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Record W2016788425 · doi:10.1049/el:20081013

Smart antennas using electro-active polymers for deformable parasitic elements

2008· article· en· W2016788425 on OpenAlexaff
Alireza Mahanfar, Carlo Menon, Rodney G. Vaughan

Bibliographic record

VenueElectronics Letters · 2008
Typearticle
Languageen
FieldEngineering
TopicDielectric materials and actuators
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAntenna (radio)Impedance matchingElectrical conductorReconfigurable antennaComputer scienceControl reconfigurationElectronic engineeringSIGNAL (programming language)Electrical impedanceSmart antennaAcousticsElectrical engineeringMaterials scienceDipole antennaEngineeringPhysicsAntenna efficiencyEmbedded system

Abstract

fetched live from OpenAlex

A novel concept for implementation of smart antennas is introduced. Deformable smart materials, as parasitic elements to alter the antenna pattern, are demonstrated. Such a reconfiguration can be used for improved spectral efficiency through diversity-type techniques. The approach effectively allows replacement of much RF circuitry and the signal processing modules present in a conventional array, by simple, low-cost, low power, smart materials. A basic, proof-of-concept prototype comprising a radiating monopole and a deformable conductive strip made of ionic polymeric–metal composite is presented. The deformable conductive strip has a voltage-controlled slant angle and its close proximity to the monopole reconfigures the pattern. Physical measurements verify the operation of the antenna. The impedance matching is also discussed.

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: Empirical
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)0.0010.000

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 head0.011
GPT teacher head0.213
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

Citations27
Published2008
Admission routes1
Has abstractyes

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