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High gain circular microstrip antennas using TM<sub>1m</sub> modes

2015· article· en· W1934380552 on OpenAlexaff
Prateek Juyal, L. Shafai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsHigh-gain antennaMicrostripAntenna gainDielectricMicrostrip antennaBroadsideAntenna (radio)Materials scienceOpticsRadiation patternPatch antennaSubstrate (aquarium)OptoelectronicsPhysicsElectrical engineeringEngineeringAntenna efficiency

Abstract

fetched live from OpenAlex

High gain patch antennas are desirable for many applications. For patch antennas printed on common material substrate and operating in the fundamental mode, the gain is limited to a maximum of about 7.5dBi. High gain is achieved via array configurations or by superstrate loading. Array design involves complicated feed network, which introduces losses. Superstrates, which usually uses high dielectric constant material or more recently partially reflective surfaces (PRS), can be used for gain enhancement but at the cost of increased antenna height. Also, moderately high gain values limited to a maximum of 11–12dBi can be achieved via stacked patch configurations. Among the basic patch shapes, solid circular disc has been extensively studied in the past. Its low gain is inherently due to the fundamental mode (TM11) of operation. By operating the disc in higher zeros of order 1 mode i.e. TM1mmodes, where m is the electric field variation along the radial direction, higher broadside gain is expected, due to increase in electrical size of the radiating patch. But, TM1m(m≠1) modes are avoided in literature, due to the high sidelobelevel in the E-plane of radiation patterns, which make them unfit for various applications. As m increases, the number of sidelobes increases and the main beam contracts.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.003

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 head0.030
GPT teacher head0.216
Teacher spread0.187 · 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 designSimulation or modeling
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".

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Citations1
Published2015
Admission routes1
Has abstractyes

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