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A Fresnel Elliptical Reflector for MMW and THz Near Field Imaging

2024· article· en· W4402982489 on OpenAlexaff
Fazel Ghiasvand, Nazli Kazemi, Petr Musı́lek, Elham Baladi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsPolytechnique MontréalUniversity of Alberta
Fundersnot available
KeywordsTerahertz radiationReflector (photography)OpticsFresnel zone antennaField (mathematics)Fresnel equationsPhysicsDirectional antennaAntenna (radio)Computer scienceRefractive indexTelecommunicationsSlot antenna

Abstract

fetched live from OpenAlex

This article describes the design and simulation of a novel Fresnel elliptical reflector that can assist emerging technologies in the field of millimeter-wave and terahertz security imaging. The analytical expressions that satisfy the corresponding amplitude and phase of each section are presented in a general manner. Two different Fresnel reflectors are designed, and their performance is compared with conventional reflectors using numerical simulations based on the Comsol and Feko software packages. The simulation results confirm the proper focusing of the Fresnel reflector at the desired frequency. Furthermore, the frequency behavior of the designed reflectors has been thoroughly investigated. This study provides valuable insights into the design and simulation of Fresnel reflectors, which can significantly enhance the performance of emerging technologies in the field of millimeter-wave and terahertz security imaging.

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)0.001
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.006
GPT teacher head0.249
Teacher spread0.244 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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