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A Novel Antenna Array with a User Flexible Metasurface

2023· article· en· W4386952399 on OpenAlexaff
Pranjal Wadhwa, Dennis D. Giannacopoulos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsAntenna (radio)Computer scienceAntenna gainRotation (mathematics)Communications satelliteMicrostrip antennaAcousticsPhysicsElectronic engineeringEngineeringTelecommunicationsAntenna efficiencySatellite

Abstract

fetched live from OpenAlex

This paper is completed in two phases. The first phase includes the designing of the novel single element microstrip patch antenna. Operation of this single element antenna happens in three frequency bands presenting its multiband characteristics. The applications of the antenna extend to the sectors of meteorological satellites and earth exploration satellites in X-Band; radar and satellite communication in K-Band; radar communication along with 5G communication in Ka-Band. The issue with the single element antenna is its low gain. To solve this concern, the single element antenna is converted into a two-element antenna array which plays a necessary role to improve the gain by a huge amount. When a Frequency Selective Surface (FSS) as well as a Normal Metasurface (without rotation of unit cells) is implemented along with the designed novel antenna array, a gain as high as 11.16 dBi is achieved. The second phase of the paper involves creating a novel User Flexible Metasurface. This metasurface is designed using circular unit cells. The orientation of these unit cells is changed by turning the unit cells in a circular direction along their circular axis at different angles and the gain is studied for each of these arrangements. These various unique orientations provide better gain as compared to the normal existing metasurface (without rotation of unit cells). After all these simulations, a novel empirical formula has also been designed for comparison between the theoretical (calculated) gain as well as simulated gain.

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 score0.004

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 communication0.0010.001
Open science0.0010.001
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 head0.022
GPT teacher head0.218
Teacher spread0.196 · 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
Published2023
Admission routes1
Has abstractyes

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