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Record W2053813838 · doi:10.4236/sgre.2011.23028

Energy Consumption Control of an Air Conditioner Using Web Services

2011· article· en· W2053813838 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSmart Grid and Renewable Energy · 2011
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAir conditioningSmart gridEnergy consumptionControl (management)Thermal comfortEnergy managementGridArchitectural engineeringAutomotive engineeringInformation and Communications TechnologyConsumption (sociology)EngineeringEnergy (signal processing)TelecommunicationsComputer scienceElectrical engineeringWorld Wide Web

Abstract

fetched live from OpenAlex

Air-conditioning (AC) systems have the highest power consumption among the appliances and consumer devices used at residential homes and buildings. Reducing their energy use will lower peak time usage and lower CO2 emissions. Recently, employment of the Information and Communications Technologies (ICT) to the power grid has smartened the grid. In the smart grid new opportunities emerge for AC energy consumption control. The aim of this paper is to reduce the air conditioning energy consumption of residential customers. It proposes an architecture that provides easy management and control using sensor network web services. A simulation thermal model of a house considers house data and outside temperature is presented. Simulation results showed a proposed temperature control method can have significant energy saving while maintaining customer comfort.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.969

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)0.0000.000

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 head0.012
GPT teacher head0.186
Teacher spread0.174 · 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