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Record W4308589878 · doi:10.1017/s1759078722001118

Design and analysis of broadband circularly polarized compact planar antennas for 2.45 GHz RFID handheld reader applications

2022· article· en· W4308589878 on OpenAlexaff
Niraj Agrawal, A. K. Gautam, Karumudi Rambabu

Bibliographic record

VenueInternational Journal of Microwave and Wireless Technologies · 2022
Typearticle
Languageen
FieldEngineering
TopicRFID technology advancements
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGround planeOpticsCoplanar waveguidePhysicsParasitic elementPlanarBroadbandBandwidth (computing)Circular polarizationOptoelectronicsAntenna (radio)TelecommunicationsMicrowaveComputer scienceMicrostrip

Abstract

fetched live from OpenAlex

Abstract In this article, an innovative design of a broadband circularly polarized compact planar antenna for RFID (radio frequency identification) receivers is presented. The suggested structure used the concept of slots loaded parasitic element printed underneath a coplanar waveguide-fed radiator to achieve the circularly polarized (CP) radiation and size reduction. A parasitic element loaded with F-slot and L-slot, and a window-type slotted ground plane was used to achieve resonance at 2.45 GHz with right-handed circularly polarized radiation for RFID handheld reader application. Experimental results confirmed that the designed antenna of size 16.5 × 14.8 × 1.6 mm3 attained a −10 dB impedance bandwidth of 15.8% (from 2.330 to 2.716 GHz) and 3 dB AR bandwidth of 3.43% (from 2.410 to 2.494 GHz). An axial ratio of 0.43 dB was achieved in the boresight of the antenna at the 2.45 GHz RFID band. The concept of electric field distribution on the antenna was used to elaborate the excitation of CP radiation in 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: 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 science0.0000.000
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 head0.016
GPT teacher head0.254
Teacher spread0.237 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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