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Record W2106374359 · doi:10.1109/aps.2009.5171575

Reconfigurable radiation pattern antenna based on active frequency selective surfaces

2009· article· en· W2106374359 on OpenAlexaff
Mahmoud Niroo Jazi, M.A. Habib, Tayeb A. Denidni

Bibliographic record

VenueDigest - IEEE Antennas and Propagation Society. International Symposium · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsReconfigurable antennaRadiation patternAntenna (radio)STRIPSComputer scienceRadiationDipole antennaRadiation propertiesElectronic engineeringPosition (finance)OptoelectronicsOpticsAntenna efficiencyMaterials scienceEngineeringPhysicsTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, a prototype of active frequency selective surfaces (AFSS) screen based on the simple dipole strips has been proposed for a reconfigurable radiation pattern antenna. The results achieved in the measurements confirm the expected objectives for the proposed structure. However, it has been observed that the parasitic elements created by the active elements are indeed the main problem in attainting the desired properties. Because of this, the position of bandgap significantly changes which it leads to an in complete transparent screen in one state. However, measurement results demonstrate that using this idea it is possible to achieve a reconfigurable radiation pattern. Study on this subject is undergoing to improve the performance of the antenna.

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 communication0.0000.000
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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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

Citations5
Published2009
Admission routes1
Has abstractyes

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