• Journal of Digital Convergence
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• v.17 no.1
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• pp.403-412
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• 2019

The purpose of this study is to analyze temporal and spatial variations of atopic dermatitis and to identify major factors. Data utilized in the study were collected by the Community Health Survey, KOSIS and so and on from 2009 to 2013. This study was analyzed using descriptive statistics and Geographically weighted regression model. As a result, regional diagnosis rate of atopic dermatitis was increased by 5 years, and difference related to geographic location was so large. The regional characteristics that contribute to the diagnosis of atopic dermatitis were as follows: older adults population ratio, ratio of basic living security received people, depression experience rate, high risk drinking rate, number of wastewater discharge business, number of tobacco retail business, number of fast food restaurant business. This study is meaningful in that it provided basic data on health policy direction and provided information on prioritization of health business in each region.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.147-156
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• 2009

We present a methodology for modeling and solving the transit frequency design problem with variable demand. The problem is described as a bi-level model based on a non-cooperative Stackelberg game. The upper-level operator problem is formulated as a non-linear optimization model to minimize net cost, which includes operating cost, travel cost and revenue, with fleet size and frequency constraints. The lower-level user problem is formulated as a capacity-constrained stochastic user equilibrium assignment model with variable demand, considering transfer delay between transit lines. An efficient algorithm is also presented for solving the proposed model. The upper-level model is solved by a gradient projection method, and the lower-level model is solved by an existing iterative balancing method. An application of the proposed model and algorithm is presented using a small test network. The results of this application show that the proposed algorithm converges well to an optimal point. The methodology of this study is expected to contribute to form a theoretical basis for diagnosing the problems of current transit systems and for improving its operational efficiency to increase the demand as well as the level of service.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.49-59
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• 2022

This study was conducted to develop a teaching competency scales customized for teaching programs conducted by Center for Teaching & Learning at A University. To achieve this purpose, a preliminary study was set up, which consists of three competency groups (basic competency, practice competency, innovation competency) and 26 learning competency factors through a review of previous studies. In order to verify the reliability and validity of the provisional teaching competency scales, an online survey was conducted on A university teachers in September 2020, The collected questionnaire data were organized and exploratory factor analysis and confirmatory factor analysis were conducted. As a result of exploratory factor analysis, 26 teaching competency was reduced to 17. As a result of the confirmatory factor analysis, the model was found to be good, Also, as a result of analyzing the construct reliability and AVE of the confirmed teaching competency factors, all 17 factors showed a good level of .7 or more. The teaching competency scales developed through this study can be used as basic data for performance evaluation and development of new programs of CTL teaching program.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.526-532
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• 2023

Falls are fatal accidents that occur more than 420,000 times a year worldwide. Therefore, to study patients with falls, we found the association between extrinsic injury codes and principal diagnosis S-codes of patients with falls, and developed a prediction model to predict extrinsic injury codes based on the data of principal diagnosis S-codes of patients with falls. In this study, we received two years of data from 2020 and 2021 from Institution A, located in Gangneung City, Gangwon Special Self-Governing Province, and extracted only the data from W00 to W19 of the extrinsic injury codes related to falls, and developed a prediction model using W01, W10, W13, and W18 of the extrinsic injury codes of falls, which had enough principal diagnosis S-codes to develop a prediction model. 80% of the data were categorized as training data and 20% as testing data. The model was developed using MLP (Multi-Layer Perceptron) with 6 variables (gender, age, principal diagnosis S-code, surgery, hospitalization, and alcohol consumption) in the input layer, 2 hidden layers with 64 nodes, and an output layer with 4 nodes for W01, W10, W13, and W18 exogenous damage codes using the softmax activation function. As a result of the training, the first training had an accuracy of 31.2%, but the 30th training had an accuracy of 87.5%, which confirmed the association between the fall extrinsic code and the main diagnosis S code of the fall patient.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6B
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• pp.579-587
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• 2010

The mid-range streamflow forecast was performed using NWP(Numerical Weather Prediction) provided by KMA. The NWP consists of RDAPS for 48-hour forecast and GDAPS for 240-hour forecast. To enhance the accuracy of the NWP, QPM to downscale the original NWP and Quantile Mapping to adjust the systematic biases were applied to the original NWP output. The applicability of the suggested streamflow prediction system which was verified in Geum River basin. In the system, the streamflow simulation was computed through the long-term continuous SSARR model with the rainfall prediction input transform to the format required by SSARR. The RQPM of the 2-day rainfall prediction results for the period of Jan. 1~Jun. 20, 2006, showed reasonable predictability that the total RQPM precipitation amounts to 89.7% of the observed precipitation. The streamflow forecast associated with 2-day RQPM followed the observed hydrograph pattern with high accuracy even though there occurred missing forecast and false alarm in some rainfall events. However, predictability decrease in downstream station, e.g. Gyuam was found because of the difficulties in parameter calibration of rainfall-runoff model for controlled streamflow and reliability deduction of rating curve at gauge station with large cross section area. The 10-day precipitation prediction using GQPM shows significantly underestimation for the peak and total amounts, which affects streamflow prediction clearly. The improvement of GDAPS forecast using post-processing seems to have limitation and there needs efforts of stabilization or reform for the original NWP.

