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Record W2909222154 · doi:10.33107/ijbte.2012.1.1.09

The effectiveness of the use of solar panels in hotels of Durres area

2012· article· en· W2909222154 on OpenAlexaff
Asllan Hajderi, Shkelqim Gjevori

Bibliographic record

VenueInternational Journal of Business & Technology · 2012
Typearticle
Languageen
FieldComputer Science
TopicSolar Radiation and Photovoltaics
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsRenewable energyEnvironmental scienceSolar energyGlobal warmingPhotovoltaic systemElectricityBoiler (water heating)Environmental engineeringEnvironmental protectionWaste managementClimate changeEngineeringEcology

Abstract

fetched live from OpenAlex

In the present study is analyzing the case of the application of solar energy with vacuum tube collectors for heating water for sanitary needs in hotels of Durres areas. In recent years there has been a special interest by the leading authorities to the EU countries and the U.S., for the use of renewable energies in general and solar energy in particular. This is mainly related with the reduction of environmental pollution from gas CO2, which directly influences the greenhouse effect and global warming. Unlike other forms of renewable energy, like wind turbines, photovoltaic panels and biomass usages, the use of solar panels for hot water, constitutes a reliable source in Albania. In the study were analyzed the types of solar panels used in our country and the world. Collector with vacuum tubes is selected for heating water, which constitute a new technology with an efficiency 40% higher than other types. For this case study were obtained tourism hotels in the coastal area of Durrës with a high level of solar intensity, which are calculated the cost for water heating with electric boiler (traditional method) and with solar panels. Results show a significant reduction of annual expenses up 3 times, compared with the use of electricity. While with interest it is the reduction of the amount of gas CO2, to achieve reduction of environmental pollution, and the reduction of global warming in general.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.259

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.260
Teacher spread0.229 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2012
Admission routes1
Has abstractyes

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