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Record W2770150997 · doi:10.1109/tap.2017.2778015

Theory of Polarization-Selective Coupling and Its Application to Design of Planar Orthomode Transducers

2017· article· en· W2770150997 on OpenAlexaff
Ahmed A. Sakr, Walid Dyab, Ke Wu

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2017
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsPlanarPolarization (electrochemistry)TransducerCoupling (piping)PhysicsAcousticsComputer scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

With the rapid and continuous development of new generations of wireless technologies and networks, exploring the underutilized millimeter-wave (mm-wave) band becomes inescapable. Polarization diversity has been an essential factor in the performance and capacity enhancement of various wireless systems including cellular networks. Accordingly, the design and development of dual-polarized antenna feeding structures in the mm-wave band is a must. In this paper, a compact wideband orthomode transducer design in the Ka-band is proposed and explored. The proposed architecture and design are based on a forward mode polarization-selective coupling strategy between two unconventional waveguides. These special waveguides are a combination between two types of guiding structure, namely, nonradiative dielectric waveguide and substrate-integrated waveguide. Polarization-selective coupling can be achieved in these structures due to different mechanisms by which orthogonally oriented modes are guided. Theoretical coupling levels of 0 dB are possible in the designed structure. Analytical analysis and design steps are given in detail. This analysis facilitates a complete control on the single-mode operation for each polarization. This control, besides the structure being planar, represents the main advantages of the proposed structure. Finally, a prototype is implemented and measured where an excellent agreement is achieved with the simulation results.

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 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.874
Threshold uncertainty score0.373

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 head0.016
GPT teacher head0.224
Teacher spread0.208 · 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 teacher head, 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

Citations19
Published2017
Admission routes1
Has abstractyes

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