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IoT Enabled Phase-Cut Dimmable Power Supply for LED Fixtures

2024· article· en· W4402474545 on OpenAlexaff
Mathieu Cote, A. J. Gonsalves, K. Godbole, Ameera Abboobakar, Vijay K. Sood

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicSynthesis and properties of polymers
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsPhase (matter)Internet of ThingsBusinessElectrical engineeringComputer scienceEngineeringComputer securityChemistry

Abstract

fetched live from OpenAlex

This paper describes the design and development of an Internet of Things (IoT) enabled light-emitting diode (LED) phase-cut dimmable power supply. The FL5160MX is a robust controller that enhances flexibility with a selectable DIM mode pin to facilitate trailing-edge or leading-edge dimming. This design encompasses both hardware and software subsystems. The hardware components include an Arduino UNO Rev4 Wi-Fi, current sensor, relay, Liquid Crystal Display (LCD), AC/DC Converter, and the dimmer circuit power supply. The software component controls the circuit protection and connects to the Arduino Cloud through the IoT. The proposed concept provides an effective solution supporting leading- and trailing-edge phase-cut dimming, efficient power supply, and flexible means of control.

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 score0.138
Threshold uncertainty score0.979

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)0.0220.001

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 head0.016
GPT teacher head0.276
Teacher spread0.261 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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