• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.5 no.2
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• pp.128-136
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• 1995

The purpose of this study is to evaluate the difference of noise level according to noise measuring methods in the noisy working environments. Sound pressure level(SPL), equivalence sound level(Leq) and personal noise exposure dose(Dose) in the fifty-nine unit workplaces of the twenty-eight industries were measured and relating factors which were affected noise level were investigated. The results were as follows ; 1. The noise levels were $88.70{\pm}5.68dB(A)$ by SPL, $89.07{\pm}5.41dB(A)$ by Leq and $89.07{\pm}5.69$ by Dose. The differences of noise levels by three measuring methods were statistically significant(P<0.001) by repeated measure ANOV A. 2. Comparing with noise levels by general classes of noise exposure, noise levels of continuous noise were $89.14{\pm}5.19dB(A)$ by SPL, $89.45{\pm}4.65dB(A)$ by Leq and $90.04{\pm}5.09$ by Dose. Noise levels of intermittent noise were $87.90{\pm}6.52dB(A)$ by SPL, $88.40{\pm}6.63dB(A)$ by Leq and $90.10{\pm}6.80$ by Dose. The differences noise level of noise measuring methods by general classese of noise exposure were statistically not significant by repeated measure ANOV A. 3. Interaction between general classese of noise exposure and noise measuring methods for noise level was not statistically significant by repeated measure ANOVA. And the noise level by noise measuring methods were statistically significant by repeated measure ANOV A(P<.001) 4. Comparing with noise levels by unit workplace size, noise levels of large unit workplace were $90.73{\pm}5.87dB(A)$ by SPL, $91.32{\pm}5.50dB(A)$ by Leq and $91.82{\pm}6.06$ by Dose and noise levels of middle unit workplace were $88.31{\pm}5.26dB(A)$ by SPL, $88.41{\pm}4.83dB(A)$ by Leq and $89.69{\pm}5.05$ by Dose. And noise levels of small unit workplace were $94.89{\pm}4.10dB(A)$ by SPL, $85.35{\pm}4.11dB(A)$ by Leq and $86.87{\pm}4.98$ by Dose. The noise level differences of noise measuring methods by unit workplace size were statistically significant by repeated measure ANOV A(P<.05). 5. The noise level by noise measuring methods were statistically significant by repeated measure ANOV A(P<.001). But Interaction between workplace size and noise level measuring methods for noise level was not statistically significant by repeated measure ANOVA. According to the above results, there was a difference of the noise level among the three measuring methods. Therefore we must use the personal noise exposure dose using by noise dose meter, possible, to prvent occupational hearing loss in noisy working environment.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1522-1527
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• 2009

Construction project is necessary element for human life to upgrade the quality and convenience. However, due to its contradictory nature to the environment conservation, environmental pollution and damage, deterioration of natural scenery, noise/vibration, water quality pollution, etc. caused in the process of construction greatly affect the environment. The purpose of this study is to propose checklist for environment management can be used in construction phase. For this, we went ahead with the research by studying the existing research related to environment-friendly construction project management both at home and abroad, investigation and analysis of environment-related laws and ordinances, and drawing the checklists for natural environment and living environment at the construction phase. As a result, we were able to compile a checklist for nine items including geological features, animals and plants, use of soil, quality of air, water, and soil, construction wastes, noise, vibration, recreation, and sceneries. The checklist is structured in 4 grades and coded so as to allow it to be developed with the use of computer system in future. We hope that the checklist presented in this study will help lead the managers at the construction phase in construction development sustainable from the perspective of environmental conservation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.704-709
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• 2014

본 연구는 현재 사회문제화 되고 있는 층간소음 피해 실태조사 분석을 통하여 적용 가능한 층간소음 분쟁의 예방을 위한 효율적인 관리시스템을 개발 적용하였다. 설문조사 분석결과, 층간소음의 주요 발생 원인으로 아이들 뛰는 소음과 어른 걷는 소음이 55% ~ 75%로 가장 심각한 소음원으로 나타났으며, 소음 피해시간대는 저녁(18시~22시) 시간대는 50% ~ 65%로 가장 높게 나타났으며, 야간(22시~ 06시) 시간대는 26% ~ 45%범위에 있는 것으로 분석되었다. 층간소음관리시스템 적용 전 후의 민원저감효과 분석결과, 전라도 광주는 100%, 대구시는 87.5%, 서울의 경우는 83%, 경기도는 71% 순으로 나타나, 평균 약 85% 이상의 민원 저감효과가 있는 것으로 나타났다. 층간소음관리시스템 적용 전 후의 아파트 가격 변화 분석결과, 적용된 아파트의 경우는 평균 17.23백만원 상승한 반면, 미적용된 아파트는 0.55백만원 하락한 것으로 평가되었다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.693-697
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• 2014

본 연구는 민원인(아래층)과 피민원인(윗층)간 전문상담사의 중재를 통해 층간소음 문제를 해결하는 층간소음 현장관리시스템의 실효성을 검증하였다. 민원인(아래층)과 피민원인(위층)의 층간소음 피해경향을 분석한 결과, 4,087건 중 80%에 해당하는 3,254건의 민원인들은 층간소음 발생장소를 바로 윗층을 지목하는 것으로 나타났고, 반면에 15%에 해당하는 피민원인들(윗층)은 피해를 받는 원인이 소음이 아니라 피민원인의 전화나 방문 등을 통한 잦은 항의를 지적하는 것으로 분석되었다. 1,304건의 현장 방문 민원건수 중 80%에 해당하는 1,050건을 대상으로 현장방문 컨설팅 전 후의 층간소음 저감 등 만족도 조사결과, 약 683건에 해당하는 65%정도의 민원인은 층간소음 현장관리시스템에 만족하고 있는 것으로 평가되었다.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.377-382
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• 2012

