• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.649-655
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• 2021

This study purposes to cross-validate its performance by applying the optimal seismic vulnerability assessment model based on previous studies conducted in Gyeongju to other regions. The test area was Pohang City, the occurrence site for the 2017 Pohang Earthquake, and the dataset was built the same influencing factors and earthquake-damaged buildings as in the previous studies. The validation dataset was built via random sampling, and the prediction accuracy was derived by applying it to a model based on a random forest (RF) of Gyeongju. The accuracy of the model success and prediction in Gyeongju was 100% and 94.9%, respectively, and as a result of confirming the prediction accuracy by applying the Pohang validation dataset, it appeared as 70.4%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2107-2113
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• 2015

This paper proposed a Prior Forecast System of Crossroad Traffic Information that allows vulnerable road users to perceive traffic signal changes beforehand and respond in concentrated traffic areas such as crossroads. Also, it mapped out information linking procedures of the proposed system and it designed a PHY based wireless communication simulator to verify the operational feasibility of wireless communications. Conclusively, by conducting performance analysis according to crossroad channel environments using the simulator designed in this paper, it verified that a Prior Forecast System of Crossroads Traffic Information service for vehicle IT based decision-making support for vulnerable road users is a possibility.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.643-654
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• 2018

In order to understand and manage traffic flows in urban areas in the past, a variety of traffic engineering theoretical indicators such as intersection lag and highway speed have been applied. However, these theories and indicators have been developed under the constraints of traffic engineering research before the construction of intelligent transportation system. Since the ATIS system currently exists, it is necessary to introduce a separate traffic engineering technology that utilizes the data. In this paper, it is aimed to confirm whether it is applicable to intermittent flow (approach road, intersection, control group, main road axis) by using 'congestion intensity' which is already used in traffic engineering field. The results of this study are as follows: (1) The traffic signal improvement effect of urban road access road, intersection road, control group, Two verification studies were performed to verify the derived congestion intensity index. (1) verification of congestion intensity threshold value analysis and (2) crossing improvement using the congestion intensity. Through verification, it was confirmed that it is possible to apply the congestion intensity in the inter - city intermittent flow using the 5 - minute unit speed data so as to be able to escape from the existing traffic signal operation management which is past passive and manpower limit.

• Journal of the Korean Society of Visualization
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• v.19 no.1
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• pp.68-73
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• 2021

In this study, the detection of rubber o-ring defects was carried out using k-fold cross validation and Support Vector Machine (SVM) algorithm. The data process was carried out in 3 steps. First, we proceeded with a frame alignment to eliminate unnecessary regions in the learning and secondly, we applied gray-scale changes for computational reduction. Finally, data processing was carried out using image augmentation to prevent data overfitting. After processing data, SVM algorithm was used to obtain normal and defect detection accuracy. In addition, we applied the SVM algorithm through the k-fold cross validation method to compare the classification accuracy. As a result, we obtain results that show better performance by applying the k-fold cross validation method.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.1
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• pp.43-50
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• 2019

The aviation demand forecast field has been actively studied along with the recent growth of the aviation market. In this study, the demand for domestic passenger demand and freight demand was estimated through cross-validation method. As a result, passenger demand is influenced by private consumption growth rate, oil price, and exchange rate. Freight demand is affected by GDP per capita, private consumption growth rate, and oil price. In particular, passenger demand is characterized by temporary external shocks, and freight demand is more affected by economic variables than temporary shocks.

• Proceedings of the Korea Contents Association Conference
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• 2017.05a
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• pp.115-116
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• 2017

자체별 또는 연도별과 같은 공통 요소를 통한 교차 분석이 가능하도록 통합 DB를 설계함으로써 다면적인 연구 분석을 위한 프레임워크를 구축하는 데 중점을 두어야 한다. 본 연구는 지자체 통합 데이터베이스에 구축되고 있는 지자체 통합 데이터의 활용성 검증을 위하여, 데이터마이닝 기법을 적용하여 지자체 통합 데이터를 분석하고자 한다. 데이터마이닝 기법을 적용하기 위해서 데이터의 추출, 적재, 변환의 과정을 수행하고, 이렇게 준비된 데이터를 실제 데이터마이닝 기법을 이용하여 분석하고 결과를 검증하는 과정을 수행하면서 지자체 통합 데이터의 활용성을 검증하고자 한다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.3
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• pp.325-333
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• 2015

