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Record W2159017290 · doi:10.1109/pcc.2002.998171

A new algorithm for fast retrieval of sequence components in 3-phase networks

2003· article· en· W2159017290 on OpenAlex
Chunlin Li, F.P. Dawson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsField-programmable gate arrayMicroprocessorComputer scienceAlgorithmTransient (computer programming)Sequence (biology)Process (computing)Component (thermodynamics)Noise (video)Filter (signal processing)Field (mathematics)Phase (matter)Gate arrayVoltageElectronic engineeringComputer hardwareArtificial intelligenceEngineeringMathematicsElectrical engineering

Abstract

fetched live from OpenAlex

The paper presents a new microprocessor based technique for fast retrieval of the current and voltage sequence components based on symmetrical component theory. The two-sample delay algorithm can operate at an arbitrary sampling frequency and executes with minimal computational burden. A three-point median filter is utilized to remove the impulsive noise that appears during the transient process. Simulations show that an optimal transient performance can be achieved using the proposed technique under unbalanced situations. Finally, a field programmable gate array (FPGA) implementation has been constructed to verify the theoretical 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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.333

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 head0.025
GPT teacher head0.264
Teacher spread0.239 · 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