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Record W2358835247

Experimental Study on Layout Designs for General Interface in Process Plant for Process Plants

2008· article· en· W2358835247 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

VenueMachine Design and Research · 2008
Typearticle
Languageen
FieldEngineering
TopicIndustrial Vision Systems and Defect Detection
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsInterface (matter)WorkloadProcess (computing)Context (archaeology)Measure (data warehouse)Fault (geology)Computer scienceInterface designReliability engineeringEngineering drawingSimulationEngineeringData miningHuman–computer interactionOperating system
DOInot available

Abstract

fetched live from OpenAlex

Operation safety in a process plant is strongly related to human-machine interface design and management. This paper presents an experimental study on the layout design of the interface,three kinds of layout interfaces in the application context of the process plant were proposed,and they were called S,SS,and NS interface,respectively. The conceptual design of the three interfaces followed the FBS methodology,and the layout was based on the PCP. In the experiment,three general classes of tasks were considered,namely normal control operation,fault detection and fault diagnosis. Two categories of measures were used:the performance measure and the subjective measure. The major results obtained from the experiment are:(1) NS interface is the most effective one for fault detection; besides,it has the lowest mental workload; (2) S interface is the best for the normal operation; (3) there appears no significant difference in the fault diagnosis for all these three interfaces. Overall,the experimental study suggests that the NS interface should be used in practice.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.225
GPT teacher head0.424
Teacher spread0.199 · 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