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Record W4402996884 · doi:10.26866/jees.2024.5.r.254

Advanced Beam Estimation for Antennas Via Patterned Coupling-Line Detection Board in Ka-Band

2024· article· en· W4402996884 on OpenAlex
Seokyeon Hong, Seunggoo Nam, Sehwan Choi, Ji-Han Joo, Jae-Sub Han

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

VenueJournal of Electromagnetic Engineering and Science · 2024
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsLine (geometry)Coupling (piping)Ka bandBeam (structure)OpticsPhysicsMaterials scienceMathematicsGeometry

Abstract

fetched live from OpenAlex

In this research, we present an innovative method for estimating the beams of array antennas. Traditional beam analysis methods rely on placing receiving antennas in the far-field region, which requires moving or rotating the Tx or Rx, and using radiation pattern measurements. However, such methods often demand vast spatial requirements and the use of high-cost network analyzers. In contrast, the technique proposed in this study utilizes a board patterned with coupling lines strategically placed in the antenna's near-field zone. Signals intercepted by these coupling lines undergo conversion into DC voltage via a power detector situated at the line terminus. Interestingly, this method enables beam estimation solely based on the DC voltage level output of the power detector, thus offering a cost-effective and space-efficient solution that represents a significant advancement from traditional beam estimation methods.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.782
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.215
Teacher spread0.211 · 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