A survey of event-based strategies on control and estimation
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
The event-based strategies have recently received considerable research attention due primarily to their irreplaceable superiority in resource-constrained systems. Compared with the widely adopted time-driven schemes, such novel event-based schemes have advantages of improving the efficiency in resource utilization in many real applications. Event-based strategies represent an effective way of generating sporadic executions, where an execution is generated only when a specific event (e.g. a certain signal exceeds a prescribed threshold) arises. In this survey, we aim to summarize the results available in the literature on event-based strategies so as to promote the related research in this realm. The progress of the event-based design and analysis strategies is systematically reviewed in both control and estimation domains. Specifically, the event-based control strategies have been discussed for networked control systems, multi-agent systems and other systems, and the event-based estimation schemes have been highlighted according to the send-on-delta and send-on-area concepts. Some potential future research directions are finally pointed out for event-based strategies.
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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 | 0.003 | 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 | 0.000 | 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