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Record W4367297917 · doi:10.1049/mia2.12366

A single layer wideband Vivaldi antenna with a novel feed structure

2023· article· en· W4367297917 on OpenAlexaff
Farhan A. Ghaffar, Noben Kumar Roy, Atif Shamim

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2023
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsLakehead UniversityBarrie Urology Group
Fundersnot available
KeywordsVivaldi antennaBandwidth (computing)Antenna efficiencyWidebandElectronic engineeringElectrical engineeringPrinted circuit boardAntenna measurementComputer scienceEngineeringMaterials scienceRadiation patternOptoelectronicsAntenna (radio)Telecommunications

Abstract

fetched live from OpenAlex

Abstract An increase of 7 GHz in the industrial, scientific and medical ISM band around 60 GHz has opened it up for many modern wireless applications such as 5G. This means that new component designs that can cater for this large bandwidth are the need of the hour. The design of a large bandwidth, completely planar and high gain novel Vivaldi antenna is presented. Being a travelling wave antenna and implemented using single metal layer make it an excellent candidate for not only Printed Circuit Board based applications but also the lossy Complementary Metal Oxide Semiconductor technology. For the first time, the feed of the antenna is integrated on the same conductor layer as the antenna itself. Using this design technique the problem of thin gap between the metal layers has been mitigated. The final measured results show that the antenna goes above and beyond ISM band with excellent matching performance from 55 to 84 GHz. A high gain of 7 dBi is maintained over a bandwidth of 57–75 GHz with a radiation efficiency of almost 80%. The results show that the design is quite suitable for integration in a millimetre‐wave transceiver system that can support high data rate applications.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
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
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.208
Teacher spread0.193 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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