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Record W2114199772 · doi:10.1155/2012/304816

Design of Multilevel Sequential Rotation Feeding Networks Used for Circularly Polarized Microstrip Antenna Arrays

2012· article· en· W2114199772 on OpenAlexaff
Aixin Chen, Chuo Yang, Zhizhang Chen, Yanjun Zhang, Yingyi He

Bibliographic record

VenueInternational Journal of Antennas and Propagation · 2012
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsDalhousie University
FundersNational Safety Academic FundNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsMicrostrip antennaCircular polarizationRotation (mathematics)MicrostripPhased arrayCommunications satelliteRadiation patternAntenna arrayBandwidth (computing)Electronic engineeringPatch antennaAxial ratioPolarization (electrochemistry)OpticsComputer scienceEngineeringAntenna (radio)TelecommunicationsPhysicsSatellite

Abstract

fetched live from OpenAlex

Sequential rotation feeding networks can significantly improve performance of the circularly polarized microstrip antenna array. In this paper, single, double, and multiple series-parallel sequential rotation feeding networks are examined. Compared with conventional parallel feeding structures, these multilevel feeding techniques present reduction of loss, increase of bandwidth, and improvement of radiation pattern and polarization purity. By using corner-truncated square patch as the array element and adopting appropriate level of sequential rotation series-parallel feeding structures as feeding networks, microstrip arrays can generate excellent circular polarization (CP) over a relatively wide frequency band. They can find wide applications in phased array radar and satellite communication systems.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.978
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.256
Teacher spread0.228 · 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
Published2012
Admission routes1
Has abstractyes

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