In this paper, the echo noise robust CHMM learning model using echo cancellation average estimator LMS algorithm is proposed. To be able to adapt to the changing echo noise. For improving the performance of a continuous speech recognition, CHMM models were constructed using echo noise cancellation average estimator LMS algorithm. As a results, SNR of speech obtained by removing Changing environment noise is improved as average 1.93dB, recognition rate improved as 2.1%.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.1
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• pp.75-81
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• 2002

In this paper, data rate of VDSL system was analyzed in noise and crosstalk environment. For this paper, Matlab tool was used to analyze the performance of VDSL system. Various "VDSL Test Loop" are used which is suggested by ANSI DSL Standard group T1E1.4. Many parameters, "Noise Model A", "Noise Model F", duplex method VDSL-998 which is suggested FDD plan by ANSI was used. The most of conditions for simulation are followed to the ANSI Standard "Spectrum management" Lots of data have been obtained according to the different conditions of the test loops. The result shows that the data rate of VDSL system is decreased due to the other DSL signals in the same cable bundle. And also there was more reduced data rate in case of Noise Model F than that of Noise Model A.

• Journal of the Korean Professional Engineers Association
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• v.33 no.3
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• pp.30-34
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• 2000

In recent years, disputes are on the increase that noise and vibration by construction equipments and blasting do damage to livestock farming families around construction sites in the construction of a road or a railway. Therefore, the following ways of improvement were presented in solving the existing problems of livestock disputes. $.$ To minimize the damage of livestock farming families by effect assessment of noise and vibration in the region expected to be damaged before the start of construction $.$ To maintain a thorough management system that can reduce noise and vibration during construction work $.$ To apply an adequate measurement method of noise and vibration taking field conditions into consideration

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.1
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• pp.49-54
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• 2016

The wind power plants were installed in many places because of the low climate changing effects since 2000. Generally, the wind power plants located in the seaside and the mountainous area and the heights of the windmills are about 40 m~140 m above the ground level. So the noises emitted from the wind power plants propagate far away compared with other environment noise sources like trains and cars noise. Because of these reasons, the noise emitted from the wind power plant is easy to cause the additional social problems like as noise complaints. Under the situation, the ministry of environment has established the guideline to evaluate the environmental effects for the wind power plant. According to the guideline, the noise of the wind power plant has to meet 55 dB(A) at daytime and 45 dB(A) at night in the residential area, which is regulated in the noise and vibration management law. But, it is difficult to estimate the noise emitted from the wind power plant because of the absence of the prediction model of the wind power plant noise. Therefore, the noise prediction model for wind power plants using the regression analysis method is developed in this study. For the development of the model, the sound pressure levels of the wind power plants in Jeju island are measured and the correlations between the sound pressure levels are analyzed. Finally, the prediction equation of the wind power plant noise using by regression analysis method derived. The prediction equation for the wind power plant noise proposed in this study can be useful to evaluate the environmental effects in any wind power plant development district.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.135-140
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• 2013

Noise estimation and detection algorithm to adapt quickly to changing noise environment using the LMS Filter. However, the LMS Filter for noise estimation for a certain period of time and need time to adapt. If the signal changes occur, have the disadvantage of being more adaptive time-consuming. Therefore, noise removal method is proposed to a frame basis AELMS Filter to compensate. In this paper, we split the input signal on a frame basis in noisy environments. Remove the LMS Filter by configuring noise predictions using the mean and variance. Noise, even if the environment changes fast adaptation time to remove the noise. Remove noise and environmental noise and speech input signal is mixed to maintain the unique characteristics of the voice is a way to reduce the damage of voice information. Noise removal method using a frame basis AELMS Filter To evaluate the performance of the noise removal. Experimental results, the attenuation obtained by removing the noise of the changing environment was improved by an average of 6.8dB.

• Journal of Environmental Health Sciences
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• v.49 no.6
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• pp.353-361
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• 2023

Background: Noise has been linked to an increased risk of various health issues, including stress, anxiety, insomnia, and cardiovascular disorders. However, research on the relationship between residential traffic noise and mental health in South Korea is limited. Objectives: This study aims to examine the correlation between regional traffic noise levels and mental health using an ecological study design. Methods: In this ecological study, all data were collected from the Korean Statistical Information Service. Traffic noise data in residential areas and the prevalence of mental health indices in 44 cities with noise monitoring stations were obtained. Pearson correlation coefficients were calculated to assess the relationship between regional traffic noise levels and mental health indices. Results: Daytime traffic noise levels were found to have a positive correlation with stress perception (r=0.428, p=0.004) and showed a borderline positive correlation with depressive symptom prevalence (r=0.273, p=0.073). In cities with airports, significant correlations was observed between 24-hour average noise levels and depressive symptoms (r=0.604, p=0.010), whereas this relationship was not observed in cities without airports (r=0.048, p=0.813). Multiple regression analysis, which adjusted for factors such as age, gender ratio, smoking, obesity, unemployment, urban size, and the presence of an airport, confirmed the relationship between 24-hour average noise levels and stress perception (beta=0.287, p=0.024). Conclusions: This study identified correlations between regional traffic noise levels and depressive symptoms or stress perception in adults, with a more pronounced effect in areas with airports. These findings suggest a potential impact of residential traffic noise on mental health, highlighting the importance of preventive measures like noise management in urban planning to promote mental well-being.