• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.52-61
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• 2006

Orthogonal wavelet tansform which is generally used in image and signal processing applications has limited performance because of lack of shift invariance and low directional selectivity. To overcome these demerits complex wavelet transform has been proposed. In this paper, we present an efficient image denoising method using dual-tree complex wavelet transform and Bernoulli-Gauss prior model. In estimating hyper-parameters for Bernoulli-Gaussian model, we present two simple and non-iterative methods. We use hypothesis-testing technique in order to estimate the mixing parameter, Bernoulli random variable. Based on the estimated mixing parameter, variance for clean signal is obtained by using maximum generalized marginal likelihood (MGML) estimator. We simulate our denoising method using dual-tree complex wavelet and compare our algorithm to well blown denoising schemes. Experimental results show that the proposed method can generate good denoising results for high frequency image with low computational cost.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.11
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• pp.92-100
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• 2009

In this paper, we analyze the hardware architecture of Low Density Parity Check (LDPC) decoder using Log Likelihood Ration-Belief Propagation (LLR-BP) decoding algorithm. Various design issues that affect the decoding performance and the hardware complexity are discussed and the tradeoffs between the hardware complexity and the performance are analyzed. The message data for passing error probability is quantized to 7 bits and among them the fractional part is 4 bits. To maintain the decoding performance, the integer and fractional parts for the intrinsic information is 2 bits and 4 bits respectively. We discuss the alternate implementation of $\Psi$(x) function using piecewise linear approximation. Also, we improve the hardware complexity and the decoding time by applying overlapped scheduling.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.5
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• pp.402-409
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• 2016

Vessel traffic servies (VTS) control movements in ports and coastal areas 24 hours a day using VHF. Thus, we were able to check ship movements and the patterns followed by VTS officers in VTS areas using VHF communication analysis. This study is intended to identify control intervals for dangerous situations and provide VTS officers with basic data and guidelines to prevent these occurrences in advance. We listened to Busan port's VHF communication for seven days and obtained risk values using the Park model with reference to controlled ships. The probability of a dangerous situation arising under a controller's watch per unit of time was confirmed to follow a Poisson distribution. As a result, for each 3.50 hours that VTS directly controls an area, (and in daytime for each 2.85 hours) a ship communicates in a VTS area every 3.84 hours, and some of there communications exceed certain risk values in VTS areas.

• Journal of the Korea Society for Simulation
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• v.17 no.3
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• pp.35-44
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• 2008

Facility location problem is an important subject in many areas of modern business environment. In this paper, we deal with uncapacitated and multi-period facility location problem where the object is a maximization of total profit within predetermined cost. We assume that all demand have to be met. Particularly, we represent various types of customer based on four well-known urban spatial structures to represent a spread of customers. Those are concentric zone model, sector model, multiple nuclei model and star model respectively. We apply to the genetic algorithm to simulate a large scaled problem and develop simulator. We analyze both optimal numbers and locations of facilities for each urban structure. Furthermore, we examine the appropriate time to further expansion of the facilities in the planning horizon. The experimental results show that the developed algorithm can be applied effectively to the facility location problem in the various types of urban area.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.744-748
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• 2012

Botnet is a network that consists of bot hosts infected by malware. The C&C server of centralized botnet, which is being used widely, is relatively easy to detect, while detecting P2P botnet is not a trivial problem because of the existence of many avoiding techniques. In this paper, we separate the network into inner and outer sub-network at the location of the router, and analyze the method of detecting botnet using path of packet and infection probability. We have extended Dye-Pumping algorithm in order to detect P2P botnet members more accurately, and we expect that the analysis of the results can be used as a basis of techniques that detect and block P2P botnet in the networks.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2060-2071
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• 1999

The complicate software failure system is defined to the superposition of the points of failure from several component point process. Because the likelihood function is difficulty in computing, we consider Gibbs sampler using iteration sampling based method. For each observed failure epoch, we applied to latent variables that indicates with component of the superposition mode. For model selection, we explored the posterior Bayesian criterion and the sum of relative errors for the comparison simple pattern with superposition model. A numerical example with NHPP simulated data set applies the thinning method proposed by Lewis and Shedler[25] is given, we consider Goel-Okumoto model and Weibull model with GOS, inference of parameter is studied. Using the posterior Bayesian criterion and the sum of relative errors, as we would expect, the superposition model is best on model under diffuse priors.

• Journal of KIISE
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• v.45 no.3
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• pp.288-293
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• 2018

There have recently been several studies investigating how to apply a privacy preserving technique to publish data. Differential privacy can protect personal information regardless of an attacker's background knowledge by adding probabilistic noise to the original data. To perform differentially private k-means clustering, the existing algorithm builds a differentially private histogram and performs the k-means clustering. Since it constructs an equi-width histogram without considering the distribution of data, there are many buckets to which noise should be added. We propose a k-means clustering algorithm using a quad-tree that captures the distribution of data by using a small number of buckets. Our experiments show that the proposed algorithm shows better performance than the existing algorithm.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.1-13
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• 2005

Latent Class model has been considered recently by many researchers and practitioners as a tool for identifying heterogeneous segments or groups in a population, and grouping objects into the segments. In this paper we consider data on prostate cancer patients from Korean National Cancer Institute and propose a method for grouping prostate cancer patients by using latent class Poisson model. A Bayesian approach equipped with a Markov chain Monte Carlo method is used to overcome the limit of classical likelihood approaches. Advantages of the proposed Bayesian method are easy estimation of parameters with their standard errors, segmentation of objects into groups, and provision of uncertainty measures for the segmentation. In addition, we provide a method to determine an appropriate number of segments for the given data so that the method automatically chooses the number of segments and partitions objects into heterogeneous segments.

• Journal of Technology Innovation
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• v.18 no.1
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• pp.99-121
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• 2010

The goal of this paper is to analyze the effects of various firm characteristics on the probability for a firm to receive government’s financial supports for R&D. In the empirical analysis, a Probit model is estimated for the 2008 Korea Innovation Survey data. The main contribution of the paper is to investigate the distribution of R&D supports at the national level, instead of the program level. Especially, it is the first academic effort to evaluate the effects of regional and industrial variables. The results show that: (1) firm size and export increase the probability of receiving government’s R&D support; (2) variables measuring firms’ innovative ability, such as official designation as innovative firm, running R&D institute, number of R&D personnel, also have significantly positive effects; (3) firms in the chemical and automobile industries are more likely to receive R&D supports; and (4) firms in Teakyoung and Bukyoung regions are more likely to receive R&D supports.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.7B
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• pp.695-705
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• 2002

In this paper, we propose a simple open loop transmit diversity (TD) scheme for the wideband code division multiple access (W-CDMA) systems in Rician multipath fading channels such as rural area or satellite channels where line-of-sight (LOS) paths are in presence. The proposed scheme does not require any pre-processing of transmit data, resulting in simpler structure as compared to conventional closed loop transmit adaptive array (TxAA) and open loop space-time transmit diversity (STTD). We analytically derive the probability density function of signal-to-noise ratio at the Rake receiver output and the uncoded bit error rate performance of the proposed scheme. Extensive simulation is Performed to verify the analytical performance of the proposed scheme under typical Rician multipath fading channel environments. Moreover, comparative results with the conventional TxAA and STTD are also provided. Simulation results show that the proposed scheme shows slightly better performance than the conventional open loop STTD under the channels with very weak LOS components, however, it significantly outperforms the STTD under the channels with dominant LOS components, and achieves a close performance of ideal closed loop TxAA.