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Record W2172988571 · doi:10.1109/ias.1995.530591

Power quality characteristics of computer loads

2002· article· en· W2172988571 on OpenAlex
D.O. Koval, C. Carter

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWaveformLine (geometry)VoltageHarmonicComputer sciencePower (physics)Electrical engineeringWorkstationQuality (philosophy)Electronic engineeringEngineeringAcousticsPhysics

Abstract

fetched live from OpenAlex

Computer loads and systems can be found in all of society's industrial, commercial and residential sectors. The nature of these loads is such that they distort the line current waveforms and in some cases can significantly distort the supply voltage waveforms causing disruption in computer system performance. The voltage (i.e., line to line, line to neutral and neutral to ground) and the phase current waveform characteristics of many computer loads are similar. Some waveform patterns remain fairly stable during loading cycles while others vary significantly and randomly. This paper presents several case studies to reveal the unique power quality characteristics of several commonly used computer systems (e.g., workstations, heating plant process computers and electron microscopes). The dominant even and odd harmonic components of the waveforms are presented and discussed in some detail. This paper also discusses the impact of the computer loads on the supply voltage waveforms.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.999

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)0.0020.000

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 head0.038
GPT teacher head0.246
Teacher spread0.208 · 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

Quick stats

Citations56
Published2002
Admission routes1
Has abstractyes

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