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Record W2031041243 · doi:10.1109/antem.2010.5552497

High-efficiency balanced phase-reversal antennas: Principle, bandwidth enhancement, frequency tuning, and beam scanning

2010· article· en· W2031041243 on OpenAlexaff
Ning Yang, Christophe Caloz, Ke Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsStriplineDipole antennaOpticsReflective array antennaRadiation patternPhysicsReconfigurable antennaDirectional antennaBandwidth (computing)Antenna measurementAntenna (radio)Antenna efficiencyElectronic engineeringElectrical engineeringSlot antennaComputer scienceEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Modern wireless systems require low-profile antennas for high integration and low cost. Moreover, balanced antennas with differential configurations have the advantages of easy integration and low cross-polarization. This talk presents a class of novel printed balanced phase-reversal antennas with small lateral footprint and interesting properties. This type of antenna may be regarded as an evolution of Franklin-type antennas. It consists of a plurality of balanced transmission line sections interconnected by phase reversing crossovers having two functions: small dipole radiators and ideal 180° phase shifters. Due to the balanced configuration of the antenna, only the crossovers radiate, and the antenna is subsequently modeled as a serial array of radiation resistances. A six-element coplanar stripline (CPS) array is demonstrated theoretically and experimentally, with measured 9.3 dBi of gain for bidirectional radiation and 12.5 dBi of gain for unidirectional radiation with a back reflector.

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 score0.003

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.239
Teacher spread0.231 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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