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Record W3139267916 · doi:10.3390/electronics10060667

High-Gain Vivaldi Antenna with Wide Bandwidth Characteristics for 5G Mobile and Ku-Band Radar Applications

2021· article· en· W3139267916 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueElectronics · 2021
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversité du Québec
FundersNational Research Foundation of KoreaNational Research Foundation
KeywordsVivaldi antennaKu bandExtremely high frequencyAntipodal pointBandwidth (computing)Antenna (radio)OpticsMaterials scienceAntenna measurementOptoelectronicsComputer sciencePhysicsTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

In this paper, antipodal Vivaldi antenna is designed for 5th generation (5G) mobile communication and Ku-band applications. The proposed designed has three layers. The upper layer consists of eight-element array of split-shaped leaf structures, which is fed by a 1-to-8 power divider network. Middle layer is a substrate made of Rogers 5880. The bottom layer consists of truncated ground and shorter mirror-image split leaf structures. The overall size of the designed antenna is confined significantly to 33.31 × 54.96 × 0.787 (volume in mm3), which is equivalent to 2λo× 3.3λo× 0.05λo (λo is free-space wavelength at 18 GHz). Proposed eight elements antenna is multi-band in nature covering Ku-bands (14.44–20.98 GHz), two millimeter wave (mmW) bands i.e., 24.34–29 GHz and 33–40 GHz, which are candidate frequency bands for 5G communications. The Ku-Band is suitable for radar applications. Proposed eight elements antenna is very efficient and has stable gain for 5G mobile communication and Ku-band applications. The simulation results are experimentally validated by testing the fabricated prototypes of the proposed design.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score0.582

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 head0.004
GPT teacher head0.190
Teacher spread0.186 · 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