Bibliographic record
Abstract
A cross-domain communications network for above and below water marine robots, based on code-division multiple access (CDMA), is reported. CDMA is a promising physical layer and multiple access technique for underwater acoustic sensor networks as it: (i) is robust to frequency selective fading, (ii) compensates for multi-path effects at the receiver, and (iii) allows receivers to distinguish amongst signals simultaneously transmitted by multiple devices. Consequently, CDMA increases channel re-use and reduces packet retransmissions, which results in decreased energy consumption and increased network throughput. The proposed CDMA network for autonomous co-ordination and networking is applied to marine robots separated by extended ranges to transmit images/information from underwater to above-water. The work involves a complete communications protocol stack from the physical to the application layer. Simulations of the proposed network were performed with Network Simulator-3 (NS-3). The proposed protocol leverages CDMA properties to achieve multiple access to the scarce underwater bandwidth while previous reported work with underwater channels only consider CDMA for the physical layer encoding. Simulations shows the proposed underwater acoustic network protocol outperforms other existing ones. The next step is preliminary testing in-water.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".