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Record W1616671578

A review of mechanically reconfigurable antennas using smart material actuators

2011· review· en· W1616671578 on OpenAlexaff
Shahrzad Jalali Mazlouman, Alireza Mahanfar, Carlo Menon, Rodney G. Vaughan

Bibliographic record

VenueEuropean Conference on Antennas and Propagation · 2011
Typereview
Languageen
FieldEngineering
TopicDielectric materials and actuators
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsReconfigurable antennaControl reconfigurationActuatorSmart antennaAntenna (radio)Electronic engineeringLimitingComputer scienceElectrical engineeringConformal antennaDistortion (music)Directional antennaEngineeringOmnidirectional antennaEmbedded systemSlot antennaAntenna efficiencyMechanical engineeringAmplifierCMOS
DOInot available

Abstract

fetched live from OpenAlex

Mechanically reconfigurable antennas have the potential to provide a large range of antenna reconfiguration and to have a lower cost than other reconfigurable technologies. Solid state devices in the RF signal path can cause distortion and power limiting, but such issues can be averted by keeping them out of the direct RF signal path. In this paper, new smart material technologies, namely electro-active polymers and shape memory alloy actuators, are presented as potential candidates to implement mechanically reconfigurable antennas. A review of some proof-of-concept reconfigurable antenna prototypes using these technologies is presented, including the advantages and disadvantages for the antenna applications.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.070
GPT teacher head0.272
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 designNot applicable
Domainnot available
GenreReview

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

Citations18
Published2011
Admission routes1
Has abstractyes

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