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Record W2151602425 · doi:10.1109/tap.2009.2027354

Polarization Characteristics of Multiband Loaded Microstrip Annular Ring Antennas

2009· article· en· W2151602425 on OpenAlexaff
Saeed I. Latif, L. Shafai

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2009
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMiniaturizationExcited statePhysicsPolarization (electrochemistry)MicrostripTopology (electrical circuits)OpticsElectrical engineeringAtomic physicsEngineeringChemistry

Abstract

fetched live from OpenAlex

Multifrequency operation can be obtained from the single-layer probe-fed annular ring antenna by loading it with a gap or slit. Two types of loading are studied: vertical and horizontal gap. For each case, two unloaded modes are excited around the dominant TM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</sub> mode of the ring, equally spaced on the frequency spectrum. These multiple modes are excited, when the loading is symmetric on one side of the ring along one axis, and the excitation is off-centered on another side, or vice-versa. By choosing the location of the vertical or horizontal gaps along the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">y</i> - or <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</i> -axis respectively, the polarization of each mode can be controlled. One of the loaded mode frequencies is much lower than the dominant TM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</sub> mode frequency of the annular ring, indicating a miniaturization of antenna to a great extent. Effects of substrate parameters are investigated on the loaded and unloaded mode frequencies, and a design guideline is presented. Simulation results are confirmed by measurements.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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

Citations20
Published2009
Admission routes1
Has abstractyes

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