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Record W4327518370 · doi:10.4236/ojapr.2023.111001

Miniaturized Electronically Steerable Parasitic Array Antenna

2023· article· en· W4327518370 on OpenAlexaff
Shafaq Kausar, Ahmed Kausar, Hani Mehrpouyan, Muhammad N.S. Hadi, Salahuddin Tariq

Bibliographic record

VenueOpen Journal of Antennas and Propagation · 2023
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAntenna (radio)Monopole antennaPassive radiatorAntenna measurementDipole antennaOmnidirectional antennaAntenna gainDirectional antennaRadiator (engine cooling)PhysicsMulti-band deviceElectrical engineeringOpticsAntenna factorAcousticsElectronic engineeringEngineering

Abstract

fetched live from OpenAlex

In this article we propose a miniaturized dual-band electronically steerable parasitic array radiator (ESPAR) antenna. The antenna can generate up to two steerable beams. The beam-steering range of the proposed antenna is 360˚ in the azimuth plane. The antenna’s eual-band coverage includes the frequency ranges from 2.3 GHz to 2.53 GHz and from 2.9 GHz to 3.7 GHz. The antenna consists of six folded parasitic monopole elements surrounding an active conical element. The folded monopole element design offers three times lower antenna height than that of the conventional ESPAR antennas. The active element has conical shape and it is larger in length than the parasitic monopole elements, this enables the dual-band operation. Thus, the proposed design is not only smaller than the conventional ESPAR antennas but it also achieves dual-band operation. Despite its compact design, the antenna has a peak gain of 6.3 dBi, which is equivalent to the gain of conventional ESPAR antennas. These characteristics make the antenna a good candidate for next generation communication systems.

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)0.001
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: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.015
GPT teacher head0.249
Teacher spread0.234 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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