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Record W2800552107 · doi:10.1109/map.2018.2819970

A Dual Reconfigurable Printed Antenna: Design Concept and Experimental Realization

2018· article· en· W2800552107 on OpenAlexaff
Chinmoy Saha, Latheef A. Shaik, Rajesh Muntha, Yahia M. M. Antar, Jawad Y. Siddiqui

Bibliographic record

VenueIEEE Antennas and Propagation Magazine · 2018
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsReconfigurable antennaAntenna (radio)Radiation patternMonopole antennaAntenna measurementCoplanar waveguideComputer scienceDipole antennaElectrical engineeringElectronic engineeringAntenna efficiencyEngineeringAcousticsPhysicsTelecommunications

Abstract

fetched live from OpenAlex

In this article, we demonstrate the design concept and experimental realization of a dual reconfigurable printed antenna. A single coplanar waveguide (CPW)-fed printed monopole antenna can provide a reconfigurable ultrawideband (UWB)-notched or narrow-band (NB) response, depending on the status of the switches and the position of the split ring resonators (SRRs) in the CPW feed region of the antenna. The rectilinear movement of the superstrate, printed with various pairs of SRRs of differing dimensions, loaded in the feed region of the antenna, provides the reconfigurable functionalities. The position of the superstrate is controlled by a commercial servo motor programmed by a microcontroller. The antenna, along with the additional accessories required to actuate the mechanical movement, are fabricated and characterized using impedance and radiation pattern measurements. The measured results for both reconfigurable cases provide a good correspondence with the simulated results and the theoretical estimation. The proposed antenna can be used as a reconfigurable communicating antenna module of the cognitive radio (CR) system.

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 score0.866
Threshold uncertainty score0.685

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 head0.020
GPT teacher head0.239
Teacher spread0.219 · 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

Citations12
Published2018
Admission routes1
Has abstractyes

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