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Record W1547770549 · doi:10.1109/jestpe.2015.2436390

A Flicker-Free Single-Stage Offline LED Driver With High Power Factor

2015· article· en· W1547770549 on OpenAlex

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

VenueIEEE Journal of Emerging and Selected Topics in Power Electronics · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsQueen's University
FundersQueen's University
KeywordsRipplePower factorLED lampFlickerCapacitorLED circuitLight-emitting diodeElectrical engineeringElectronic engineeringVoltagePower (physics)Flyback transformerComputer scienceEngineeringShort circuitPhysicsTransformer

Abstract

fetched live from OpenAlex

A conventional offline single-stage light-emitting diode (LED) driver with a high power factor usually produces a significant twice-line-frequency ripple LED current, where the ripple LED current is presented as flickering to human eye. This paper introduces a ripple cancellation method to remove the twice-line-frequency voltage ripple for an offline single-stage LED driver with a power factor correction. Consequently, a dc LED current can be produced to achieve flicker-free LED driving performance. At the same time, the required storage capacitor for the proposed LED driver can be greatly reduced, and the circuit implementation to achieve ripple cancellation is simple. Thus, the overall cost of the proposed LED driver is low. The proposed LED driver also features high efficiency because of its power structure. A 35-W Flyback experimental prototype and a 10-W Buck-Boost experimental prototype have been built to validate the proposed design and demonstrate its optimal performance.

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 categoriesMeta-epidemiology (narrow)
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 score0.467
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.221
Teacher spread0.211 · 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