• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.593-610
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• 2015

Adaptive Rejection Sampling (ARS) method is a well-known random number generator to acquire a random sample from a probability distribution, and has the advantage of improving the proposal distribution during the sampling procedures, which update it closer to the target distribution. However, the use of ARS is limited since it can be used only for the target distribution in the form of the log-concave function, and thus various methods have been proposed to overcome such a limitation of ARS. In this paper, we attempt to compare five random number generators based on ARS in terms of adequacy and efficiency. Based on empirical analysis using simulations, we discuss their results and make a comparison of five ARS-based methods.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.4
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• pp.315-328
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• 2016

Techniques for determinating hydrodynamic derivatives of underwater tow-fish using CFD(Computational Fluid Dynamics) are described in this paper. Main components of hydrodynamic derivatives are added mass, linear damping and non-linear damping coefficients. In this study, linear and non-linear damping coefficients for translational velocities are settled by CFD analysis. In order to analyze the underwater tow-fish, UlsanFOAM based on open-source CFD code, namely OpenFOAM, is employed. By simulating pitch and yaw angle variation of underwater tow-fish, 6DOF(Degree-of-Freedom) forces and moments are estimated at each attitudes. In order to determinate the hydrodynamic derivatives, curves(forces and moments vs attitude) for CFD results are fitted by least square methods. To demonstrate the applicability of the current approach, two different problems(impulsive side towing and straight towing) are simulated and all results are validated.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1049-1068
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• 2014

Autoregressive models are used to analyze an univariate time series data; however, these methods can be inappropriate when a structural break appears in a time series since they assume that a trend is consistent. Threshold autoregressive models (popular regime-switching models) have been proposed to address this problem. Recently, the models have been extended to two regime-switching models with delay parameter. We discuss two regime-switching threshold autoregressive models from a Bayesian point of view. For a Bayesian analysis, we consider a parametric threshold autoregressive model and a nonparametric threshold autoregressive model using Dirichlet process prior. The posterior distributions are derived and the posterior inferences is performed via Markov chain Monte Carlo method and based on two Bayesian threshold autoregressive models. We present a simulation study to compare the performance of the models. We also apply models to gross domestic product data of U.S.A and South Korea.

• Journal of Korean Society of Forest Science
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• v.97 no.3
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• pp.316-325
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• 2008

This study was done to compare socio-economic characteristics and travel pattern, preferences for ecotourism facilities and programs of domestic and international tourists who visited to Jeju Island. On-site survey was carried out during July, 2006 and a total of five hundred and fifty five (555) individuals' data were analyzed. Survey results showed that there were significant differences between socioeconomic characteristics and travel patterns as well as preferences of both parties. Even among international tourists from countries with different languages showed different characteristics. These different characteristics among tourist groups imply that tour route design and program development should be accordingly considered to provide satisfactory experiences.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.39-45
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• 2018

Compressive sensing allows recovering an original signal which has a small dimension of the signal compared to the dimension of the entire signal in a short period of time through a small number of observations. In this paper, we proposed a method for detecting tonal signal which caused by the machinery component of a vessel such as an engine, gearbox, and support elements. The tonal signal can be modeled as the sparse signal in the frequency domain when it compares to whole spectrum range. Thus, the target tonal signal can be estimated by S-OMP (Simultaneous-Orthogonal Matching Pursuit) which is one of the sparse signal recovery algorithms. In simulation section, we showed that S-OMP algorithm estimated more precise frequencies than the conventional FFT (Fast Fourier Transform) thresholding algorithm in low SNR (Signal to Noise Ratio) region.

• The Journal of the Acoustical Society of Korea
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• v.37 no.5
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• pp.300-308
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• 2018

The contribution analysis of various external aeroacoustic noise sources to interior noise is important, enabling to design an automobile with a low interior noise level. With a new technique, the CD (Cholesky Decomposition), it is proposed to decompose an overall interior noise spectrum into multiple spectra, each representing the contribution of a specific noise source to the interior noise. In order to validate this method, three kinds of experiments were conducted. Furthermore, it is proposed to improve the CD-based contribution analysis method to be integrated with existing exterior microphone arrays in the wind tunnel. This method was validated with an experiment with two speakers.

