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The use of warning lights and siren by the ambulance crew in the Universiti Kebangsaan Malaysia Medical Centre

Ismail AK, Mohd Salleh NI, Hamdan NA, Mohd Jawi MI, Abdul Razak SN, Md Jamal S, et al.

Eur J Emerg Med, 2012 Dec;19(6):408-9.
PMID: 22343753 DOI: 10.1097/MEJ.0b013e328351e62e
Matched MeSH terms: Noise, Transportation*
Fulltext A vision of the environmental and occupational noise pollution in Malaysia

Yuen FK

Noise Health, 2014 Nov-Dec;16(73):427-36.
PMID: 25387540 DOI: 10.4103/1463-1741.144429

Environmental noise remains a complex and fragmented interplay between industrialization, population growth, technological developments, and the living environment. Next to the circulatory diseases and cancer, noise pollution has been cited as the third epidemic cause of psychological and physiological disorders internationally. A reliable and firm relationship between the cumulative health implications with the traffic annoyance and occupational noise has been established. This agenda has called for an integrated, coordinated, and participatory approach to the reliable protection of noise interference. Despite several fragmented policies, legislation and global efforts have been addressed; the noise pollution complaints have been traditionally neglected in developing countries, especially in Malaysia. This paper was undertaken to postulate an initial platform to address the dynamic pressures, gigantic challenges, and tremendous impacts of noise pollution scenario in Malaysia. The emphasis is speculated on the traffic interference and assessment of industrial and occupational noise. The fundamental importance of noise monitoring and modeling is proposed. Additionally, the confronting conservation program and control measure for noise pollution control are laconically elucidated.

Matched MeSH terms: Noise, Transportation/adverse effects; Noise, Transportation/legislation & jurisprudence; Noise, Transportation/prevention & control*
Vehicular traffic noise prediction and propagation modelling using neural networks and geospatial information system

Ahmed AA, Pradhan B

Environ Monit Assess, 2019 Feb 26;191(3):190.
PMID: 30809746 DOI: 10.1007/s10661-019-7333-3

This study proposes a neural network (NN) model to predict and simulate the propagation of vehicular traffic noise in a dense residential area at the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia. The proposed model comprises of two main simulation steps: that is, the prediction of vehicular traffic noise using NN and the simulation of the propagation of traffic noise emission using a mathematical model. First, the NN model was developed with the following selected noise predictors: the number of motorbikes, the sum of vehicles, car ratio, heavy vehicle ratio (e.g. truck, lorry and bus), highway density and a light detection and ranging (LiDAR)-derived digital surface model (DSM). Subsequently, NN and its hyperparameters were optimised by a systematic optimisation procedure based on a grid search approach. The noise propagation model was then developed in a geographic information system (GIS) using five variables, namely road geometry, barriers, distance, interaction of air particles and weather parameters. The noise measurement was conducted continuously at 15-min intervals and the data were analysed by taking the minimum, maximum and average values recorded during the day. The measurement was performed four times a day (i.e. morning, afternoon, evening, and midnight) over two days of the week (i.e. Sunday and Monday). An optimal radial basis function NN was used with 17 hidden layers. The learning rate and momentum values were 0.05 and 0.9, respectively. Finally, the accuracy of the proposed method achieved 78.4% with less than 4.02 dB (A) error in noise prediction. Overall, the proposed models were found to be promising tools for traffic noise assessment in dense urban areas.

Matched MeSH terms: Noise, Transportation
Fulltext A profile of noise sensitivity on the health-related quality of life among young motorcyclists

Ali A, Hussain RM, Dom NC, Md Rashid RI

Noise Health, 2018 4 21;20(93):53-59.
PMID: 29676296 DOI: 10.4103/nah.NAH_14_17

Introduction: Motorcycle riders with noise sensitivity (NS) may suffer from degraded health-related quality of life (HRQOL) because they are exposed to acute noise levels on a daily basis.
Materials and Methods: This study was aimed to identify the relationship between NS and HRQOL among young motorcycle riders (undergraduate university students) aged between 19 and 25 years (n = 301) through a cross-sectional questionnaire-based study, that is, Weinstein noise sensitivity scale and the World Health Organization Quality of Life. The effects of NS on HRQOL were assessed based on gender, the years of motorcycle driving experience, and noise sensitive among groups using one-way analysis of variances with an alpha value of 0.05.
Results: The results showed no significant difference in NS between males and females. On the other hand, motorcycle driving experience for <4 years displayed a higher tendency toward NS. Moreover, a significantly (P = 0.004) decreasing trend among low, moderate, and high NS with their respective HRQOL was observed, while a high NS showed significantly (P = 0.015) lower scores on the social domain of the quality of life.
Conclusion: The overall premise of the study has statistical significance and shows that individuals with high NS tend to have degraded HRQOL compared to individuals with low NS. Furthermore, in-depth studies are required from the other demographical background of participants to investigate the motorcyclist's NS and HRQOL as an integral requirement for the rider's safety and health.

Matched MeSH terms: Noise, Transportation/adverse effects*
Fulltext Noise exposure and noise induced hearing loss among Kuala Lumpur traffic point duty personnel

Thomas N, Mariah AN, Fuad A, Kuljit S, Philip R

Med J Malaysia, 2007 Jun;62(2):152-5.
PMID: 18705450 MyJurnal

Thirty-two points in Kuala Lumpur were selected where traffic personnel were on duty. Sound level readings were taken three times a day. Generally, the traffic noise levels were between 75 dBA to 85 dBA. The maximum sound level recorded was 108.2 dBA. Noise emitted by traffic equipment and vehicles were up to 133 dBA. Results of audiometric tests revealed that out of 30 who were tested, 24 or 80% were positive for noise-induced hearing loss. A questionnaire survey revealed a lack of knowledge on occupational safety and personal protective equipment.

Matched MeSH terms: Noise, Transportation/adverse effects*