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Resonator Substrate-Integrated Waveguide (SIW) Sensor for Measurement of AC Electric Fields

2018· article· en· W2895822489 on OpenAlexaff
Amirmasoud Amirkabiri, Greg E. Bridges, Behzad Kordi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsResonatorVaricapCapacitanceOptoelectronicsMaterials scienceWaveformElectric fieldDiodeResonance (particle physics)Electrical engineeringWaveguideSubstrate (aquarium)Radio frequencyAcousticsPhysicsVoltageEngineeringElectrode

Abstract

fetched live from OpenAlex

In this paper, a wireless, passive electric field sensor that is based on a substrate-integrated waveguide (SIW) resonator is designed, fabricated, and evaluated. When exposed to an external electric field, the resonance frequency of the resonator shifts due to the variation of the capacitance of a diode varactor that is mounted on the sensor. The sensor is designed to work in the ISM band and demonstrates a high loaded quality factor of more than 200. An interrogation system has been developed that is capable of rapidly measuring the resonance frequency of the resonator and determine the waveform of the external electric field at a rate of 100 kHz. The interrogator sends pulses of radio frequency signals to the sensor and determines the resonant frequency from the ring back that is emitted by the resonator.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.023
GPT teacher head0.233
Teacher spread0.210 · 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 teacher head, 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

Citations3
Published2018
Admission routes1
Has abstractyes

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