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Record W2002142209 · doi:10.4103/1463-1741.40824

Occupational noise in rice mills

2008· article· en· W2002142209 on OpenAlex
Prasanna Kumar, K.N. Dewangan, Amaresh Sarkar, Amrita Kumari, Banani Kar

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNoise and Health · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and Biological Electrophysiology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMillNoise (video)Environmental sciencePulp and paper industryEngineeringComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: A major occupational hazard for the workers in rice mills is the noise during the operation of various machines. A noise survey was conducted in the workrooms of eight renowned rice mills of the north-eastern region of India established during the period between 1980 and 1985. The rice mills were selected on the basis of the outcome of a walk-through noise survey involving several rice mills of the region. A noise survey map of each rice mill was drawn to identify the predominant noise sources and the causes of high noise in the workrooms of the rice mill. The sound-pressure level (SPL) in the workrooms of the rice mill varied from 78 to 92 dBA. The paddy cleaner, rubber roll sheller, compartment separator, rice cleaner, auxiliary sieve shaker and an electric motor without enclosure were found to be the predominant noise sources in the workrooms of the mill. The causes of high noise in the rice mills may be attributed to the use of a long flat belt drive, crank-and-pitman mechanism, absence of an electric motor enclosure, poor machine maintenance and inadequate acoustic design of the workroom of the rice mill. About 26% of the total labourers were found to be exposed to higher levels of noise than 85 dBA. Subjective response indicated that about 26% of the total labourers felt noise interferes in their work and about 49% labourers were of opinion that noise interferes with their conversation. CONTEXT: Noise from machines in the rice mills was found to be the major occupational hazard for the rice mill workers. The predominant noise sources need to be identified and the causes of high noise need to be studied to undertake the appropriate measures to reduce the noise level. AIMS: To identify the predominant noise sources and their distributions in rice mills, to study the causes of high levels of noise in rice mills and to examine the response of the workers towards noise. SETTINGS AND DESIGN: A noise survey was conducted in eight renowned rice mills of the north-eastern region of India. The mills were selected based on a walk-through survey conducted for the identification of rice mills with high noise. A noise survey map of each rice mill was collected by following the guidelines of Canadian Centre for Occupational Health and Safety (CCOHS). The distribution of high noise in rice mills was studied and the causes of high noise were identified. The subjective response to noise in rice mills was assessed by conducting personal interview with all the workers of the rice mills using a structured form. METHODS AND MATERIAL: The guidelines of CCOHS were followed during the noise survey. A sound level meter (SLM; Model-824) was used to record the noise level at each grid point marked at 1 m x 1 m. SPL in weighting scale "A" and the noise spectrum were recorded at each grid point for 30 s and data were stored in SLM. A noise survey map of equivalent SPL was drawn for each rice mill by drawing contour lines on the sketch of the rice mill between the points of equal SPL. The floor area in the rice mill where SPL exceeded 85 dBA was identified from the noise survey map of each rice mill to determine the causes of high levels of noise. In order to study the variation in SPL in the workroom of the rice mill throughout the shift, equivalent SPL was measured at six locations in each rice mill. The subjective response to noise in rice mills was assessed by conducting personal interview with all the workers of the rice mills using a structured form. Demographic information, nature of work, working hours, rest period, experience of working in mill, degree of noise annoyance, activity interference, and psychological and physiological effects of machine noise on the worker were asked during the interview. STATISTICAL ANALYSIS USED: Nil. RESULTS: The noise survey in eight select rice mills of the major paddy-growing regions of India revealed that the workrooms of five rice mills had SPL more than 85 dBA in the locations where workers were engaged for most of the time. The predominant noise sources in the rice mills were paddy cleaner, rubber roll sheller, compartment separator, rice cleaner, sieve shaker and an electric motor without enclosure. The causes of high noise in the rice mills may be due to the use of a long flat belt drive, crank-and-pitman mechanism, absence of an electric motor enclosure, poor machine maintenance and inadequate acoustic design of the workroom in the rice mill. In general, a well-maintained rice mill with each machine being run individually using an electric motor produced less noise than that being run using a single electric motor along with flat belt drives. The normal working period in the rice mill was 48 h/week and it was 56 h/week during the peak season of rice milling. About 26% of the total workers were exposed to noise of more than 85 dBA. Subjective response indicated that about 26% of the total workers felt noise interferes in their work and about 49% workers were of opinion that noise interferes with their conversation. CONCLUSIONS: The workers in the rice mills are exposed to high noise, which will have detrimental effect on their health. Apart from undertaking appropriate noise control measures, preventive maintenance of machines needs to be given due importance in all the rice mills.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.188

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 head0.067
GPT teacher head0.280
Teacher spread0.214 · 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