MétaCan
Menu
Back to cohort
Record W2991731786 · doi:10.1109/lawp.2019.2957288

Broadband Folded Reflectarray Fed by a Dielectric Resonator Antenna

2019· article· en· W2991731786 on OpenAlexaff
Jin Yang, Qiang Cheng, Mustafa K. Taher Al‐Nuaimi, Ahmed A. Kishk, Abdelhady Mahmoud

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsConcordia University
FundersNational Key Research and Development Program of China Stem Cell and Translational ResearchNational Natural Science Foundation of China
KeywordsBroadbandMicrostripBandwidth (computing)Dielectric resonator antennaOpticsMaterials scienceResonatorDielectricMicrostrip antennaPhase compensationWidebandLinearityPolarization (electrochemistry)OptoelectronicsAntenna (radio)PhysicsElectronic engineeringEngineeringTelecommunications

Abstract

fetched live from OpenAlex

In this letter, a broadband folded reflectarray (FRA) is designed and fabricated. The FRA consists of a main reflectarray, the polarizing grid, and a feeding dielectric resonator antenna embedded in its structure. With the help of the multilayered reflecting element, the main reflectarray is capable to provide 90°of polarization rotation and proper phase compensation for a linearly polarized incident wave. By altering the microstrip line length, a wide phase coverage can be obtained with a good phase linearity. To validate the FRA design, both simulations and experiments are conducted, and good agreements are obtained. The FRA accomplishes 31% matching bandwidth from 9 to 12.1 GHz. In addition, a high aperture efficiency of 50.3% and the peak gain of 28.08 dBi at 10.8 GHz is achieved. Compared with the published works, the proposed FRA is especially advantageous for low profile and good efficiency.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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

Citations24
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Antennas and Wireless Propagation LettersSame topicAdvanced Antenna and Metasurface TechnologiesFrench-language works237,207