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Record W2886212354 · doi:10.1109/mwsym.2018.8439532

Magneto-Electric-Dipole-Based Leaky-Wave Radiating Structure with Reduced Frequency-Dependent Beam Squint

2018· article· en· W2886212354 on OpenAlexaff
Yue-Long Lyu, Fan‐Yi Meng, Ke Wu, Qun Wu, Guohui Yang, Cong Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsBeam (structure)DipolePhysicsFrequency bandOpticsMagnetoRadiationPhase (matter)Radio frequencyMain lobeElectrical engineeringVoltageTelecommunicationsBandwidth (computing)Computer scienceEngineering

Abstract

fetched live from OpenAlex

Frequency-induced beam squint is probably the biggest hurdle in some cases that limits the application of leaky-wave antennas (LWAs) and leaky-wave radiating structures (LWRSs) to communication systems. In this paper, we derive a frequency-phase condition of guided-wave radiation elements in an LWA or LWRS to prevent beam squint from frequency scanning. It is found out that magneto-electric (ME) dipoles can be used as radiation elements which possess the required frequency-phase condition in a considerable wide band. Over this band of interest, the main lobe direction of the obtained LWA or LWRS based on the ME dipole can be constant. A simulated LWA prototype demonstrates its beam is fixed at -14° from 16.9 GHz to 17.9 GHz with a well suppressed effect of beam squint over the operation band.

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 score0.001
Threshold uncertainty score0.003

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.187
Teacher spread0.179 · 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
Published2018
Admission routes1
Has abstractyes

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