• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.721-740
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• 2019

Noise reduction is an important field in image processing and requires a statistical approach. However, it is difficult to assume a specific distribution of noise, and a spatial filter that reflects regional characteristics is a small sample and cannot be accessed in a parametric manner. The first order image differential and the second order image differential show a clear difference according to the noise level included in the image and can be more clearly understood using the canyon edge detector. The Fligner-Killeen test was performed and the bootstrap method was used to statistically check the noise level. The estimated noise level was set between 0 and 1 using the cumulative distribution function of the beta distribution. In this paper, we propose a nonparametric noise reduction algorithm that accounts for the noise level included in the image.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.889-899
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• 2017

Independent component analysis is a multivariate approach to separate mixed signals into original signals. It is the most widely used method of blind source separation technique. ICA uses linear transformations such as principal component analysis and factor analysis, but differs in that ICA requires statistical independence and non-Gaussian assumptions of original signals. PCA have a natural ordering based on cumulative proportion of explained variance; howerver, ICA algorithms cannot identify the unique optimal ordering of the components. It is meaningful to set order because major components can be used for further analysis such as clustering and low-dimensional graphs. In this paper, we compare the performance of several criteria to determine the order of the components. Kurtosis, absolute value of kurtosis, negentropy, Kolmogorov-Smirnov statistic and sum of squared coefficients are considered. The criteria are evaluated by their ability to classify known groups. Two types of data are analyzed for illustration.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.525-534
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• 2012

The purpose of this study is to increase the employment rate of graduates in the fields of the S/W and H/W. In order to seek employment in various major fields of the S/W and H/W, firstly, this paper proposes the educational case study that increases the concern about employment and develops learner's ability in the unfavorable major fields. Secondly, this paper presents the future driving improvement for the employment rate on the basis of the department's special characteristics and the actual circumstances in the fields of the S/W and H/W. This paper conducts the surveys of each 40 seniors majoring in S/W and H/W respectively in order to measure the understanding of probability/statistics which has been used as tools in the unfavorable major fields. With the purpose of increasement on the employment rate, the paper is designed to have 3 steps, that is, a preliminary questionnaire for employment preference, major courses connecting probability/statistics and a post-questionnaire for employment preference, which eventually investigates the changes of the perception on employment. This paper is verified by the multiple regression analysis to approve the effect on improving learner's academic achievement.

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.283-292
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• 2008

Smoothing parameter or bandwidth plays a key role in nonparametric classification based on kernel density estimation. We consider choosing smoothing parameter in nonparametric classification, which optimize the Bayes risk. Hall and Kang (2005) clarified the theoretical properties of smoothing parameter in terms of minimizing Bayes risk and derived the optimal order of it. Bootstrap method was used in their exploring numerical properties. We compare cross-validation and bootstrap method numerically in terms of optimal order of bandwidth. Effects on misclassification rate are also examined. We confirm that bootstrap method is superior to cross-validation in both cases.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.81-85
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• 2002

We present a statistical analysis of Korean phonological variations using automatic generation of phonetic transcription. We have constructed the automatic generation system of Korean pronunciation variants by applying rules modeling obligatory and optional phonemic changes and allophonic changes. These rules are derived from knowledge-based morphophonological analysis and government standard pronunciation rules. This system is optimized for continuous speech recognition by generating phonetic transcriptions for training and constructing a pronunciation dictionary for recognition. In this paper, we describe Korean phonological variations by analyzing the statistics of phonemic change rule applications for the 60,000 sentences in the Samsung PBS(Phonetic Balanced Sentence) Speech DB. Our results show that the most frequently happening obligatory phonemic variations are in the order of liaison, tensification, aspirationalization, and nasalization of obstruent, and that the most frequently happening optional phonemic variations are in the order of initial consonant h-deletion, insertion of final consonant with the same place of articulation as the next consonants, and deletion of final consonant with the same place of articulation as the next consonants. These statistics can be used for improving the performance of speech recognition systems.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.125-140
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• 2008

