• 한국정보과학회:학술대회논문집
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• 한국정보과학회 1998년도 가을 학술발표논문집 Vol.25 No.2 (2)
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• pp.467-468
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• 1998

Impulsive noise appears as black and/or white spots in an image. It is usually caused by errors during the image acquisition or transmission through communication channels. This paper presents a study on the impulsive noise reduction filter of digital image. A much more effective method for removing impulse noise is weighted median filtering. But it loses some information by changing center value with no condition. We propose some new technique to change center value with some conditions. In this paper, the performance of conditional weighted median filter is compared to the commonly used median filter, mean filter, max/min filter, and weighted median filter. A quantitative comparison is performed on MSE (Mean Square Error), RMSE (Root Mean Square Error), and SNR (Signal to Noise Ratio). Proposed conditional weighted median filter can yield better performance than regular filters.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 추계 학술발표회 논문집
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• pp.199-206
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• 2005

• 자원ㆍ환경경제연구
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• 제14권1호
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• pp.51-73
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• 2005

소비자들이 실제로 선택한 행위를 분석하여 국립공원과 같은 자연생태계에 대한 수요를 분석하고 그 경제적 가치를 도출하는 대표적인 방법은 여행비용법과 이산선택모형을 이용하는 방법이다. 한국에서는 여행비용법의 적용사례는 상당히 많이 있으나, 상대적으로 많은 장점을 가짐에도 불구하고 이산선택모형을 적절히 적용한 연구사례는 아직 없는 실정이다. 본 연구는 전국적인 표본조사를 통해 18개 국립공원 가운데 방문지를 선택하는 행위를 조건부로짓모형과 계층로짓모형을 추정해 실증분석하고, 그 결과를 이용해 각 국립공원별 경제적 가치와 국립공원 특성별 경제적 가치를 도출한다.

• 응용통계연구
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• 제22권5호
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• pp.995-1005
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• 2009

금융 시계열 자료들 간의 상관계수는 자산의 배분, 위험관리 그리고 포트폴리오의 선택에 있어서 중요한 역할을 한다. 이러한 상관계수들을 모형화하기 위해 단변량-GARCH 모형을 다변량-GARCH 모형으로 확장시킨 MGARCH류 모형들에 대한 많은 연구들이 진행되고 있다. 특히, CCC 모형 (Bollerslev, 1990)과 DCC 모형 (Engle, 2002)은 다른 모형들에 비해 추정해야 할 모수의 수가 작다는 이점으로 인해 분석에 널리 쓰이고 있다. 본 논문에서는 국내 주가자료에 대해 CCC 모형과 DCC 모형을 적합시킨 후, 각 모형들에 대한 VaR(value at risk)와 사후검증(back-testing), 결합예측영역(joint prediction region) 등을 통하여 두 모형의 예측 능력을 비교해 보고자 한다.

• 경영과정보연구
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• 제24권
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• pp.97-124
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• 2008

This study aimed to explore how the involvement of environment influenced eight subjects group. Thus, experiment was performed to clarify the role that the attitude of university student consumer plays in the communication process depending on the level of engagement of consumer in the environment and method to raise donation for preservation of environment. Analyzing as per the type of appeal, the mark in altruistic appeal type was higher in all variables than egoistic appeal type. Finally, checking the average mark of each variable as per the condition of donation, the value in unconditional donation was higher than in all variables than conditional donation. It was found 3 groups composed of 2 groups with high level of environmental engagement and 1 group with low level of environmental engagement were suitable to double mediation model among the 8 experimental groups. The group where double mediation model best corresponds than any other group was high level related to environment and the group that contacts altruistic appeal and the message in the form of conditional donation. It was also found that the group that has low level of environmental engagement and contacts egoistic appeal type and conditional donation shows the group that corresponds to double mediation model in the second place among the 8 groups. Finally, it was found that the group that has high level of environmental engagement and is stimulated by altruistic appeal and unconditional donation corresponds to double mediation model. Depending on the condition of message stimulation, unconditional donation is found to better correspond to double mediation model than conditional donation. However, opposite phenomena is observed when the level of environmental engagement is high and appeal type is egoistic. Namely, it was found that conditional donation better corresponds to double mediation model than unconditional donation.

