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Record W2903698161 · doi:10.1109/ecce.2018.8557570

A Multi-Output AC/DC Converter for LED Grow Lights

2018· article· en· W2903698161 on OpenAlexaff
Rahil Samani, Dawood Shekari, Hamid Pahlevani, Majid Pahlevani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTopology (electrical circuits)Forward converterBoost converterDetectorPower (physics)Light intensityFlyback converterLED lampComputer scienceLight-emitting diodeElectronic engineeringVoltageElectrical engineeringPhysicsEngineeringOptics

Abstract

fetched live from OpenAlex

This paper presents a new LED grow light structure based on a multi-output AC/DC converter with an embedded light detector and the control systems. The proposed multi-output AC/DC converter uses the primary side as well as secondary side control in order to regulate the light intensity and the light spectrum of the grow light. In addition, a light detector is embedded in the LED grow light to continuously feedback various parameters to the control system. The power circuit of the proposed AC/DC converter is based on a single-stage power circuit topology, which combines a bridge-less Power Factor Correction (PFC) topology and a resonant converter with multiple outputs. The control system of the AC/DC converter ensures the optimal production of light intensity and light spectrum in order to optimize the plant growth. Simulation and experimental results from a 600-watt LED grow light prototype verifies the feasibility of the proposed circuitry and demonstrate its superior 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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
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 score0.184
Threshold uncertainty score0.998

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)0.0030.000

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 head0.268
Teacher spread0.243 · 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 teacher head, not a consensus.

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

Citations4
Published2018
Admission routes1
Has abstractyes

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