• The Journal of the Acoustical Society of Korea
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• v.37 no.5
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• pp.271-275
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• 2018

There are several methods for estimating the time delay between incoming signals to two sensors. Among them, the GCC-PHAT (Generalized Cross Correlation-Phase Transform) method, which estimates the relative delay from the signal whitening and the cross-correlation between the different signal inputs to the two sensors, is a traditionally well known method for achieving stable performance. In this paper, we have identified a part of GCC-PHAT that can improve the periodicity. Also, we apply the auto-correlation method that is widely used as a method to improve the periodicity. Comparing the proposed method with the GCC-PHAT method, we show that the proposed method improves the mean square error performance by 5 dB ~ 15 dB at the SNR above 0 dB for white Gaussian signal source and also show that the method improves the mean square error performance up to 15 dB at the SNR above 2 dB for the color signal source.

• Journal of KIISE
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• v.45 no.3
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• pp.234-241
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• 2018

The study of classifying gamer types or analyzing the characteristics of gamers is a field of interest for data analysis researchers. From the past to the present, much research has been done on gamer categorization and gamer analysis. However, most studies use surveys or bio-signals, which is not practical because it is difficult to obtain large amounts of data. Even if the game log is used, it is difficult to analyze the psychology of the gamer because the gamer is categorized and analyzed by extracting only statistical values. However, if we can extract the cognitive psychology information of the gamer from the basic game log, we can analyze the gamer more intuitively and easily. In this paper, we extracted eight cognitive psychological features representing the behavior and psychological information of the gamer using Crazy Dragon's game log, which is a mobile Role-Playing-Game (RPG). In addition, we classified gamers based upon cognitive psychological features and analyzed them using eight cognitive psychological features. As a result, most gamers were highly correlated with one or two types.

• Bulletin of the Korean Chemical Society
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• v.35 no.10
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• pp.2974-2978
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• 2014

$Mn_3O_4$/multi-walled carbon nanotube (MWCNT) composites are prepared by chemically synthesizing $Mn_3O_4$ nanoparticles on a MWCNT film at room temperature. Structural and morphological characterization has been carried out using X-ray diffraction (XRD) and scanning and transmission electron microscopies (SEM and TEM). These reveal that polycrystalline $Mn_3O_4$ nanoparticles, with sizes of about 10-20 nm, aggregate to form larger nanoparticles (50-200 nm), and the $Mn_3O_4$ nanoparticles are attached inhomogeneously on MWCNTs. The electrochemical behavior of the composites is analyzed by cyclic voltammetry experiment. The $Mn_3O_4$/MWCNT composite exhibits a specific capacitance of $257Fg^{-1}$ at a scan rate of $5mVs^{-1}$, which is about 3.5 times higher than that of the pure $Mn_3O_4$. Cycle-life tests show that the specific capacitance of the $Mn_3O_4$/MWCNT composite is stable up to 1000 cycles with about 85% capacitance retention, which is better than the pure $Mn_3O_4$ electrode. The improved supercapacitive performance of the $Mn_3O_4$/MWCNT composite electrode can be attributed to the synergistic effects of the $Mn_3O_4$ nanoparticles and the MWCNTs, which arises not only from the combination of pseudocapacitance from $Mn_3O_4$ nanoparticles and electric double layer capacitance from the MWCNTs but also from the increased surface area, pore volume and conducting property of the MWCNT network.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.5
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• pp.388-399
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• 2016

A motion analysis of an underwater towed cable is a complex task due to its nonlinear nature of the problem. The major source of the nonlinearity of the underwater cable analysis is that the motion of the cable involves large rigid-body motion. This large rigid-body motion makes difficult to use standard displacement-based finite element method. In this paper, the authors apply recently developed nodal position-based finite element method which can deal with the geometric nonlinearity due to the large rigid-body motion. In order to enhance the stability of the large-scale nonlinear cable motion simulation, an efficient time-integration scheme is proposed, namely predictor/multi-corrector Newmark scheme. Three different predictors are introduced, and the best predictor in terms of stability and robustness for impulsive cable motion analysis is proposed. As a result, the nonlinear motion of underwater cable is predicted in a very efficient manner compared to the classical finite element of finite difference methods. The efficacy of the method is demonstrated with several test cases, involving static and dynamic motion of a single cable element, and also under water towed cable composed of multiple cable elements.