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Record W2904037184 · doi:10.1109/antem.2018.8573040

High Gain High Dense Dielectric Patch Antenna Using FSS Superstrate for Millimeter-Wave Applications

2018· article· en· W2904037184 on OpenAlexaff
Muftah Asaadi, Abduladeem Beltayib, Abdel-Razik Sebak

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsAntenna gainAntenna apertureRadiation patternPatch antennaAntenna measurementAntenna efficiencyAntenna factorMaterials scienceOpticsMicrostrip antennaExtremely high frequencyAntenna (radio)OptoelectronicsPhysicsTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

High gain low profile linearly polarized square dense dielectric (DD) patch antenna using a frequency selective surface (FSS) superstrate layer is proposed. The implemented antenna is designed, and excited by aperture coupled feeding technique. The DD patch is used as a radiated element. An array of frequency selective surface FSS is used to enhance the gain of the antenna. The antenna gain is enhanced by 10 dBi. The implemented antenna obtained a gain of about 17.78 dBi at 28 GHz with radiation efficiency of 90 %. Furthermore, it has a bandwidth of about 9 %. It has a good radiation performance. For some attractive advantages such as low profile, low cost, light weight, small size, and ease of implementation, the proposed antenna is a good candidate for millimeter wave wireless communications.

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 score0.465
Threshold uncertainty score0.732

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 head0.033
GPT teacher head0.250
Teacher spread0.217 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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