Recently, thermal bridge breaker systems(TBBSs) applicable to RC slab-wall connections have been increasingly studied and proposed. This study also aims at proposing an analytic model which is applicable to predicting the flexural behavior of TBBS embedded in slabs from the initial elastic stages, yield states to ultimate conditions. The analytic models are developed by considering strain compatibility, force equilibrium and the constitutive law obtained from material test results. To verify the accuracy of the proposed analytic model, the moment-curvature relationship and change of neutral axis according to the loading states are compared with those of experimental results. Based on the comparison, it is verified that the proposed analytic model provides well predict the flexural behavior of TBBS embedded in slabs.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.481-486
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• 2004

본 연구에서는 분석된 산사태 발생원인을 근거로 산사태 발생 가능 지역에 대한 산사태 발생원인에 대한 등급값을 이용하여, 인접한 연구지역에 교차 적용하여 위험성을 평가하여 취약성도를 작성하고 산사태 피해 예방을 위한 방재 사업, 국토개발 계획 및 건설계획을 위한 기초 자료로 적용 및 활용할 수 있도록 하였다. 연구대상 지역은 여름철 집중호우시 산사태가 많이 발생하는 지역으로 정하였으며, 행정구상으로 강원도 강릉시 사천면 사기막리와 주문진읍 삼교리에 해당한다. 산사태가 발생할 수 있는 요인으로 지형도로부터 경사, 경사방향, 곡률, 수계추출을, 정밀토양도로부터 토질, 모재, 배수, 유효토심, 지형을, 임상도로부터 임상, 경급, 영급, 밀도를, 지질도로부터 암상을, Landsat TM 영상으로부터 토지이용도와 추출하여 격자화 하였으며, 아리랑1호 영상으로부터 선구조를 추출하여 l00m 간격으로 버퍼링한 후 격자화 하였다. 이렇게 구축된 산사태 발생 위치 및 발생요인 데이터베이스를 이용, Frequence ratio를 이용하여 각 요소간의 분류를 산사태와의 상관관계를 바탕으로 취약성도를 구하였다. 그리고 계산된 산사태 취약성 지수의 기존 산사태 발생을 설명하는 능력을 정량적으로 표현하기 위하여 추정능력을 계산하였다 또한 이를 교차적용 하여 산사태 취약성도를 각각의 경우에 맞게 만들었다 이러한 평가는 산사태 피해 예방을 위한 방재 사업, 국토개발 계획, 건설계획 등에 기초자료로서 적용 및 활용될 수 있다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.3
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• pp.369-374
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• 2010

Linear motors are easily affected by load disturbances, force ripples, friction, and parameter variations because there are no mechanical transmissions that can reduce the effects of model uncertainties and external disturbance. In this study, a nonlinear adaptive controller to achieve high-speed/high-accuracy position control of a two-axis linear motor is designed. The operation of this controller is based on a cross-coupling algorithm. Nonlinear effects such as friction and force ripples are estimated and compensated for. An enhanced cross-coupling algorithm is proposed for effectively improving the biaxial contour accuracy while achieving closed-loop stability. The proposed controller is evaluated by performing computer simulations.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.963-973
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• 2019

This study reviews a urban flooding risk criteria estimation model to predict risk criteria in areas where flood risk criteria are not precalculated by using watershed characteristic data and limit rainfall based on damage history. The risk criteria estimation model was designed using Support Vector Machine, one of the machine learning algorithms. The learning data consisted of regional limit rainfall and watershed characteristic. The learning data were applied to the SVM algorithm after normalization. We calculated the mean absolute error and standard deviation using Leave-One-Out and K-fold cross-validation algorithms and evaluated the performance of the model. In Leave-One-Out, models with small standard deviation were selected as the optimal model, and models with less folds were selected in the K-fold. The average accuracy of the selected models by rainfall duration is over 80%, suggesting that SVM can be used to estimate flooding risk criteria.