Adaptive zone based active noise control for a moving target
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
This study focuses on enhancing active noise control (ANC) in room enclosures, specifically targeting zones of quiet (ZoQ) around aircraft passenger seats. By integrating virtual sensing and motion tracking techniques, we aim to dynamically adapt the ZoQ to moving targets. Key to our approach is the strategic placement of actuators and sensors, forming the core of the ANC system. Our methodology includes virtual sensing for ANC analysis, ZoQ optimization for varied applications, and in-depth case studies. We introduce an innovative combination of a speaker gimbal system, a vision system, and custom software for precise motion tracking, significantly improving ZoQ localization. The findings offer insights into maintaining effective ZoQs for multiple input multiple output (MIMO) local ANC configurations, laying the groundwork for adaptive ZoQ control about sound sources and desired cancellation locations. This research marks a significant step towards more effective and adaptable noise cancellation in enclosed spaces.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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