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Record W2897245098 · doi:10.1109/lmwc.2018.2860596

A Dual-Mode Split-Ring Resonator to Eliminate Relative Humidity Impact

2018· article· en· W2897245098 on OpenAlexafffund
Mohammad Abdolrazzaghi, Sabreen Khan, Mojgan Daneshmand

Bibliographic record

VenueIEEE Microwave and Wireless Components Letters · 2018
Typearticle
Languageen
FieldEngineering
TopicMicrowave and Dielectric Measurement Techniques
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsResonatorMicrowaveDual modeRelative humidityResonance (particle physics)Sensitivity (control systems)Materials scienceAnalytical Chemistry (journal)HeptanePhysicsOptoelectronicsComputer scienceElectronic engineeringChemistryTelecommunicationsEngineeringAtomic physicsOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

In this letter, a compact resonant-based dual-mode microwave sensor is proposed, aimed to eliminate the erroneous effect of relative humidity (RH) in microwave chemical sensing within the uncontrolled environment. A single split-ring resonator (SRR) is employed as the sensor core and the first resonance (f1~ 0.552 GHz) and the second resonance (f2~ 1.03 GHz) of the resonator are utilized to calibrate the potential measurement error arising from ambient RH. Simulations of the sensor's design and sensitivity using the finite-element method were performed and presented, which are further confirmed by measurements for resonant profile variation considering RH change of 5%-70%. Using the proposed technique, SRR size reduction of 50% is achieved. In addition, common chemical materials of methanol, ethanol, 2-Isopropanol (IPA), and heptane are successfully detected, achieving clear distinction from the impact of external humidity.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.022
GPT teacher head0.258
Teacher spread0.236 · 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

Citations42
Published2018
Admission routes2
Has abstractyes

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Same venueIEEE Microwave and Wireless Components LettersSame topicMicrowave and Dielectric Measurement TechniquesFrench-language works237,207