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Record W2785830304 · doi:10.1109/epec.2017.8286200

Characterization of commercial LED lamps for power quality studies

2017· article· en· W2785830304 on OpenAlex
Radwa M. Abdalaal, Carl Ngai Man Ho

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsUniversity of Manitoba
FundersManitoba HydroUniversity of Manitoba
KeywordsLED lampFlickerHarmonicsLight-emitting diodeVoltage sagVoltageElectrical engineeringPower qualityQuality (philosophy)Power (physics)Luminous fluxElectronic engineeringComputer scienceEngineeringLight sourceOpticsPhysics

Abstract

fetched live from OpenAlex

Continuous research to achieve high luminous efficiency with low cost LED lamps has widen the field of LED lighting applications, which dictates the need to study different characteristics of commercial LEDs and their impact on power quality parameters. This paper addresses the negative influence of utilizing LED lamp as a lighting source on power grid and on public health. The operation of the LED and its behavior as a nonlinear load has been further discussed. Various experimental tests that include harmonic analysis, voltage flickering voltage sag, swell and voltage harmonics have been conducted to investigate current and voltage quality issues. This paper aims at a better understanding to the characterization of commercial LED lamps in order to highlight the need for power quality improvement techniques for such an application also the need for new developments that improve LEDs internal power electronic driving circuit.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.352

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 head0.074
GPT teacher head0.371
Teacher spread0.297 · 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