• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.328-333
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• 2019

In this paper, to investigate the cavitation erosion phenomenon on the ship propeller, the correlation between the propeller noise and the cavitation intensity was analyzed. Cavitation erosion is closely related to cavitation collapsing intensity, which can be defined as the frequency and intensity of cavitation collapse. The pressure wave generated by cavitation collapse appears as a continuous acoustic pulse and this result is analyzed with the cavitation behavior to determine the relationship of the propeller noise to cavitation collapse intensity. This technique is applied to the propeller erosion test using the inclined shaft propeller model.

• Journal of Astronomy and Space Sciences
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• v.38 no.3
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• pp.165-173
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• 2021

Apophis is a near-Earth object with a diameter of approximately 340 m, which will come closer to the Earth than a geostationary orbit in 2029, offering a unique opportunity for characterizing the object during the upcoming encounter. Therefore, Korea Astronomy and Space Science Institute has a plan to propose a space mission to explore the Apophis asteroid using scientific instruments such as a laser altimeter. In this study, we evaluate the performance metrics of a laser altimeter using a pseudorandom noise modulation technique for the Apophis mission, in terms of detection probability and ranging accuracy. The closed-form expression of detection probability is provided using the cross correlation between the received pulse trains and pseudo-random binary sequence. And the new ranging accuracy model using Gaussian error propagation is also derived by considering the sampling rate. The operation range is significantly limited by thermal noise rather than background noise, owing to not only the low power laser but also the avalanche photodiode in the analog mode operation. However, it is demonstrated from the numerical simulation that the laser altimeter can achieve the ranging performance required for a proximity operation mode, which employs commercially available components onboard CubeSat-scale satellites for optical communications.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.8
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• pp.583-590
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• 2003

For the preestimate of the vibration level of the ground next to a dwelling, a multivariate statistical analysis on the experiment data acquired from a variety of construction sites was performed, and then a new estimate model for the value of K and n that can be applied in the diagnosis of the damage was offered. The results maybe summarized as follows : First, the $K_{95}$ and n showed high correlation at P$\leq$0.05. Specially the correlation coefficient about $W_{max}$, S were higher in $K_{95}$ than in n. indicating that $K_{95}$ is generally associated with source conditions. Second, the factor analysis permitted to identify two major sources in each fraction. These sources accounted for at least 73 % of valiance of $K_{95}$. Third, the multiple regression model for the estimate of $K_{95}$ was developed from Fac1 which depend upon the source conditions and Fac2 which depend upon the transmission conditions. The n value is able to determine from the correlation relationship associated with $K_{95}$./.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.79-86
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• 2002

This paper proposes a new algorithm for estimating ARMA model parameters. In estimating ARMA model parameters, several methods such as generalized least square method, instrumental variable method have been developed. Among these methods, the utilization of a bootstrap type algorithm is known as one of the effective approach for the estimation, but there are cases that it does not converge. Hence, in this paper, making use of a cross correlation function and utilizing the relation of structural a priori knowledge, a new bootstrap algorithm is developed. By introducing theoretical relations, it became possible to remove terms, which is liable to include much noise. Therefore, this leads to robust parameter estimation. It is shown by numerical examples that using this algorithm, all simulation cases converge while only half cases succeeded with the previous one. As for the calculation time, judging from the fact that we got converged solutions, our proposed method is said to be superior as a whole.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.1
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• pp.60-69
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• 2014

Footstep detection using seismic sensors for security is a very meaningful task, but readings can easily fluctuate due to noise in outdoor environment. We propose NSSC method based on nonlinear spectral subtraction and cross-correlation using prime footstep model signal as a footstep signal refining process that enhances the signal-to-noise ratio (SNR) and attenuates noise. After de-noising, a detection event classification method is presented as further refining process to ensure that the detection result is a footstep. To validate the proposed algorithm, representative experiments including sunny and rainy-day cases are demonstrated.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.446-451
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• 2007

An Improved finite element model updating method to address the numerical difficulty associated with ill-conditioning and rank-deficiency. These difficulties frequently occur in model updating problems, when the identification of a larger number of physical parameters is attempted than that warranted by the information content of the experimental data. Based on the standard Bounded Variables Least-squares (BVLS) method, which incorporates the usual upper/lower-bound constraints, the proposed method is equipped with new constraints based on the correlation coefficients between the sensitivity vectors of updating parameters. The effectiveness of the proposed method is investigated through the numerical simulation of a simple framed structure by comparing the results of the proposed method with those obtained via pure BVLS and the regularization method. The comparison indicated that the proposed method and the regularization method yield approximate solutions with similar accuracy.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.127-136
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• 2011

