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

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.27 no.5
• /
• pp.430-437
• /
• 2016

In general, noise measurement results show larger random ripple than those of the network analyzer. The reason for the lager random ripple of the noise measurements is considered that the general noise measurements uses absolute measured noise powers, while the network analyzer measures using a ratio of the measured powers. In this paper, a novel measurement method of noise correlation matrix using relative noise ratios is proposed. Proposed method measures the five noise powers of DUT for the five input impedance variations and the four relative noise ratios are formed using the five measured noise powers. The four noise ratios are used to compute the noise correlation matrix and noise parameters. The resulting noise parameters for a 0.5 dB attenuator show good agreements with theoretical values calculated by S-parameters. Also, the noise parameters of an active DUT with a noise figure of less than 1 dB are measured and the measured results show a small random ripple as expected and their values are physically acceptable. In conclusion, the proposed method can be applied to the noise parameter measurements for DUT with a noise figure below 1 dB.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.14 no.9 s.90
• /
• pp.884-890
• /
• 2004

In this paper, an index for the evaluation of vehicle intake booming noise is developed through a correlation analysis of objective measurement data and subjective evaluation data. First, intake orifice noise is measured at the wide-open test condition. And then, acoustic transfer function between intake orifice noise and interior noise at the steady state condition is estimated. Simultaneously, subjective evaluation was carried out with a ten-scale score by 8 engineers. Next, the correlation analysis between the psycho-acoustic parameters derived from the measured data and the subjective evaluation is performed. The most critical factor was determined and the corresponding index for the intake booming noise is obtained from the multiple factor regression method. At last, the effectiveness of the proposed index is validated.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2005.11a
• /
• pp.551-554
• /
• 2005

The method of the reduction of the automotive induction noise can be classified by the method of passive control and the method of active control. However, the passive control method has a demerit to reduce the effect of noise reduction at low frequency (below 500Hz) range and to be limited by a space of the engine room. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used the LMS (Least-Mean-Square) algorithm because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, When the Filtered-X LMS (FXLMS) algorithm is applied to an ANC system. However, the convergence performance of LMS algorithm goes bad when the FXLMS algorithm is applied to an active control of the induction noise under rapidly accelerated driving conditions. Thus Normalized FXLMS algorithm was developed to improve the control performance under the rapid acceleration. The advantage of Normalized FXLMS algorithm is that the step size is no longer constant. Instead, it varies with time. But there is one additional practical difficulty that can arise when a nonstationary input is used. If the input is zero for consecutive samples, then the step size becomes unbounded. So, in order to solve this problem. the Correlation FXLMS algorithm was developed. The Correlation FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Correlation FXLMS Is presented in comparison with that of the other FXLMS algorithms based on computer simulations.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.15 no.8 s.101
• /
• pp.939-944
• /
• 2005

In this paper, a sound quality index for the evaluation of the vehicle intake noise was developed through a correlation analysis of the objective measurement and the subjective evaluation. First, intake orifice noise was measured at the wide-open throttle sweep condition. And then, the acoustic transfer function between intake orifice noise and interior noise was measured. Simultaneously, subjective evaluation was carried out with a 10-scale score by 8 special engineers. The correlation analysis between the psychoacoustic parameters derived from the measurement and the subjective evaluation was performed. The most critical factor was determined and the corresponding sound quality index for intake noise was obtained from the multiple factor regression analysis method. Finally, the effectiveness of the proposed index was validated.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.6
• /
• pp.28-38
• /
• 2010

In order to remove the noise contained in recorded analog video, it is important to recognize the real characteristics and strength of the noise. This paper presents an efficient training-based noise reduction method for recorded analog video after analyzing the noise characteristics of analog video captured in a real broadcasting system. First we show that there is non-negligible noise correlation in recorded analog video and describe the limitations of the traditional noise estimation and reduction methods based on additive white Gaussian noise (AWGN) model. In addition, we show that auto-regressive (AR) model considering noise correlation can be successfully utilized to estimate and synthesize the noise contained in the recorded analog video, and the estimated AR parameters are utilized in the training-based noise reduction scheme to reduce the video noise. Experiment results show that the proposed method can be efficiently applied for noise reduction of recorded analog video with non-negligible noise correlation.

• Journal of Biomedical Engineering Research
• /
• v.26 no.4
• /
• pp.199-205
• /
• 2005

When recording single-unit responses from neural systems, a common problem is the accurate detection of spikes (action potentials) in the presence of competing unwanted (noise) signals. While some sources of noise can be readily dealt with through filtering or 'template subtraction' techniques, other sources present a more difficult problem. In particular, noise components introduced by power supplies, which contain harmonics of the power-line frequency, can be particularly troublesome in that they can mimic the shape of the desired spikes. Thus, standard 'template subtraction' techniques or notch-filtering approaches are not appropriate. In this study, we propose the use of a novel template-subtraction scheme that involves estimating the power-line noise waveform and using cross-correlation techniques to subtract them from the recordings. This technique requires two key steps: (1) cross-correlation analysis of each recorded waveform extracts a robust representation of the power-line noise waveform and (2) a second level of cross-correlation to successfully subtract that representation from each recorded waveform. This paper describes this algorithm and provides examples of its implementation using actual recorded waveforms that are contaminated with these noise signals. An improvement (reduction) in the noise level is reported, as are suggestions for future implementation of this strategy.

• The Journal of the Acoustical Society of Korea
• /
• v.20 no.2
• /
• pp.86-92
• /
• 2001

Various array processing techniques to identify the noise source position or bearing have been developed. Typical array processing techniques which are based on time delay between received signals at two sensors, are classified as conventional beamforming, correlation function and NAH (Near-Field Acoustic Holography) techniques which have their own characteristics with respect to application field and signal processing method. In this study, correlation function technique which could be applied for broadband noise source detection, is adopted and the effective detection technique is proposed considering the effects of source bandwidth and measurement noise correlation of noise sources. The validity of the Proposed technique is evaluated using the 3-dimensional nonlinear any which does not give 3-dimensional Position or bearing ambiguity

• Korean Journal of Remote Sensing
• /
• v.25 no.3
• /
• pp.263-270
• /
• 2009

Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

• Journal of the Semiconductor & Display Technology
• /
• v.19 no.3
• /
• pp.82-87
• /
• 2020

The comprehensive and physics-based compact noise models for advanced CMOS devices were presented. The models incorporate important physical effects in nanoscale MOSFETs, such as the low frequency correlation effect between the drain and the gate, the trap-related phenomena, and QM (quantum mechanical) effects in the inversion layer. The drain current noise model was improved by including the tunneling assisted-thermally activated process, the realistic trap distribution, the parasitic resistance, and mobility degradation. The expression of correlation coefficient was analytically described, enabling the overall noise performance to be evaluated. With the consideration of QM effects, the comprehensive low frequency noise performance was simulated over the entire bias range.