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Record W1487035440 · doi:10.1109/apec.2015.7104453

A scalable HB-LED driver for multi-color Adaptive lighting systems

2015· article· en· W1487035440 on OpenAlexfundno aff
Kumar Modepalli, Leila Parsa

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicImpact of Light on Environment and Health
Canadian institutionsnot available
FundersCanadian Celiac AssociationNational Science Foundation
KeywordsLED lampColor rendering indexConstant currentTopology (electrical circuits)Rendering (computer graphics)InductorComputer scienceVoltageLight-emitting diodeColor temperatureLED circuitScalabilityControl theory (sociology)Electrical engineeringPhysicsEngineeringArtificial intelligenceOptoelectronicsControl (management)

Abstract

fetched live from OpenAlex

In this paper a HB- LED driver that can drive multi-color HB-LED strings using Single Inductor Multiple Current Output (SIMCO) buck converter topology is presented. Constant current sources are required to drive LED strings due to their non-linear I-V characteristics. In the proposed topology the average current in multi-color LED strings are controlled independently by using a combination of non-linear charge control and traditional Average Current Mode Control (ACMC) from a single DC voltage source. The SIMCO buck converter is operated in Continuous Conduction Mode (CCM) with ACMC to realize a constant source feeding multi-color LED strings. Simulation and experimental results of a high color rendering index (CRI) multi-color LED lighting system with 48V DC input and 500lm output are presented.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.291
Teacher spread0.217 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations2
Published2015
Admission routes1
Has abstractyes

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