• The Journal of Asian Finance, Economics and Business
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• 제8권5호
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• pp.533-542
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• 2021

The main objective of this article is to investigate the existence of the lunar effect during the full moon period (FM period) and the new moon period (NM period) on the selected Islamic stock market returns and volatilities. For this purpose, the Ordinary Least Squares model, Autoregressive Conditional Heteroscedasticity model, Generalised Autoregressive Conditional Heteroscedasticity model and Generalised Autoregressive Conditional Heteroscedasticity-in-Mean model are employed using the mean daily returns data between January 2010 and December 2019. Next, the log-likelihood, Akaike Information Criterion and Schwarz Information Criterion value are analyzed to determine the best models for explaining the returns and volatility of returns. The empirical results have deduced that, during the NM period, excluding Malaysia, the total mean daily returns for all of the selected countries have increased mean daily returns in contrast to the mean daily returns during the FM period. The volatility shocks are intense and conditional volatility is persistent in all countries. Subsequently, the volatility behavior tends to have lower volatility during the FM period and NM period in the Islamic stock market, except Malaysia. This article also concluded that the ARCH (1) model is the preferred model for stock returns whereas GARCH-M (1, 1) is preferred for the volatility of returns.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.2096-2106
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• 2023

Rotating machinery is widely applied in important equipment of nuclear power plants (NPPs), such as pumps and valves. The research on intelligent fault diagnosis of rotating machinery is crucial to ensure the safe operation of related equipment in NPPs. However, in practical applications, data-driven fault diagnosis faces the problem of small and imbalanced samples, resulting in low model training efficiency and poor generalization performance. Therefore, a deep convolutional conditional generative adversarial network (DCCGAN) is constructed to mitigate the impact of imbalanced samples on fault diagnosis. First, a conditional generative adversarial model is designed based on convolutional neural networks to effectively augment imbalanced samples. The original sample features can be effectively extracted by the model based on conditional generative adversarial strategy and appropriate number of filters. In addition, high-quality generated samples are ensured through the visualization of model training process and samples features. Then, a deep convolutional neural network (DCNN) is designed to extract features of mixed samples and implement intelligent fault diagnosis. Finally, based on multi-fault experimental data of motor and bearing, the performance of DCCGAN model for data augmentation and intelligent fault diagnosis is verified. The proposed method effectively alleviates the problem of imbalanced samples, and shows its application value in intelligent fault diagnosis of actual NPPs.

• 디지털융복합연구
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• 제19권1호
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• pp.187-198
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• 2021

본 연구는 소비자 관점에서 리테일 분야의 사물인터넷 기반 제품 및 서비스 활용 현황을 파악하고 각각 서비스의 역할과 소비가치에 대해 분석하고자 한다. 이를 위해 의사결정과정을 구매이전, 구매, 구매이후 단계로 나누고 사물인터넷 제품 및 서비스 사례를 단계별로 분류한 후, 각 재품 및 서비스의 특징 및 소비가치를 분석하였다. 연구결과에 따르면 의사결정과정에 이용되는 사물인터넷 제품 및 서비스는 구매 이전 단계에서 정보제공, 대안비교 기능을 수행하며 구매단계에서는 상호작용, 자동결제시스템에 활용되고 있다. 구매 이후 단계에서는 반복 구매를 유도하고 사후서비스를 제공한다. 의사결정 전반에서 스마트 리테일은 인식 가치, 기능적 가치를 제공하고 구매 이전 단계에서는 상황적 가치 및 사회적 가치를, 구매 이후 단계에서는 상황적 가치를 추가적으로 제공한다. 본 연구는 기존의 기술·산업중심으로 이루어졌던 사물인터넷 연구에서 나아가 소비자중심에서 소비가치를 고찰함으로써 소비자의 만족도 향상과 스마트 리테일의 발전을 위한 조언을 제공함에 있다.

• 응용통계연구
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• 제23권4호
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• pp.669-681
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• 2010

Value-at-Risk(VaR) is an important part of risk management in the financial industry. This paper present a VaR forecasting for financial time series based on the quantile regression for GARCH models recently developed by Lee and Noh (2009). The proposed VaR forecasting features the direct conditional quantile estimation for GARCH models that is well connected with the model parameters. Empirical performance is measured by several backtesting procedures, and is reported in comparison with existing methods using sample quantiles.

• Communications for Statistical Applications and Methods
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• 제6권1호
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• pp.25-32
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• 1999

A single outlier can influence on the least squares estimators and can invalidate analysis based on these estimators. The Cook's statistic has been introduced to measure influence of individual data point on parameter estimation and the quantile of the F distribution is recommended as a reference value. but in practice subjective judgement is applied in the choice of appropriate quantile. A simple reference value is introduced in this paper which is developed by approximating conditional quantities of Cook's measure. The performance of the proposed criterion is evaluated through analysis of real data set.