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Microwave Imaging with the use of Time-Modulated Metasurface Enclosures

2022· article· en· W4308096952 on OpenAlexaff
Mario Phaneuf, Puyan Mojabi

Bibliographic record

Venue2022 Sixteenth International Congress on Artificial Materials for Novel Wave Phenomena (Metamaterials) · 2022
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsEnclosureMicrowave imagingPermittivityInterference (communication)MicrowaveCoupling (piping)Electromagnetic interferenceOpticsTime domainAcousticsPhysicsNoise (video)Electromagnetic shieldingMaterials scienceComputer scienceOptoelectronicsTelecommunicationsDielectric

Abstract

fetched live from OpenAlex

We propose a time-modulated metasurface enclosure for microwave imaging to shield the imaging domain from outside interference and to enable creating quantitative images of the relative complex permittivity profile of the object being imaged under the Sommerfeld radiation boundary condition without the necessity to utilize high-loss coupling fluids. This is achieved by a metallic-backed time-modulated metasurface enclosure that spreads the reflected power over a spectrum of frequencies, thus suppressing the enclosure reflections at the imaging frequency so as to emulate the Sommerfeld radiation boundary condition. This allows for lower-loss coupling fluids to be used, which can then enhance the signal to noise ratio of the data. The validity of the approach is demonstrated with an imaging problem using synthetic data.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.000
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 communication0.0000.001
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 head0.035
GPT teacher head0.238
Teacher spread0.203 · 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 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

Citations4
Published2022
Admission routes1
Has abstractyes

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Same venue2022 Sixteenth International Congress on Artificial Materials for Novel Wave Phenomena (Metamaterials)Same topicMicrowave Imaging and Scattering AnalysisFrench-language works237,207