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Record W4402087292 · doi:10.1177/09574565241278714

A holistic approach to different regulations for acoustic improvements in industrial facilities

2024· article· en· W4402087292 on OpenAlexaboutno aff
Muammer Yaman, Gülsu Ulukavak Harputlugil, Cüneyt Kurtay

Bibliographic record

VenueNoise & Vibration Worldwide · 2024
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessEngineeringArchitectural engineering

Abstract

fetched live from OpenAlex

With the developing technology and mechanization, the number of industrial facilities has increased. It is important for the worker’s physical and mental health to be in suitable working conditions. This paper analyses the regulations applied in the examination and evaluation of the acoustic environment in industrial facilities. The European Parliament and Council Directive, the United States, Singapore, Canada, Australia, Mexico, Japan, and WHO principles were analysed in detail. Simultaneously, analyses were conducted on the auditory perception of the workers in industrial facilities. As a result of the study, 85, 87, and 90 dBA noise exposure levels were determined for 8 h in different regulations examined. It has been determined that the regulative systems for the auditory perception of the workers in industrial facilities are insufficient. It was found necessary to develop regulation systems for evaluating noise exposure levels and the auditory perception of the workers together. It is important for the occupational health and safety of workers to develop a holistic approach in the update and revision of international regulation and to evaluate the control mechanisms within this scope. The protection of mental and physical health of the workers is presented as the most fundamental requirement. Moreover, it should be ensured that the noise control measures that can be taken (at the source, at the transmission path, and at the receiver) are formed by reducing the noise exposure and increasing the auditory perception of the workers in a positive view.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.455
Threshold uncertainty score0.740

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 head0.101
GPT teacher head0.383
Teacher spread0.282 · 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 designNot applicable
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

Citations3
Published2024
Admission routes1
Has abstractyes

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