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Record W2066951285 · doi:10.1109/tpel.2013.2286104

Burst-Mode Resonant LLC Converter for an LED Luminaire With Integrated Visible Light Communication for Smart Buildings

2013· article· en· W2066951285 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.

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBurst mode (computing)Pulse-position modulationVisible light communicationDemodulationTransmission (telecommunications)Electronic engineeringEngineeringData transmissionPulse-width modulationElectrical engineeringModulation (music)Computer sciencePulse-amplitude modulationVoltageLight-emitting diodePulse (music)PhysicsAcousticsChannel (broadcasting)

Abstract

fetched live from OpenAlex

This study presents a digitally controlled LLC resonant dc-dc converter targeted to white LED luminaires in smart buildings. The module uses the LED array both for ambient lighting and for transmitting sensor data. Visible light communication is implemented with minimal incremental cost, by operating the LLC converter in burst mode, without causing any visible disturbance. The converter operates with a regulated average LED current, while the burst pulse timing is controlled to minimize the current disturbance and reduce the output capacitance. Variable pulse position modulation is used to modulate the data, while supporting a range of dimming settings. A digital demodulation scheme that supports variable frequency transmission is demonstrated. The 80 W, 340-400 to 23 V converter prototype has an efficiency of 95.1%. The bit error rate of the complete system is fully characterized versus distance and angle.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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