What is a safe noise exposure level for the public?

2017 ◽  
Vol 141 (5) ◽  
pp. 3731-3731
Author(s):  
Daniel Fink
Author(s):  
Feifan Chen ◽  
Zuwei Cao ◽  
Emad M. Grais ◽  
Fei Zhao

Abstract Purpose Noise-induced hearing loss (NIHL) is a global issue that impacts people’s life and health. The current review aims to clarify the contributions and limitations of applying machine learning (ML) to predict NIHL by analyzing the performance of different ML techniques and the procedure of model construction. Methods The authors searched PubMed, EMBASE and Scopus on November 26, 2020. Results Eight studies were recruited in the current review following defined inclusion and exclusion criteria. Sample size in the selected studies ranged between 150 and 10,567. The most popular models were artificial neural networks (n = 4), random forests (n = 3) and support vector machines (n = 3). Features mostly correlated with NIHL and used in the models were: age (n = 6), duration of noise exposure (n = 5) and noise exposure level (n = 4). Five included studies used either split-sample validation (n = 3) or ten-fold cross-validation (n = 2). Assessment of accuracy ranged in value from 75.3% to 99% with a low prediction error/root-mean-square error in 3 studies. Only 2 studies measured discrimination risk using the receiver operating characteristic (ROC) curve and/or the area under ROC curve. Conclusion In spite of high accuracy and low prediction error of machine learning models, some improvement can be expected from larger sample sizes, multiple algorithm use, completed reports of model construction and the sufficient evaluation of calibration and discrimination risk.


1992 ◽  
Vol 30 (2) ◽  
pp. 65-76 ◽  
Author(s):  
Seyed Mohammad MIRBOD ◽  
Ryoichi INABA ◽  
Hideyo YOSHIDA ◽  
Chisato NAGATA ◽  
Yoko KOMURA ◽  
...  

2020 ◽  
Vol 185 (9-10) ◽  
pp. e1551-e1555
Author(s):  
Sean E Slaven ◽  
Benjamin M Wheatley ◽  
Daniel L Christensen ◽  
Sameer K Saxena ◽  
Robert J McGill

Abstract Introduction Noise exposure is an occupational health concern for certain professions, especially military servicemembers and those using power tools on a regular basis. The purpose of this study was to quantify noise exposure during total hip arthroplasty (THA) and total knee arthroplasty (TKA) cases compared to the recommended standard for occupational noise exposure. Materials and Methods A sound level meter was used to record cumulative and peak noise exposure levels in 10 primary THA and 10 primary TKA surgeries, as well as 10 arthroscopy cases as controls. Measurements at the distance of the surgeon were taken in all cases. In TKA cases, measurements were taken at 3 feet and 8 feet from the surgeon, to simulate the position of the anesthetist and circulating nurse, respectively. Results Time-weighted average was significantly higher in THA (64.7 ± 5.2 dB) and TKA (64.5 ± 6.8 dB) as compared to arthroscopic cases (51.1 ± 7.5 dB, P < 0.001) and higher at the distance of the surgeon (64.5 ± 6.8 dB) compared to the anesthetist (52.9 ± 3.8 dB) and the circulating nurse (54.8 ± 11.2 dB, P = 0.006). However, time-weighted average was below the recommended exposure level of 85 dB for all arthroplasty cases. Peak levels did not differ significantly between surgery type or staff role, and no values above the ceiling limit of 140 dB were recorded. Surgeon’s daily noise dose percentage per case was 1.78% for THA and 2.04% for TKA. Conclusion Noise exposure in THA and TKA was higher than arthroscopic cases but did not exceed occupational standards. A daily dose percentage of approximately 2% per case indicates that repeated noise exposure likely does not reach hazardous levels in modern arthroplasty practice.


2020 ◽  
Vol 175 ◽  
pp. 14001
Author(s):  
Mariya Balmashnova ◽  
Tatyana Sorokoumova

As a result of increase in the number of residents of megacities, the anthropogenic impact on the public, recreational and agricultural areas is increasing. Anthropogenic load causes degradation of the natural structure of the city and has a negative impact on public health. In current situation, more recreational areas are organized for residents of the city. However, the organization of recreational areas does not always comply with the population requirements. In the formation that sort of spaces, it is necessary to obtain complete and reliable information about the quality of the environment, which can only be obtained through the regular monitoring studies. This article considers a number of recreational, agricultural and public areas under the noise exposure. The spatial organization of recreational areas should be carried out taking into account the main goal of creating a comfortable architectural and planning structure of the urban environment. This article shows the insolvency of the public, recreational and agricultural areas as comfortablespaces.


