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Record W1569773184 · doi:10.1109/icit.2015.7125422

Wireless pulse echo interrogation of an AC electric potential resonator sensor

2015· article· en· W1569773184 on OpenAlexafffund
Mana Yazdani, D. J. Thomson, Behzad Kordi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsUniversity of Manitoba
FundersMitacsManitoba HydroUniversity of Manitoba
KeywordsResonatorInterrogationRadio frequencySIGNAL (programming language)Pulse repetition frequencyAcousticsPulse (music)VaricapResonance (particle physics)Q factorElectrical engineeringMaterials sciencePhysicsOptoelectronicsTelecommunicationsVoltageCapacitanceEngineeringComputer scienceElectrodeRadarAtomic physics

Abstract

fetched live from OpenAlex

In this paper, a wireless interrogation method based on pulse-echo technique is demonstrated for passive resonator based sensors. This technique can be employed for the measurement of time varying measurands. The measurand studied in this paper is a 60 Hz AC electric potential that varies the resonance frequency of a passive, resonator sensor. The resonance frequency shifts in response to applied potentials due to a varactor that is coupled to the cavity. The interrogator sends radio frequency pulses to the resonator and records the ringback received from the resonator. The wireless interrogation system is designed for the frequency range of 2400-2500 MHz in the ISM band. The pulses that contain the RF signal have a repetition frequency of 1.5 MHz for a resonator with a quality factor of 500. The maximum interrogation distance is then theoretically calculated as 15.75 m for a maximum resolution of 20 kHz corresponding to a potential shift of 100 mV.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.484

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 head0.012
GPT teacher head0.225
Teacher spread0.212 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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