MétaCan
Menu
Back to cohort
Record W1947795819

ACTIVE CONTROL OF AN OFF-AXIS NOISE SOURCE

2001· article· en· W1947795819 on OpenAlex
Jingnan Guo, Murray Hodgson, Jie Pan

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueUWA Profiles and Research Repository (University of Western Australia) · 2001
Typearticle
Languageen
FieldEngineering
TopicAdvanced Adaptive Filtering Techniques
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsQUIETNoise (video)Channel (broadcasting)Ambient noise levelActive noise controlNoise floorAcousticsWavefrontPhysicsControl theory (sociology)OpticsNoise measurementComputer scienceTelecommunicationsControl (management)Noise reduction
DOInot available

Abstract

fetched live from OpenAlex

A multi-channel active-noise-control system can been used to create a large quiet zone in free-space when the noise source is on the symmetry axis of the control system. In this study, the efficiency of a multi-channel active-noise-control system is investigated numerically for the case of a noise source located at off-axis positions. It was found that both the location and the size of the quiet zone change significantly with the off-axis location of the noise source. The control system is still able to construct a large area of wavefront matching, and create a large quiet zone, when the off-axis shift of the noise source is within this range. There exists an off-axis range for which an optimally pre-arranged multiple-channel control system remains optimized. This range is expressed analytically in terms of the wavelength at the frequency of interest, and of the configuration of the control system.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.047
GPT teacher head0.296
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it