• Computational Structural Engineering
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• v.7 no.4
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• pp.137-144
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• 1994

As for the safety evaluation of existing large-scale structures, methods for the estimation of structural and dynamic properties are studied. Sequential prediction error method in time domain and frequency response function estimators in frequency domain are examined. For this purpose, impact tests are performed on a steel frame structure with 2 bays and 3 floors. Results from both methods are found to be consistent to each others. However those from the finite-element analysis are slightly different from the experimental results. The discrepancies may be caused by the improper modeling of the complex behavior at the connection joints of the model structure.

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.211-227
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• 2018

This study evaluates the prediction skills of stratospheric polar vortex intensification events (VIEs) in Global Seasonal Forecasting System (GloSea5) model, an operational subseasonal-to-seasonal (S2S) prediction model of Korea Meteorological Administration (KMA). The results show that the prediction limits of VIEs, diagnosed with anomaly correlation coefficient (ACC) and mean squared skill score (MSSS), are 13.6 days and 18.5 days, respectively. These prediction limits are mainly determined by the eddy error, especially the large-scale eddy phase error from the eddies with the zonal wavenumber 1. This might imply that better prediction skills for VIEs can be obtained by improving the model performance in simulating the phase of planetary scale eddy. The stratospheric prediction skills, on the other hand, tend to not affect the tropospheric prediction skills in the analyzed cases. This result may indicate that stratosphere-troposphere dynamic coupling associated with VIEs might not be well predicted by GloSea5 model. However, it is possible that the coupling process, even if well predicted by the model, cannot be recognized by monotonic analyses, because intrinsic modes in the troposphere often have larger variability compared to the stratospheric impact.

• Proceedings of the KSMRM Conference
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• 2002.11a
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• pp.105-105
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• 2002

목적： 수소 자기 공명 분광기법은 자기공명 영상으로는 얻을 수 없는 화학적 성분에 대한 정보를 제공하여 암을 포함한 여러 질환의 진단과 예측에 사용된다. 이 기법으로는 어떤 특정한 작은 체적을 선택하여 그 부위에만 자기공명 분광신호를 획득하는 단일 체적기법과 체적 전체를 위상변화를 주면서 여기시킨 후, 데이터 후처리 과정에서 체적별로 분리해내는 다중체적기법이 있다. 다중체적기법은 더 긴 영상 획득시간에도 불구하고 단일 체적기법에 비하여 분광상을 대조군과 비교할 수 있는 잇점이 있다. 뇌를 진단하는데 사용하기 위한 수소분광선을 얻기 위하여 다중체적 화학적 영상기법을 개발하여 모형과 자원자에 대하여 적용하여 그 유용성 확인하였다.

• Proceedings of the KSMRM Conference
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• 2002.11a
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• pp.81-81
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• 2002

목적： 수소 핵 자기 공명 분광기법은 자기공명 영상으로는 얻을 수 없는 화학적 성분에 대한 정보를 제공하여 암을 포함한 여러 질환의 진단과 예측에 사용된다. 이 기법으로는 어떤 특정한 작은 체적을 선택하여 그 부위에만 자기공명 분광신호를 획득하는 단일 체적기법과 체적 전체를 위상변화를 주면서 여기 시킨 후, 데이터 후처리 과정에서 체적별로 분리해내는 다중체적기법이 있다. 다중체적기법은 더 긴 영상 획득시간에도 불구하고 단일 체적기법에 비하여 분광상을 대조군과 비교할 수 있는 잇점이 있다. 뇌를 진단하는데 사용하기 위한 수소분광선을 얻기 위하여 다중체적 화학적 영상기법을 개발하여 모형과 자원자에 대하여 적용하여 그 유용성 확인하였다.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.9-20
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• 2005

Accident type and/or factor identification is important in accident reduction planning. The aim of this paper is to apply the hierarchical approach with binomial distribution and logistic regression analysis to find out types and factors, respectively. Based on 2001 Suwon city black spot data, a binomial distribution modeling approach has been applied to diagnose the black spots, with the help of safety performance modeling approach has been applied to diagnose the black spots, with the help of safety performance function. Then, the logistic regression analysis has been employed to identify the critical factors. Some accident remedies are also reviewed in the light of the model outcomes. The proposed research framework sheds light on a different accident related research and can also be successfully applied to similar studies and sites.