Source localization using a double three-dimensional intensity array
Bibliographic record
Abstract
The precision of source localization methods using an array of multiple microphones depends on the number of microphones and spacing, i.e., it requires many microphones, small spacing and large aperture. To overcome the demerit in size, cost and data processing time, a double-module array system was suggested, of which a three-dimensional intensity array consists of a module. A three-dimensional intensity vector indicating the bearing angle was estimated using a set of four microphones arranged in a tetrahedral shape. Because a microphone in the apex was used in common for two modules along with the compactness of tetrahedron, number of microphones and size could be reduced. To cover a wide frequency range, two modules had different microphone spacing to minimize the low frequency phase error and high frequency finite difference error. Three-dimensional intensity was calculated by using the Taylor series expansion. For a double-module array having 16 and 80 mm in array spacing, simulations, assuming an anechoic condition, were conducted to test performances of angle detection varying bearing angle of source location, which was 1.3 m apart from the detection module. Average error of all bearing angles was less than 2o for 270-7800 Hz. (Partially supported by BK 21 project)
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".