• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.4
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• pp.303-309
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• 2004

Absorptive material arrangement method for effective interior noise control is proposed. Sound field with arbitrary boundary condition is formulated by Kirchhoff-Helmholtz integral equation. A simple example such as a rectangular cavity will present physical meaning between changing boundary condition and control of sound field. The effect of changing boundary condition is expressed in modal admittance. From this formulation. an admittance map is presented. The admittance map is the figure to represent position where absorptive material is attached for effective interior noise control. The admittance map can be assigned to each resonant frequency. There. however, may be common area of those maps. Then, frequency robust arrangement of absorptive material in noise control will be presented.

• Journal of Institute of Convergence Technology
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• v.12 no.1
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• pp.1-5
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• 2022

This paper describes an algorithm for generating a terrain using a noise function and a height map as one of the procedural terrain generation methods. The polygon mesh data structure to represent the generated terrain concisely and render it is also described. The Perlin noise function is used as the noise technique for terrain mesh, and the height data of the terrain is generated by combining the four noise waves. In addition, the terrain height information can be also obtained from actual image data taken from the satellite. The algorithm presented in this paper generates the geometry part of the polygon topography from the height data obtained, and generated a material for texture mapping with two textures, that is, a diffuse texture and a normal texture. The validity of the terrain method proposed in this paper is verified through application examples, and its possibility can be confirmed through performance verification.

• Journal of Environmental Policy
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• v.6 no.1
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• pp.111-132
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• 2007

The traffic noise of Busan, the second largest city in Korea, is polluting the area. Noise map is a map that shows data on an existing or predicted noise condition in terms of a noise indicator, breaches of a limit value, the number of dwellings exposed to certain values of a noise indicator in a certain area, or on cost-benefit ratios or other economic data on mitigation methods or scenarios with Geographic Information System. With noise map, the effect of traffic noise and the efficiency of city development plan are exactly estimated. So making systematic counteroffer is possible with it. This study is aimed to the construction of basis for noise map construction method for domestic use and the area focus is Busan.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.438-442
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• 2006

Reasonably accurate estimation of the exposed population to the distinct levels of noise is essential to the efficient management of urban environmental noise. This study proposes a method of calculating the number of exposed people to industrial noise by using GIS tool and noise mapping. The exposed population of noise based on estimation of the number of people that lived in each building in urban area is compared with the one based on density of population. This study suggests the six step method that consists of gathering the fundamental data, extracting the property from the digital map, noise mapping based on the three dimensional topography, estimating population that lives in each building, merging the various results with GIS tool, and estimating exposed population to industrial noise through analyzing the noise map with GIS tools

• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.256-261
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• 2018

There are three types of noise generated inside the vehicle: BSR (Buzz, Squeak, Rattle). In this paper, we propose a classifier that automatically classifies automotive BSR noise by using features extracted from deep convolutional neural networks. In the preprocessing process, the features of above three noises are represented as noise-map using STFT (Short-time Fourier Transform) algorithm. In order to cope with the problem that the position of the actual noise is unknown in the part of the generated noise map, the noise map is divided using the sliding window method. In this paper, internal parameter of the deep convolutional neural networks is visualized using the t-SNE (t-Stochastic Neighbor Embedding) algorithm, and the misclassified data is analyzed in a qualitative way. In order to analyze the classified data, the similarity of the noise type was quantified by SSIM (Structural Similarity Index) value, and it was found that the retractor tremble sound is most similar to the normal travel sound. The classifier of the proposed method compared with other classifiers of machine learning method recorded the highest classification accuracy (99.15 %).

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.709-714
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• 2008

The various computer programs are used in computer simulation of the traffic noise prediction. But the difference or problem of calculation method used for road traffic noise prediction is not exactly investigated. In this paper, Road traffic noise is predicted on the specific regions by using four prediction methods such as XPS31-133 model(France), RLS-90 model(Germany), ASJ RTN model(Japan) and FHWA model(U.S.A.), which are operated by a program named SoundPLAN, a program to predict road traffic noise. Those prediction values are compared with a measurement value. The results show that four prediction values for taraffic noise are a little different, because of various input factors according to the prediction methods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.929-932
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• 2012

Beat map shows the distribution property of the beating sound in the bell structure. Using the beat map, beat control and beat estimation are available. To draw the beat map, mode pair parameters of the bell are required. However, in case of large bell which is struck by a heavy wooden hammer, it is very difficult to measure the excitation force and to obtain the mode pair parameters. In this paper, we determined the mode pair parameters of the bell from the transmissibility between the roving signal and reference signal, using ODS(operational deflection shape) method. The mode pair data are input to the theoretical model of the beat response and beating waves are generated on the bell circumference. All the numerical and beat map drawing procedures are automatized using Matlab. Finally, the reliability of the beat map generated by the program is verified.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.500-504
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• 2008

Residents in an area where both trains and cars pass through are exposed to not only road traffic noise but also railway noise. Nevertheless, the degree of annoyance the caused to the residents is being under evaluated as the noises have been evaluated separately. Therefore, this study aimed at evaluating the integrated noise of road traffic and railway, and proving the accuracy of the evaluation result.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.7
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• pp.741-745
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• 2008

Residents in an area where both trains and cars pass through are exposed to not only road traffic noise but also railway noise. Nevertheless, the degree of annoyance the caused to the residents is being under evaluated as the noises have been evaluated separately. Therefore, this study aimed at evaluating the integrated noise of road traffic and railway, and proving the accuracy of the evaluation result.

• The Journal of the Korea Contents Association
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• v.14 no.12
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• pp.555-564
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• 2014

The boundary noise in image syntheses using DIBR consists of noisy pixels that are separated from foreground objects into background region. It is generated mainly by edge misalignment between the reference image and depth map or blurred edge in the reference image. Since hole areas are generally filled with neighboring pixels, boundary noise adjacent to the hole is the main cause of quality degradation in synthesized images. To solve this problem, a new boundary noise removal algorithm using a preprocessing of the depth map is proposed in this paper. The most common way to eliminate boundary noise caused by boundary misalignment is to modify depth map so that the boundary of the depth map can be matched to that of the reference image. Most conventional methods, however, show poor performances of boundary detection especially in blurred edge, because they are based on a simple boundary search algorithm which exploits signal gradient. In the proposed method, a two-step hierarchical approach for boundary detection is adopted which enables effective boundary detection between the transition and background regions. Experimental results show that the proposed method outperforms conventional ones subjectively and objectively.