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Record W3148724178

Study and Fabrication of IoT Enabled VAWT

2019· article· en· W3148724178 on OpenAlexaff
Hanamant Yaragudri, Raghav V. Rao, Shashank R. Shankar, P Sai Sri Raj, Ashwanth Ramesh

Bibliographic record

VenueSSRN Electronic Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicBelt Conveyor Systems Engineering
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsVertical axis wind turbineRenewable energyTurbineWind powerTurbine bladeInternet of ThingsMarine engineeringEnvironmental scienceAutomotive engineeringMeteorologyEngineeringAerospace engineeringComputer scienceElectrical engineeringComputer securityGeography
DOInot available

Abstract

fetched live from OpenAlex

The rapid depletion of fossil fuels has resulted in the gradual shift towards renewable sources of energy, such as wind energy but nevertheless the efficiency of traditional wind mills is only in the range of 30-40%. In order to counter this defect, the technology of Vertical Axis Wind Turbine was developed (VAWT). As the name suggests VAWT is a turbine whose axis is vertically mounted. This produces a drastic change in the efficiency of the device. However, during adverse conditions of weather, extreme wind speeds can have a detrimental effect on the blades of the turbine. This project focuses on minimizing the damage caused to the turbine blades by reducing the surface area of the blade exposed to the wind by the concept of furling. The furling action is actuated remotely over the internet by the concept of Internet of things (IOT).

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.004
GPT teacher head0.187
Teacher spread0.183 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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