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Record W2750006085 · doi:10.1049/iet-map.2017.0294

Dual band high‐gain antenna with beam switching capability

2017· article· en· W2750006085 on OpenAlexaff
Abdolmehdi Dadgarpour, Ahmed A. Kishk, Tayeb A. Denidni

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2017
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsInstitut National de la Recherche ScientifiqueConcordia University
Fundersnot available
KeywordsHigh-gain antennaDual (grammatical number)Antenna (radio)Antenna gainBeam (structure)Reconfigurable antennaAntenna measurementElectronic engineeringMicrostrip antennaComputer scienceMaterials sciencePhysicsAntenna efficiencyTelecommunicationsAntenna factorEngineeringOpticsOptoelectronics

Abstract

fetched live from OpenAlex

This study presents an antenna with dual‐band and high‐gain for a wireless local area network and Worldwide Interoperability for Microwave Access applications operating over 3.4–3.6 and 5–6 GHz bands. The proposed antenna is composed of three double‐sided bowtie radiators loaded by a 2 × 6 array of double split rectangular (DSR) unit cells, which leads to a considerable gain enhancement. The DSR unit cell acts as an equivalent medium with a high refractive index operating at 3.5 and 5.5 GHz. By loading 2 × 6 arrays of proposed unit cells in the off‐axis of the bowtie antenna in the H‐plane, the main beam direction is tilted by 17° and 20° at the 3.5 and 5.5 GHz bands, respectively. A prototype of the bowtie antenna loaded with asymmetric unit cells in the H‐plane is fabricated and measured. The measured results confirm the deflection of the main beam direction by 17° at 3.5 and 20° at 5.5 GHz with a peak gain of 10 and 10.5 dBi, respectively.

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 categoriesMeta-epidemiology (narrow)
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 score0.565
Threshold uncertainty score1.000

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 studies0.0010.000
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 head0.009
GPT teacher head0.210
Teacher spread0.200 · 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.

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

Citations11
Published2017
Admission routes1
Has abstractyes

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