The purpose of this study is to analysis the economic impacts of regional cultural festival via using the regional input-output model. In order to achieve this purpose, calculate output, value added and employment multiplier impacts of the Jeonju International Film Festival. The impacts of the JIFF on regional economic follow as ; Output is 112 hundred million won, value added is 53 hundred million won and employes is 254 labors. We need a new following strategies to obtain highly positive impacts from regional cultural festival. It needs to made networks among sight-seeing places, cultural remains, restaurants, hotels and entertainment institutions, in order to made visitors and customers expend much.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1210-1216
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• 2009

In this paper we analyze the convergence behavior of the recursive least rank (RLR) L-filter. The RLR L-filter is an order statistics filter, filter coefficients of which are the weights according to the order of magnitude of inputs. And RLR L-filter is a non-linear adaptive filter, that uses RLR algorithm for coefficient updating. The RLR algorithm is a non-linear adaptive algorithm based on rank estimates in Robust statistics. The mean and mean-squared convergence behavior of the RLR L-filter is examined with variable step-sizes. The RLR L-filter adapts the median filter type to the heavy-tailed distribution function of impulse noise, and adapts the average filter type to Gaussian noises.

• Korean Security Journal
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• no.8
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• pp.361-377
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• 2004

This study is to examine the relations between the big five critical crime that consist of homicide, robbery, rape, theft, violence and the private security services. To achieve this objective, this research selected the subject of study, specially, 2002 status of the private security such as the number of companies and employees classified by areas along with the big five crime mentioned above classified by area. The research data is secondary data that is from '2003 Crime Analysis' of the Supreme Public Prosecutors' Office and 'The private Security Related Data' of the National Police Agency. The selected data were analyzed according to the variables by using SPSS 10.0 statistics software program. Each hypothesis was verified around the level of significance ${\alpha}$=.05 by using the statistical techniques, such as Descriptive Statistics, Correlation, Regression, etc. The following was the result of the study, First, the total number of the big five crime affects the number of the companies at significant level. Second, the number of the security companies can be explained by the each total number of the big five crime in the order of theft, robbery, violence, rape and murder. Third, the total number of the big five crime affects the number of the security employees at significant level. Forth the number of the security employees can be explained by the each total number of the big five crime in the order of theft, robbery, violence, rape and murder.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.7
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• pp.719-729
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• 1992

An improved MXTM (maximum trimmed mean) -CFAR (constant false alarm rate) processor is proposed to reduce false alarm rates In detecting radar targets and Its performance character is ticsare analyzed to be compared with those of other CFAR processors. The proposed MXTM-CFAR processor is obtained by combining the GO (greatest of ) -CFAR processor reducing excessive falsealarm rate at riutter edges with the TM-CFAR processor showing good performances In homo-geneous Jnonhornog eneous background. Performance analyses have been done by computing detection probability, constant false alarm rate and detection thresholds under the homogeneous or multiple target environments and at the clutter edges. Analysis results how that the proposed CFAR processor maintains its performance as good as those of,05(order statistics) and TM-CFAR inhomogeneous and multiple target environments and Can reduce the false alarm rate at clutter edges. Overall computing time hfs been also reduced.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.495-504
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• 2013

Evolutionary algorithms have been applied to multi-objective optimization problems by approximation methods using computational intelligence. Those methods have been improved gradually in order to generate more exactly many approximate Pareto optimal solutions. The paper introduces a new method using support vector machine to find an approximate Pareto frontier in multi-objective optimization problems. Moreover, this paper applies an evolutionary algorithm to the proposed method in order to generate more exactly approximate Pareto frontiers. Then a decision making with two or three objective functions can be easily performed on the basis of visualized Pareto frontiers by the proposed method. Finally, a few examples will be demonstrated for the effectiveness of the proposed method.