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Record W3120107045 · doi:10.3390/electronics10010083

Miniaturized Antipodal Vivaldi Antenna with Improved Bandwidth Using Exponential Strip Arms

2021· article· en· W3120107045 on OpenAlexafffund
Mohammad Mahdi Honari, Mohammad Saeid Ghaffarian, Rashid Mirzavand

Bibliographic record

VenueElectronics · 2021
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Technology Futures
KeywordsVivaldi antennaAntipodal pointBandwidth (computing)MiniaturizationOpticsExponential functionSlot antennaWidebandRadiation patternPhysicsAcousticsMaterials scienceAntenna (radio)EngineeringElectrical engineeringMathematicsTelecommunicationsGeometryMathematical analysis

Abstract

fetched live from OpenAlex

In this paper, a miniaturized ultra-wideband antipodal tapered slot antenna with exponential strip arms is presented. Two exponential arms with designed equations are optimized to reduce the lower edge cut-off frequency of the impedance bandwidth from 1480 MHz to 720 MHz, resulting in antenna miniaturization by 51%. This approach also improves antenna bandwidth without compromising the radiation characteristics. The dimension of the proposed antenna structure including the feeding line and transition is 158 × 125 × 1 mm3. The results show that a peak gain more than 1 dBi is achieved all over the impedance bandwidth (0.72–17 GHz), which is an improvement to what have been reported for antipodal tapered slot and Vivaldi antennas with similar size.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.200
Teacher spread0.192 · 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 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

Citations35
Published2021
Admission routes2
Has abstractyes

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