Noise pollution is one of the common physical harmful factors in many work environments.The current study aimed to assess personal and environmental sound pressure level and project the sound-Isosonic map in one of th...Noise pollution is one of the common physical harmful factors in many work environments.The current study aimed to assess personal and environmental sound pressure level and project the sound-Isosonic map in one of the Razavi Khorasan Paste manufacture using Surfer V.14 and Noise at work V.5.0.This cross-sectional,descrip-tive study is analytical that was conducted in 2018 in the Paste factory that contains Canister,production and Brewing unit.Following ISO 9612:2009,Casella Cel-320 was used to measure personal sound pressure level,while CEL-450 sound level meter(manufactured by Casella-Cel,the UK)was employed to assess environmental sound pressure level.Statistical analyzes was done using SPSS V.18 and Linear Regression test.The sound-isosonic maps were projected using Surfer V.14 and Noise at work V.5.0.The results of assessing personal sound pressure level indicated that the highest received dose(172.21%)and personal equivalent sound level(87.36 dBA)were recorded for workers in the Canister unit.According to results of measuring of the environmental sound pressure level,out of 16 measurement stations in this unit,overall 87.5%were regarded as danger and caution areas.The lowest and highest sound pressure levels in this units were 61 dBA and 92 dBA that belong to Brewing and Canister units respectively.Results indicate Over 75%of the Canister and production units had a sound pressure level greater than 85 dBA and these two units were regarded as the most dangerous area in terms of noise pollution.It is there-fore necessary to implement noise control measures,apply hearing protection program and auditory tests among workers in these units.展开更多
Noise pollution is one of the most significant harmful physical factors in the industrial and occupational environments.Due to the high costs of exposure to excessive noise;continuous sound evaluation,propose and impl...Noise pollution is one of the most significant harmful physical factors in the industrial and occupational environments.Due to the high costs of exposure to excessive noise;continuous sound evaluation,propose and implement noise control plans in occupational environments is necessary.Thus,the present study aimed to review environmental sound measurements,drawing of noise maps,and prioritizing the engineering noise control methods using the Analytic Hierarchy Process(AHP).This study was a descriptive-analytical study that aimed to assess occupational noises and present a control plan in the City Gas Stations(CGSs)of Kerman,Iran in 2021.The present study was done in two phases.In the first phase,six CGSs were investigated to measure and evaluate the noise.In addition,the noise map of a CGS was drawn using the Surfer software.Finally,the AHP was used in the second phase of the research to prioritize the control measures.In this phase,four criteria and ten alternatives were identified.According to first phase results,the sound pressure level(SPL)of the stations varied from 76 to 98 dBA.Besides,the majority of the studied stations had a sound level higher than 85 dBA(danger zone).The second phase of the study showed that out of the four evaluated criteria,the executability criterion had the highest impact and the cost criterion had the lowest impact on the selection of control measures with a weight of 0.587 and 0.052,respectively.Based on the results of prioritization of the alternatives,using a silenced regulator(weight of 0.223)and increasing the thickness of the tube(weight of 0.023)had the highest and lowest priorities among the alternatives,respectively.The use of engineering noise control methods such as using silenced regulators was the best way to control the noises of CGSs.Additionally;it is noteworthy that AHP is a practical method for prioritizing alternatives to achieve the most accurate decision-making.The results of AHP can be of great help to health and safety experts and managers in choosing the sound展开更多
文摘Noise pollution is one of the common physical harmful factors in many work environments.The current study aimed to assess personal and environmental sound pressure level and project the sound-Isosonic map in one of the Razavi Khorasan Paste manufacture using Surfer V.14 and Noise at work V.5.0.This cross-sectional,descrip-tive study is analytical that was conducted in 2018 in the Paste factory that contains Canister,production and Brewing unit.Following ISO 9612:2009,Casella Cel-320 was used to measure personal sound pressure level,while CEL-450 sound level meter(manufactured by Casella-Cel,the UK)was employed to assess environmental sound pressure level.Statistical analyzes was done using SPSS V.18 and Linear Regression test.The sound-isosonic maps were projected using Surfer V.14 and Noise at work V.5.0.The results of assessing personal sound pressure level indicated that the highest received dose(172.21%)and personal equivalent sound level(87.36 dBA)were recorded for workers in the Canister unit.According to results of measuring of the environmental sound pressure level,out of 16 measurement stations in this unit,overall 87.5%were regarded as danger and caution areas.The lowest and highest sound pressure levels in this units were 61 dBA and 92 dBA that belong to Brewing and Canister units respectively.Results indicate Over 75%of the Canister and production units had a sound pressure level greater than 85 dBA and these two units were regarded as the most dangerous area in terms of noise pollution.It is there-fore necessary to implement noise control measures,apply hearing protection program and auditory tests among workers in these units.
文摘Noise pollution is one of the most significant harmful physical factors in the industrial and occupational environments.Due to the high costs of exposure to excessive noise;continuous sound evaluation,propose and implement noise control plans in occupational environments is necessary.Thus,the present study aimed to review environmental sound measurements,drawing of noise maps,and prioritizing the engineering noise control methods using the Analytic Hierarchy Process(AHP).This study was a descriptive-analytical study that aimed to assess occupational noises and present a control plan in the City Gas Stations(CGSs)of Kerman,Iran in 2021.The present study was done in two phases.In the first phase,six CGSs were investigated to measure and evaluate the noise.In addition,the noise map of a CGS was drawn using the Surfer software.Finally,the AHP was used in the second phase of the research to prioritize the control measures.In this phase,four criteria and ten alternatives were identified.According to first phase results,the sound pressure level(SPL)of the stations varied from 76 to 98 dBA.Besides,the majority of the studied stations had a sound level higher than 85 dBA(danger zone).The second phase of the study showed that out of the four evaluated criteria,the executability criterion had the highest impact and the cost criterion had the lowest impact on the selection of control measures with a weight of 0.587 and 0.052,respectively.Based on the results of prioritization of the alternatives,using a silenced regulator(weight of 0.223)and increasing the thickness of the tube(weight of 0.023)had the highest and lowest priorities among the alternatives,respectively.The use of engineering noise control methods such as using silenced regulators was the best way to control the noises of CGSs.Additionally;it is noteworthy that AHP is a practical method for prioritizing alternatives to achieve the most accurate decision-making.The results of AHP can be of great help to health and safety experts and managers in choosing the sound
文摘面向心脏疾病计算机辅助诊断,本文提出一种基于一维卷积神经网络和循环神经网络混合深度学习结构的心音分析方法.本结构首先利用卷积神经网络学习心脏病症在心音信号上的表征,然后通过循环神经网络处理心音信号中的时序信息进行分类,在提升心音分类正确率的同时,大幅度降低了网络参数.为验证本深度学习结构所学特征的有效性,除已有的成人心音数据集外,本文还专门构建了一个面向婴幼儿先天性心脏病的心音数据集,并通过端到端的类别响应图证明了本方法在室缺诊断时学习到的心音信号特征符合临床医师的心音听诊经验.实验结果表明,本文方法能在3153例成人心音数据分类上达到92.56%的正确率,在528例婴幼儿心音数据分类上达到97.48%正确率,模型参数仅有0.05 M.
