Large Scale Satellite-Based Wireless Sensor Networks for Arctic Monitoring
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
Abstract Nowadays wireless sensor networks (WSNs) have been widely used as a field information gathering technology in remote monitoring and control areas. However, deploying WSNs in the Arctic areas is still facing some special challenges. The extremely low temperature (below -40°C degrees) and frequent snow/ice covering may affect the stable operation of regular electronic circuitry. And inaccessibility makes the Arctic WSNs be isolated from human's maintenance most of the time. In this paper, we propose a Large-Scale Satellite-based Wireless Sensor Network (LSSWSN) architecture for the Arctic areas. Based on ZigBee-Pro protocol, our proposed LSSWSN holds the capacity of 64,000 nodes in total, which are divided into 100 sub-networks with 640 nodes for each sub-network. This proposed design can make sure some critical network faults to be isolated into small sub-network domain. Moreover, FPGA-based hardware implementation of AES has been integrated to improve communication security. Special considerations have been also taken into account for the enclosure design of the sensor nodes, routers, and coordinator within LSSWSN.
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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 | 0.001 | 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 it