Author(s):  
Grant S. Nash ◽  
Jason C. Ross ◽  
Basant K. Parida ◽  
Abdullatif K. Zaouk ◽  
Swamidas K. (John) Punwani

It is estimated that up to 9.3 million people may be impacted by locomotive horn noise and up to 4.6 million of those may be severely impacted.1 In 2009, there were over 1,900 incidents, over 700 injuries, and over 240 fatalities at highway-rail grade crossings.2 Approximately 4,000 times per year, a train and highway vehicle collide at one of over 262,000 public and private highway-rail grade crossings in the United States. Compared to a collision between two highway vehicles, a collision with a train is eleven times more likely to result in a fatality, and five and a half times more likely to result in a disabling injury. Approximately half of all collisions occur at grade crossings that are not fully equipped with warning devices. Some of the drivers involved in these collisions may have been unaware of the approaching train.3 The National Academy of Engineering Committee on Technology for a Quieter America has indicated that the public would benefit if a train horn was more directional and has recommended that research and development be undertaken to better understand the effects on safety, with benefits to the public.4 As a part of an ongoing Federal Railroad Administration (FRA)-sponsored research and development effort, the authors have developed an Acoustical Warning Device (AWD) prototype with an overall goal of maximizing safety at a grade crossing and minimizing environmental noise pollution (at the wayside and in the cabin of a locomotive in reducing railroad worker occupational hazard noise exposure). An initial prototype was created that consisted of one acoustical element. An advanced prototype is currently being developed with three acoustical elements to provide variable directivity and steering capabilities through beamforming. A digitized horn signal has been created based on characteristics from an analog air-pressure locomotive horn. The initial AWD prototype has been analyzed for detectability and noise impact area and the directivity pattern of its sound emissions have been tested. The expected performance of the advanced three-unit prototype has been evaluated based on the test results of the initial prototype and acoustic simulation modeling. During development of the initial AW D prototype, spectrograms, polar directivity plots, frequency response plots, 1/3-octave band plots, and LAeq measurements of the AWD propagation were analyzed to ensure proper functionality of the AWD, in accordance with FRA and QinetiQ North America’s (QNA) specifications. Based on acoustic simulation modeling, the advanced AWD prototype is expected to generate sound up to 110 dBA at 100 feet forward of the locomotive. The AWD prototype is expected to improve detectability and reduced environmental noise exposure to the community and locomotive cabin.


Author(s):  
Truls Gjestland

The European Regional Office of the World Health Organization (WHO, 2018) recently dramatically lowered its former (WHO, 2000) recommendations for cumulative aircraft noise exposure levels associated with risks of adverse public health effects. WHO’s recommendations, although lacking the force of law, are nonetheless of interest to aviation regulatory bodies and to the public at large. It is therefore important that WHO’s recent recommendations receive and withstand careful scrutiny. WHO’s (2018) recommendations are based on controversial assumptions, analyses and interpretations prepared by Guski et al. (2017). Gjestland (2018) identified a number of limitations of the opinions expressed by Guski et al. (2017). Guski et al. (2019) subsequently challenged some of Gjestland’s (2018) observations. This paper responds to the defenses offered by Guski et al. (2019) of the opinions expressed in their prior (2017) publication.


2020 ◽  
Vol 305 ◽  
pp. 00044
Author(s):  
Sorin Simion ◽  
Alexandru Simion ◽  
Izabella Kovacs ◽  
Vlad Lautaru

A general problem in the vicinity of industrial compressors is the noise generated in the working environment by their operation. A large number of workers suffer from hearing problems caused by exposure to high levels of noise in the workplace. Thus, legal provisions regulating occupational noise exposure aim to reduce the risk of hearing loss by reducing noise level, the most effective measures being those applied directly to the noise source combined with the use of hearing protection. Quantification of noise exposure level and mitigation of occupational hazards generated by it at each workplace is required in order to prevent accidents and occupational diseases. The current paper analyses how noise generated by industrial compressors influences worker’s activity. Prevention of noise exposure must be based on noise level measurements. In this sense, the purpose of the paper is to analyse noise measurements performed at a compressor hall and to compare the values obtained with limit values set by in force legislation, in order to apply the best technical organizational methods for lowering noise exposure and increasing acoustic comfort in order to improve working conditions of those working in the compressor hall.


2006 ◽  
Author(s):  
Rafael A. C. Laranja ◽  
Luiz C. Gertz ◽  
Charles Rech ◽  
Alexandre Balbinot ◽  
Rosa Leamar Dias Blanco ◽  
...  

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