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Record W2318168021 · doi:10.1109/tap.2014.2345581

Design and Analysis of SIW Cavity Backed Dual-Band Antennas With a Dual-Mode Triangular-Ring Slot

2014· article· en· W2318168021 on OpenAlexaff
Tao Zhang, Wei Hong, Yan Zhang, Ke Wu

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2014
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
FundersNational Natural Science Foundation of China
KeywordsDual modeMulti-band deviceSlot antennaPhysicsWaveguidePlanarRing (chemistry)Topology (electrical circuits)Mode (computer interface)Electrical impedanceAntenna (radio)OpticsDirectional antennaComputer scienceElectrical engineeringElectronic engineeringTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Substrate integrated waveguide (SIW) cavity backed dual-band triangular-ring slot (TRS) antennas are proposed for planar integration. First, a low profile dual band 45$^{\circ}$linearly polarized (LP) antenna is designed and analyzed. The dual-mode TRS is proposed and developed by simultaneously exciting the mode of the slot and the mode of the patch inside the slot. To minimize the antenna size, the lowest mode (TE110 mode) of the SIW cavity is adopted to excite the TRS. The$-$10 dB impedance bandwidth at the higher band is 5.9%, 58.3% wider than that of the conventional SIW cavity backed slot antenna. The interactions of the SIW cavity, the slot mode and the patch mode are analyzed with circuit models and verified by full wave simulations, which provides a new insight into the SIW cavity backed antennas. Then, by exciting a pair of the 45$^{\circ}$LP antennas with an SIW coupler, a circularly polarized (CP) dual band antenna with a small frequency ratio of 1.26 is developed. The two antennas are fabricated and tested, and the measured and simulated results agree well.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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

Citations150
Published2014
Admission routes1
Has abstractyes

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