• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.205-208
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• 2008

This paper propose a advanced technique for exciting and receiving the guided torsional wave to detect flaws in pipe systems. There are some difficulties in selecting and exciting of modes by using the nickel strip attached on pipe systems, such as qualification of residual magnetic field and multi-exciting of the unwanted modes etc. In order to there difficulties we propose the new sensor, so called Crossed-coils sensor. We will prove that it is possible to select the modes to be excited and to find a optimal excitation condition for torsional mode by using the proposed sensor.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.856-862
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• 2008

This paper propose a advanced technique for exciting and receiving the guided torsional wave to detect flaws in pipe systems. There are some difficulties in selecting and exciting of modes by using the nickel strip attached on pipe systems, such as qualification of residual magnetic field and multi-exciting of the unwanted modes etc. In order to there difficulties we propose the new sensor, so called Crossed-coils sensor. We will prove that it is possible to select the modes to be excited and to find a optimal excitation condition for torsional mode by using the proposed sensor.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1164-1168
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• 2010

수자원이 우리 생활의 전반적으로 중요한 역할을 차지하면서 댐의 효율적인 운영과 안정적인 용수공급에 대한 연구는 지속적으로 수행되어지고 있다. 1990년대 이후 비선형적인 특성을 잘 모의하는 장점을 가진 인공신경망(ANN)을 이용하여 유입량 예측에 대한 많은 연구가 수행되었다. 하지만 ANN 모형을 포함한 회귀모형은 월 강우 및 유입량의 예측에 대해 간편하게 사용을 할 수 있지만, 예측의 정확성에 한계를 가지고 있다. 본 연구에서는 ANN 모형과 회귀모형의 예측오차를 후처리 과정을 통하여 오차를 줄임으로써 예측모형의 성과를 향상시키는 방법을 제안하였다. 연구지역은 금강수계의 대청댐 유역으로, 1982년 9월부터 2005년 12월에 해당하는 유역 내 11개 지점의 강우관측소에서 관측한 월 강우와 댐 유입량을 수집하여 모형을 구축하였다. 강우량과 유입량 자료에 대해 자기상관함수와 교차상관함수를 이용하여 입력변수를 결정하였고, 정규화를 통한 전처리 과정을 거쳐 ANN 모형과 회귀모형을 이용한 예측모형을 구축하였으며, 예측성과의 향상을 위하여 군집 분석을 이용하여 오차를 재조정하였다. 이러한 오차 후처리 과정을 포함한 모형은 RMSE와 상관계수를 이용하여 비교 평가한 결과, 예측성과를 약 40% 정도 향상시켰다.

• Environmental and Resource Economics Review
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• v.4 no.2
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• pp.223-242
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• 1995

본 연구는 1977년 부터 한국에서 적용된 계절 시간대별 차등요금에 대한 반응성을 분석하기 위하여 각 요금적용시간대에 대한 전력소비의 탄력성을 1987년 1월부터 1992년 12월 까지의 자료를 이용하여 초월대수 비용 함수 (Translog Cost Function)을 이용하여 추정 분석하였다. 추정결과 낮 시간대, 저녁시간대, 밤 시간대에 대한 자기가격탄력성은 산업용(을) 고압 A 수용가의 경우 각각 -0.386, 0.351, -0.114이며, 고압 B 수용가는 각각 -0.095, -0.230, -0.192이었다. 일반적으로 대규모 수용가(고압 B)는 소규모 수용가(고압 A)에 비해 계시별 요금제에 대한 반응성이 더 낮은 것으로 나타났다. 한편 교차가격 탄력성 산출결과 상호 시간대간에 전력사용량의 대체성이 존재함을 알 수 있다. 즉, 산업용(을) 고압 A 수용가는 낮시간대와 저녁시간대간에 강한 대체성이 나타났으며, 산업용(을) 고압 B 수용가는 저녁시간대와 밤시간대간에 대체성이 높은 것으로 나타났다. 또한 계시별 요금제 구조의 변화에 따른 수용가의 반응성을 분석하기 위해 표본기간을 1987년 1월 부터 1989년 12월 까지(기간 I)와 1990년 1월 부터 1992년 12월 까지 (기간 II)로 분리하여 탄력성을 추정하였다. 기간 I에서는 계시별 요금제에 대한 수용가의 반응성이 아주 낮았으나, 기간 II에서는 현저하게 높아졌다. 이러한 결과로 보아 기간 II에서 시행된 1991. 6의 요금구조 개편은 수용가의 반응성을 증가시키는데 크게 기여하였으며, 이에 따라 계절 시간대별 차등 요금제가 부하관리를 위한 효율적인 방법임을 알 수 있었다.

