MétaCan
Menu
Back to cohort
Record W2147119912 · doi:10.1109/oceansap.2006.4393830

Source Tracking with Multiple-Forgetting-Factor RLS Using a Vector-Hydrophone Away From or Near a Reflecting Boundary

2006· article· en· W2147119912 on OpenAlexaff
Kainam Thomas Wong, Mohamad Khattar Awad

Bibliographic record

VenueOCEANS 2006 - Asia Pacific · 2006
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHydrophoneAzimuthAcousticsSource trackingComputer sciencePhysicsOptics

Abstract

fetched live from OpenAlex

A vector-hydrophone (a.k.a. acoustic vector-sensor) is composed of two or three spatially collocated but orthogonally oriented velocity-hydrophones, possibly plus a collocated pressure-hydrophone. A vector-hydrophone may form azimuth-elevation spatial beams that are invariant with respect to the sources' frequencies, bandwidths and radial locations (i.e., in near field as opposed to the far field). This paper adopts a multiple-forgetting-factor recursive-least-squares (RLS) adaptive algorithm to a single vector-hydrophone for source tracking, without needing any prior knowledge of the source power and/or the noise powers.

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.

How this classification was reachedexpand

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
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 score0.279
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.000
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 head0.024
GPT teacher head0.259
Teacher spread0.235 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueOCEANS 2006 - Asia PacificSame topicSpeech and Audio ProcessingFrench-language works237,207