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Record W2079867198 · doi:10.1155/2014/574270

Implementation and Test of a LED-Based Lamp for a Lighthouse

2014· article· en· W2079867198 on OpenAlexfundno aff
Luca Mercatelli, D. Jafrancesco, F. Francini, D. Fontani, Elisa Sani, S. Coraggia, Marco Meucci, Paola Sansoni

Bibliographic record

VenueInternational Journal of Photoenergy · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicImpact of Light on Environment and Health
Canadian institutionsnot available
FundersInstitute of Musculoskeletal Health and ArthritisCentre National de la Recherche Scientifique
KeywordsLED lampLight-emitting diodeComputer scienceRealization (probability)Light sourcePower consumptionPower (physics)Automotive engineeringWork (physics)TelecommunicationsEmbedded systemEnvironmental scienceElectrical engineeringEngineeringOpticsMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

A novel sustainable source was developed for an existing Italian lighthouse, exploiting the light emitting diode (LED) technology and the norms evolution. The research work started with the optical design of the device, while this work concerns the realization, installation, and test of the new LED lamp. The lamp recombines multiple separated LEDs, realizing a quasipunctual localized source. After installation in the lighthouse, specific photometric tests verified that the proposed power-saving source satisfied the illumination requirements of the marine signaling norms. The advantages of the LED-based lamp are reduced energy consumption, enhanced efficiency, longer life, decreased faults, slower aging, and lower maintenance costs. The obtained LED signalling device is more durable and reliable. In the future the application of these power-saving long-life sources could be extended to other maritime signaling devices or to other traffic signs.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.287
Teacher spread0.279 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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