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Record W2594221543

Ground plane PBGs and their effects on the performance of microstrip patch antennas

2002· article· en· W2594221543 on OpenAlexaff
M. Fallah‐Rad, L. Shafai

Bibliographic record

VenueInternational Symposium on Antenna Technology and Applied Electromagnetics · 2002
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGround planeMicrostrip antennaPatch antennaMicrostripRadiation patternAcousticsDirectional antennaNarrowbandBandwidth (computing)PhysicsOpticsAntenna (radio)TelecommunicationsComputer science
DOInot available

Abstract

fetched live from OpenAlex

Microstrip antennas are known for their advantages in lightweight, low volume, low cost, and compatibility with integrated circuits. These advantages make this antenna a useful candidate in applications such as mobile radio, satellite communications, biomedical radiators and feed elements for reflectors. An important factor in the performance of microstrip patch antennas is the ground plane. The size of the ground plane has a significant effect on the radiation pattern and the gain of the patch antenna as reported by S. Noghanian and L. Shafai [1]. In addition to the size of the ground plane, it has been shown that by etching holes in the ground plane one can control the excitation of certain modes of a microstrip patch antenna [2]. In this paper, the effects of perforations in the ground plane on the performance of narrow band and wide band patch antennas are studied. It is shown that by placing a hole or multiple holes in the ground plane of a simple patch, one can cause a shift in the resonance and an increase in the bandwidth of the antenna. In addition, placing slots in the ground plane of a narrowband microstrip can create a frequency shift of the higher modes and in the case of a wide band antenna an increase in the bandwidth.

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)0.002
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.168
Teacher spread0.163 · 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".

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

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