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Dual Band Antenna Design Using Pixeled DGS for Energy Harvesting Applications

2022· article· en· W4280629368 on OpenAlexaff
Mohammed Cherif Derbal, Mohammed Farouk Nakmouche, Mourad Nedil, Allam Amma, Diaa E. Fawzy, Mohamed Fathy Abo Sree

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsMulti-band deviceAntenna (radio)Computer scienceEnergy harvestingElectronic engineeringAntenna measurementDirectional antennaElectrical engineeringDual (grammatical number)Energy (signal processing)AcousticsPhysicsEngineeringTelecommunications

Abstract

fetched live from OpenAlex

This letter describes a dual-band antenna for energy harvesting applications at 3.5 GHz and 5.8 GHz utilizing a multi-objective Genetic Algorithm (GA). An optimized Defected Ground Structure (DGS) has been etched in the patch antenna's ground to achieve a dual-band response. Moreover, the GA allows obtaining a maximum gain in both frequency bands. The proposed antenna has a good gain of 7.22 dBi and 6.18 dBi at 3.5 GHz and 5.8 GHz. An experimental validation is conducted using ROHDE & SCHWARZ ZVB20 network analyzer, and a good agreement with the simulation result is obtained. Therefore, this antenna is suitable for Wi-Fi energy harvesting 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

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)0.0000.000

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 head0.033
GPT teacher head0.224
Teacher spread0.191 · 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
Published2022
Admission routes1
Has abstractyes

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