Sensitivity Analysis of a Beamforming Technique for Acoustic Measurements
Bibliographic record
Abstract
Beamforming is a technique that is used to determine the location of an acoustic source and the sound level spectrum of the signal produced by the source. This technique involves an array of microphones which record acoustic signals at multiple locations. A detailed analysis of the beamforming technique was carried out for three different array geometries: a uniform linear array, a uniform planar array, and a random array. The effect of various parameters, such as the number of microphones in an array, on the applicability of the technique was examined using both simulations and experiments. The simulation results established that the source localization capability of a uniform linear array is limited to an acoustic source lying in the plane of the array. In contrast, a planar array (either uniform or random) does not suffer the above limitation. The results also showed that a random array (eg., a spiral array) is the best of all the array geometries. The experimental results demonstrated the robustness of the beamforming technique in localizing an acoustic source and also confirmed the superiority of a uniform planar array over a uniform linear array.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".