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Record W2122321076 · doi:10.1109/pes.2006.1708992

Flicker representation via STFT and wavelets

2006· article· en· W2122321076 on OpenAlexaff
Alexandre B. Nassif, T. Tayjasanant

Bibliographic record

Venue2006 IEEE Power Engineering Society General Meeting · 2006
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsUniversity of Alberta
FundersUniversity of Manchester
KeywordsFlickerShort-time Fourier transformWaveletWavelet transformFourier transformHarmonic wavelet transformHarmonicComputer scienceTime–frequency analysisHarmonicsTime–frequency representationFrequency domainElectronic engineeringDiscrete wavelet transformArtificial intelligenceMathematicsFourier analysisComputer visionAcousticsEngineeringPhysicsElectrical engineeringMathematical analysis

Abstract

fetched live from OpenAlex

Flicker is an important power quality disturbance and has received an increasing concern from power system researchers. Interharmonics are the non-integral frequencies other than harmonic frequencies. Nowadays, research has shown that interharmonics and flicker seem to be closely related. To clarify this relationship, flicker is characterized in the frequency domain. The traditional Fourier-based methods have shown some drawbacks in representing non-stationary, non-periodic power signals and therefore other methods should be investigated for accomplishing this task. This paper introduces two common signal-processing approaches to assess the problem, the short term Fourier transform (STFT) and the wavelet transform. The wavelet transform has shown superior performance to circumvent the problem time-frequency resolution

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations7
Published2006
Admission routes1
Has abstractyes

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