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Record W1488245461

Design and FDTD analysis of single-band and dual-band antennas for RFID and WiMAX applications

2011· article· en· W1488245461 on OpenAlexaff
Nazish Irfan, M.C.E. Yagoub, Khelifa Hettak

Bibliographic record

VenueInternational Conference on Software, Telecommunications and Computer Networks · 2011
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsCommunications Research Centre CanadaUniversity of Ottawa
Fundersnot available
KeywordsMulti-band deviceFinite-difference time-domain methodWiMAXReturn lossComputer scienceElectronic engineeringMicrostripMicrostrip antennaElectrical engineeringTelecommunicationsPhysicsAntenna (radio)EngineeringWirelessOptics
DOInot available

Abstract

fetched live from OpenAlex

In this paper, inset fed microstrip antennas for single band and dual-band operation are proposed. This design aims to achieve single band operation for RFID at 2.4 GHz as well as dual-band operation at 2.4 GHz for RFID and 3.5GHz for WiMAX applications. Simulation results exhibit a return loss of −27dB for single-band operation (2.4 GHz) while at and −20dB and −12.87dB for 2.4GHz and 3.5GHz (for dual-band) respectively. The Finite Difference Time Domain (FDTD) technique was used to analyze both antennas showing close agreement with the simulated results.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.053
GPT teacher head0.249
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 designSimulation or modeling
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

Citations2
Published2011
Admission routes1
Has abstractyes

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