• Journal of Soil and Groundwater Environment
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• v.19 no.4
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• pp.23-30
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• 2014

Coastal aquifer in Muan, Jeonnam, has experienced heavy seawater intrusion caused by the extraction of a substantial amount of groundwater for the agricultural purpose throughout the year. It was observed that groundwater level dropped below sea level due to heavy pumping during a dry season, which could accelerate seawater intrusion. Therefore, water level needs to be monitored and managed to prevent further seawater intrusion. The purpose of this study is to develop the autoregressive-cross-regressive (ARCR) models that can predict the present or future groundwater level using its own previous values and pumping events. The ARCR model with pumping and water level data of the proceeding five hours (i.e., the model order of five) predicted groundwater level better than that of the model orders of ten and twenty. This was contrary to expectation that higher orders do increase the coefficient of determination ($R^2$) as a measure of the model's goodness. It was found that the ARCR model with order five was found to make a good prediction of next 48 hour groundwater levels after the start of pumping with $R^2$ higher than 0.9.

• Korean Journal of Childcare and Education
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• v.15 no.5
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• pp.23-45
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• 2019

Objective: The purpose of this study is to identify the longitudinal reciprocal relationship between young children's vocabulary ability and physical aggression in young children. Methods: Two waves of panel data(2013/2015) from the Panel Study of Korean Children were analyzed in this study by using an adapted version of Autoregressive cross-lagged modeling. A total of 306 five-year-old and seven-year-old preschoolers, and their mothers participated in the study. Autoregressive cross-lagged modeling for multiple groups was conducted by using AMOS 24.0. Results: First, vocabulary ability and physical aggression showed stability over time. Second, young children's vocabulary ability(t) had a statistically significant effect on physical aggression(t+1). Conclusion/Implications: This study confirmed the interrelationships of young children's vocabulary ability and physical aggression by examining longitudinal data using the longitudinal analysis method. This study highlights the importance of developing interventions to support language development with aggressive children. The results of the present study can be used as a source in developing policies for aggressive children and their parents.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.773-794
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• 2021

Prediction of vehicle traffic volume is very important in planning municipal administration. It may help promote social and economic interests and also prevent traffic congestion costs. Traffic volume as a time-varying trajectory is considered as functional data. In this paper we study three functional regression models that can be used to predict an unseen trajectory of traffic volume based on already observed trajectories. We apply the methods to highway tollgate traffic volume data collected at some tollgates in Seoul, Chuncheon and Gangneung. We compare the prediction errors of the three models to find the best one for each of the three tollgate traffic volumes.

• Journal of Child Welfare and Development
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• v.16 no.2
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• pp.109-135
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• 2018

The purpose of this study was to analyze the longitudinal causal relationship between caregiver relations and peer relations of children in out-of-home care. We analyzed the three years(2011-2013) of longitudinal data from the Panel Study on Korean Children in Out-of-Home Care. The autoregressive cross-lagged model (ARCL) was used to measure the longitudinal causal relationship between caregiver relations and peer relations. As a result, first, caregiver relations and peer relations showed stability over time. In other words, the results of the measurement at three time points showed that the caregiver relations and peer relations at the previous time had a significant effect on the caregiver relations and peer relations at the later time point. Second, the previous caregiver relations had a significant effect on the subsequent peer relations over time. Third, the previous peer relations had a significant effect on the subsequent caregiver relations over time. This study confirmed the interrelationships of caregiver relations and peer relations of children in care by examining the longitudinal data using the longitudinal analysis method.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.281-293
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• 2022

Time series analysis was performed on data from 2009 to 2018 from the Chuncheon groundwater observation network to understand the characteristics of groundwater level fluctuations in the network. There are five observatories, all of which are installed in rock aquifers, and periodic inspections and management are performed by the relevant operating organization. Auto-correlation, spectral density, and cross-correlation analysis was performed.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.271-279
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• 2024

This study was conducted to examine the policies and current status of career education at universities and to compile foundational data for improving career education through an analysis of undergraduate's career awareness and career education programs. The data was collected by restructuring career education-related items from a career awareness survey conducted on 1,322 enrolled students at G University. Analyzing students' career awareness based on their year and major, a cross-analysis was conducted, while the preference for career education programs was analyzed using descriptive statistics. Based on the research findings, the proposal was made to strengthen career exploration programs through self-understanding, expedite the timing of career decision-making, and highlight the necessity of developing career education programs tailored to individual career readiness levels.