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Record W1576351949

Wavelet-based solution of integral equations for acoustic scattering

2006· article· en· W1576351949 on OpenAlexvenueno aff
Mohamed Hesham Farouk

Bibliographic record

VenueCanadian acoustics · 2006
Typearticle
Languageen
FieldEngineering
TopicNumerical methods in engineering
Canadian institutionsnot available
Fundersnot available
KeywordsWaveletHelmholtz equationWavelet transformMathematicsWavelet packet decompositionMathematical analysisHelmholtz free energyIntegral equationStationary wavelet transformCascade algorithmDiscrete wavelet transformMoment (physics)Matrix (chemical analysis)AlgorithmMathematical optimizationApplied mathematicsComputer sciencePhysicsClassical mechanicsArtificial intelligenceBoundary value problem
DOInot available

Abstract

fetched live from OpenAlex

In this work, the multi-resolution wavelet analysis is used to solve Helmholtz integral equation for acoustic scattering.The integral equation is solved using moment method with wavelet basis.The unknown field is expressed as a two fold summation o f shifted and dilated forms o f a properly chosen mother wavelet.The wavelet expansion covers the scatterer surface for distributing the wavelet localized functions.A simpler formulation o f a square wavelet operator is proposed and tested in this investigation to obtain the moment matrix.The proposed operator saves some traditional stages o f wavelet transform and accordingly a part of the computations required.The square matrix inversion can be implemented easily on different media.The resulting matrix can be made sparse by applying an appropriate threshold.The solution of such sparse matrix saves a large portion o f the computational load.The accuracy o f the proposed solution is compared to the exact solution o f the problem.Computational savings are illustrated for acoustic scattering on a sphere for different wave numbers and wavelet bases order. s o m m a ir eDans ce travail, l 'analyse de ondelette est employee pour résoudre l 'équation intégrale de Helmholtz pour la dispersion acoustique.L'équation intégrale est résolue en utilisant la méthode de moment avec la base de ondelette.Le champ inconnu est exprimé comme une addition de deux fois des formes décalées et dilatées d'un ondelette correctement choisi de mère.L'expansion de ondelette couvre la surface de diffuseur pour distribuer les functions localisées par ondelette.Un opérateur carré de ondelette est propose dans une formulation plus simple et examiné pour que ce problème obtienne la matrice de moment.L'opérateur proposé sauve quelques étapes traditionnelles de ondelette transforment et en conséquence une partie des calculs priés.L'inversion carrée de matrice peut être mise en application facilement sur différents médias.L'application d 'un seuil approprié sur la matrice résultante la rend clairsemée.La solution d 'une telle matrice clairsemée sauve une grande partie du volume des calculs.L'exactitude de la solution proposée est examinée par l 'intermédiaire de la comparaison avec la solution exacte du problème.L'épargne informatique est illustrée pour la dispersion acoustique sur une sphère pour des nombres de vague et l'ordre différents de bases de ondelette.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.015
GPT teacher head0.232
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations3
Published2006
Admission routes1
Has abstractyes

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