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Record W2992545905 · doi:10.1049/iet-map.2019.0365

Broadband planar slot antenna using a simple single‐layer FSS stopband

2019· article· en· W2992545905 on OpenAlexaff
Belmessaoud Djaouida, Khaled Rouabah, Idris Messaoudene, Tayeb A. Denidni

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2019
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsStopbandBroadbandPlanarSimple (philosophy)Antenna (radio)Materials scienceElectronic engineeringComputer scienceAcousticsTelecommunicationsOptoelectronicsEngineeringPhysicsResonator

Abstract

fetched live from OpenAlex

In this study, the authors propose a simple structure of a new broadband planar slot antenna using a wide single‐layer frequency selective surface (FSS) stopband. The proposed design is realised in two stages. First, the performances of the FSS unit cells are investigated using the finite element method of high‐frequency structure simulator. Besides, the FSS structure considered as a stop‐band filter in the bandwidth , is also validated by computer simulation technology microwave studio. Second, this FSS reflector is combined with a miniaturised wideband planar slot antenna . The final proposed combination is also designed, optimised, fabricated and validated by measurements. The obtained results show an operating impedance bandwidth of including the Worldwide interoperability for Microwave Access band, the C band for satellite applications, and the Wireless Local Area Network band. Furthermore, the antenna provides an measured maximum gain. Compared to the same antenna without FSS, a maximum gain enhancement of is achieved by the proposed structure. In addition, the back lobes are reduced in the proposed structure by , compared to a simple antenna. The total size of the proposed antenna, integrating the FSS, is .

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
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)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.020
GPT teacher head0.223
Teacher spread0.203 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations14
Published2019
Admission routes1
Has abstractyes

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