor Networks (WSN) usually consists of numerous wireless devices deployed in a region of interest, each able to collect and process environmental information and communicate with neighboring devices. It can thus be regarded as a Multi-Agent System for territorial security, where individual agents cooperate with each other to avoid duplication of effort and to exploit other agent’s capacities. The problem of sensor deployment becomes non-trivial when we consider environmental factors, such as terrain elevations. Due to the fact that all sensors are homogeneous, the chromosomes that encode sensor positions are actually interchangeable, and conventional crossover schemes such as uniform crossover would cause some redundancy as well as over-concentration in certain specific geographical area. We propose a Parsing Crossover Scheme that intends to reduce redundancy and ease geographical concentration pattern in an effort to facilitate the search. The proposed parsing crossover method demonstrates better performances than those of uniform crossover under different terrain irregularities.
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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