Multiplicative noise model is the one of popular method for masking continuous variables. In this paper, we propose the transformation on the variable to which random noise was multiplied. An advantage of the masking method using proposed transformation is that the masking data users can obtain the unbiased values of mean and variance of original (unmasked) data. We also consider the data utility and correlation structure of variables when we apply the proposed multiplicative noise scheme. To investigate the properties of the method of masking based on multiplicative noise, a simulation study has been conducted using the 2008 Householder Income and Expenditure Survey data.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.269-276
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• 2010

In this paper, we present the detection method of moving objects based on two background models. These background models support to understand multi layered environment belonged in images taken by shaking camera and each model is MBM(Multiple Background Model) and TMBM (Temporal Median Background Model). Because two background models are Pixel-based model, it must have noise by camera movement. Therefore correlation coefficient calculates the similarity between consecutive images and measures camera motion vector which indicates camera movement. For the calculation of correlation coefficient, we choose the selected region and searching area in the current and previous image respectively then we have a displacement vector by the correlation process. Every selected region must have its own displacement vector therefore the global maximum of a histogram of displacement vectors is the camera motion vector between consecutive images. The MBM classifies the intensity distribution of each pixel continuously related by camera motion vector to the multi clusters. However, MBM has weak sensitivity for temporal intensity variation thus we use TMBM to support the weakness of system. In the video-based experiment, we verify the presented algorithm needs around 49(ms) to generate two background models and detect moving objects.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.6
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• pp.725-733
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• 1998

The pressure fluctuation on the surface of a submerged body has been recognized as a dominant noise source. There have been many studies concerning the flow induced noise on a flat plate. However, the noise over an axisymmetric body has not been well reported. This paper addresses the way in which we have investigated the mechanism of noise generation due to an axisymmetric body. The associated experiments and signal processing methods are introduced. A 3-dimensional axisymmetric body whose length and diameter were 2 m and 10.4 cm, was prepared as a test specimen. The wall pressure on the surface of the body was measured in a large scale low noise wind tunnel at KIMM(Korea Institute of Machinery and Metals). To measure the wall pressure, we used two microphone arrays which were tangential and normal to the flow. Based on the measured signal, frequency-wavenumber spectrum which explains the structure of turbulence noise, was estimated. Tangential to the flow, there exists convective ridge at a relatively higher wavenumber region; this can cause spatial aliasing. To circumvent this problem, the cross spectrum was interpolated. The interpolation has been performed by unwrapping the phase and smoothing the cross spectrum. The phase unwrapping was done based on the Corcos model; the phase of cross spectrum decreases linearly with the distance between microphones. Aforementioned signal processings are possible by employing the experimental results that the estimated wavenumber spectrum quite resembles the Corcos model. We try to modify the Corcos model which is applicable to the flat plate, by altering the magnitude of cross spectrum to fit the experimental data more accurately. We proposed that this wavenumber spectrum model is suitable for the 3-dimensional axisymmetric body. Normal to the flow, there exists a little correlation between signals of different microphones. The circumferential wavenumber spectrum contains uniform power along the wavenumbers.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1443-1448
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• 2006

The reduction of the vehicle interior noise has been the main interest of NVH engineers. The driver's perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. In particular, the HVAC sound among the vehicle interior noise has been reflected sensitively in the side of psychology. Even though the HVAC noise is not louder than overall noise level, it clearly affects subjective perception in the way of making a diver become nervous or annoyed. Therefore, these days a vehicle engineer takes aim at developing sound quality as well as reduction of noise. In this paper, we acquired noises in the HVAC from many vehicles. Through the objective and subjective sound quality evaluation with acquiring noises caused by the vehicle HVAC system, the simple and multiple regression models were obtained for the subjective evaluation 'Pleasant' using the sound quality metrics. The regression procedure also allows you to produce diagnostic statistics to evaluate the regression estimates including appropriation and accuracy. Furthermore, the neural network model were obtained using three inputs(loudness, sharpness and roughness) of the sound quality metrics and one output(subjective 'Pleasant'). And then the models were compared with correlations between sound quality index outputs and hearing test results for 'Pleasant'. As a result of application of the sound quality index, the neural network was verified with the largest correlation of the sound quality index.