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Record W2332496526 · doi:10.1109/tap.2016.2537361

Analytical Models of Dual-Polarized Primary Matched Feeds for Offset Reflector Antennas With Low Cross-Polarization Properties at Both Asymmetry and Diagonal Planes

2016· article· en· W2332496526 on OpenAlexaff
Z. Allahgholi Pour, L. Shafai

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2016
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsOpticsOffset (computer science)Polarization (electrochemistry)DiagonalPhysicsAsymmetryMaterials scienceComputer scienceMathematicsGeometry

Abstract

fetched live from OpenAlex

Conjugate-matched primary feeds for offset reflector antennas are reviewed and investigated for both xand y-polarized cases. Tapered dual-mode circular waveguide feeds are analytically modeled to support a TE11-type mode with unequal beamwidths and the TE21-type mode for the two orthogonal polarizations. First, required mode content factors and tapering numbers of the TE11 mode are addressed for the y-polarized case in offset reflectors with different focal length-to-diameter ratios. Then, the model is appropriately tailored for the x-polarized primary feeds. It is shown that when the polarization orientation changes, the corresponding beamwidths of the TE11 mode should be swapped in the principal Eand H-planes. This is particularly important to simultaneously realize low cross-polarization levels at both asymmetry and diagonal planes, when a dual-polarized matched feed is utilized in offset reflector antennas.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.016
GPT teacher head0.218
Teacher spread0.202 · 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
GenreMethods

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

Citations16
Published2016
Admission routes1
Has abstractyes

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