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Record W4290034015 · doi:10.1049/rsn2.12301

Two‐dimensional synthetic aperture imaging of targets behind reinforced concrete walls

2022· article· en· W4290034015 on OpenAlex

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.

Bibliographic record

VenueIET Radar Sonar & Navigation · 2022
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsReinforced concreteMaterials scienceGeologyComposite material

Abstract

fetched live from OpenAlex

Abstract Synthetic aperture imaging of targets closely behind a reinforced concrete wall, modelled by a periodic structure by using the proper Green's function (GF) of the structure, is studied. To compute the GF accurately, using the rigorous coupled‐wave analysis (RCWA) is proposed. The radiation of a line source in the spectral domain as a summation of plane waves is represented. Illuminating the periodic structure by each plane wave, Bragg modes by RCWA are computed. Then, the GF is estimated as the superposition of all the Bragg modes' contributions. The numerical Finite Element Method results of COMSOL validate the results of our semi‐analytical approach. Having COMSOL numerically calculated backscattered fields of a target behind the wall and the simple free‐space GF, the synthetic aperture image of a target is not focussed. Employing the phase of the proper GF instead of the simple free‐space GF, the target image is successfully refocussed. The effect of the number of Bragg modes on the estimation of the GF and also uncertainties in the distances between reinforced metallic bars on the target image is investigated.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.831
Threshold uncertainty score0.535

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 head0.006
GPT teacher head0.233
Teacher spread0.226 · 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