• Journal of Industrial Convergence
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• v.20 no.10
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• pp.131-136
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• 2022

This study examines the mediating effect of self-esteem in the influence of family decision-making attitudes on adolescents' human rights awareness. In order to achieve the purpose of this study, data from the Korea Youth Policy Research Institute surveyed in 2018 were used and analyzed. After extracting 693 adolescents with part-time work experience among all respondents in this data, missing values, outliers, and weights were removed, and a total of 511 people were selected as final research subjects. The SPSS WIN 25.0 program was used to verify the influence and mediating effect between measurement variables. As a result of the analysis, the partial mediating effect of self-esteem was confirmed in the influence of decision-making attitudes within the family on the human rights consciousness of adolescents. In addition, the Sobel Test was conducted to confirm the significance of the mediating effect of self-esteem. Based on the results of this study, the necessity of social welfare intervention was suggested for desirable communication between parents and children, raising awareness of human rights and enhancing self-esteem suggested.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.260-269
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• 2022

In this paper, We propose an anomaly detection model using deep neural network to automate the identification of outliers of the national air pollution measurement network data that is previously performed by experts. We generated training data by analyzing missing values and outliers of weather data provided by the Institute of Environmental Research and based on the BeatGAN model of the unsupervised learning method, we propose a new model by changing the kernel structure, adding the convolutional filter layer and the transposed convolutional filter layer to improve anomaly detection performance. In addition, by utilizing the generative features of the proposed model to implement and apply a retraining algorithm that generates new data and uses it for training, it was confirmed that the proposed model had the highest performance compared to the original BeatGAN models and other unsupervised learning model like Iforest and One Class SVM. Through this study, it was possible to suggest a method to improve the anomaly detection performance of proposed model while avoiding overfitting without additional cost in situations where training data are insufficient due to various factors such as sensor abnormalities and inspections in actual industrial sites.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.319-326
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• 2015

Rainfall data is necessary component for water resources design and flood warning system. Most analysis are used long-term hourly data of surface synoptic stations from the Meteorological Administration, Ministry of land, Infrastructure and Transport and others. However, It will be used minutely data of more high density automatic weather stations than surface synoptic stations expecting to increase the frequency of heavy precipitation. But minutely data has a problem about quality of rainfall data by auto observation. This study analyzed about quality control method using automatic weather station's minutely rainfall data of meteorological administration. It was performed assessment of the quality control that was classified quality control of miss Data, outlier data and rainfall interpolation. This method will be utilized when hydrological analysis uses minute rainfall data.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.157-157
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• 2017

우리나라에서는 급속도로 진행되고 있는 도시화의 영향으로 토지사용 방법이 변화함에 따라 도심지 내 불투수율이 증가하고 있으며, 불투수면적과 강우유출량 또한 증가하였다. 이러한 변화는 도심홍수, 수질오염 등의 피해를 더욱 심화시킬 뿐 아니라, 도시유역 물순환 체계 및 자연생태계 균형 파괴 등의 심각한 환경문제를 발생시키고 있다. 이에 국내 외에서 도시유역 물순환 체계 관련 다양한 대안이 검토되고 있으며 외국에서는 약 20년 전부터 저영향개발 (Low Impact Development; LID)을 통한 수자원의 활용과 환경 친화적인 개발에 관심을 기울이고 있다. 국내에서 주로 사용되는 LID 기법은 소규모 유출저감 시설과 녹지면을 이용하여 빗물을 분산시키는 분산형 유출저감 시설물이 있다. 분산형 유출저감 시설물은 빗물의 발생원에서 빗물을 침투 저류시켜 저류된 빗물은 조경용수, 청소용수, 하천 유지용수 등으로 이용하는 친환경 빗물관리 방식으로 침투도랑, 측구형 침투시설, 식생수로, 빗물 저류조, 투수성 블록 등의 다양한 시설물이 이에 포함된다. 현재 이와 같이 LID 시설물이 급속도로 증가하고 있으나 시설물의 저감효과 분석을 위한 모니터링관련 연구가 많지 않은 실정이다. 이에 본 연구에서는 LID 시설물의 유출 저감효과를 분석하기 위해 부산대학교 양산캠퍼스 실증실험단지에 설치되어 있는 LID 시설물의 모니터링 계측결과를 바탕으로 다양한 강우사상에 따른 LID 시설물의 유출저감 효과를 분석하였다. 대상지역의 정확한 유출저감 효과를 분석하기 위한 방안으로 자료의 이상치, 결측치 등을 보정하는 방안을 고려하였으며 실험실증단지에 내리는 강우의 지속시간, 총강우량, 선행강우에 따라 강우사상을 분류하여 이를 토대로 강우사상 별 LID 시설물의 유출 저감효과와 유출 지속시간에 미치는 영향을 분석하였다.

• Journal of Korea Water Resources Association
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• v.48 no.4
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• pp.245-255
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• 2015

This study used high density network of integrated meteorological sensor, which are operated by SK Planet, with KMA weather stations to estimate the quantitative precipitation field in Seoul area. We introduced SK Planet network and analyzed quality of the observed data for 3 months data from 1 July to 30 September 2013. As the quality analysis result, we checked most SK Planet stations observed similar with previous KMA stations. We developed the real-time quality check and adjustment method to reduce the error effect for hydrological application by missing and outlier value and we confirmed the developed method can be corrected the missing and outlier value. Through this method, we used the 190 stations(KMA 34 stations, SK Planet 156 stations) that missing ratio is less than 20% and the effect of the outlier was the smallest for quantitative precipitation estimation. Moreover, we evaluated reproducibility of rainfall field high density rain gauge network has $3km^2$/gauge. As the result, the spatial relative frequency of rainfall field using SK Planet and KMA stations is similar with radar rainfall field. And, it supplement the blank of KMA observation network. Especially, through this research we will take advantage of the density of the network to estimate rainfall field which can be considered as a very good approximation of the true value.