• 보건의료산업학회지
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• 제13권3호
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• pp.13-26
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• 2019

Objectives: To investigate whether medical institutions can prevent accidents by analyzing the root cause of a medical accident and identifying the tendencies. Methods: A total of 345 medical cases were used for the RCA(Root Cause Analysis). The root causes were classified using the SHELL model. The suitability of the model was confirmed by SPSS's MDPREF and Euclidean distance. An SPSS20.0 hierarchical regression analysis was used as an influencing factor on the degree of injury resulting from medical accidents. Results: The SHELL model was suitable for classification. The rates of accident causes were LS49%, L34%, LL10.2%, LE3.7%, LH2.3%. The order in which the degree of a patient's injury was affected were: Risk Threshold (${\beta}=.180$), Time (${\beta}=.175$), Surgical stage (${\beta}=-.166$), Do not use procedure (${\beta}=.147$). Conclusions: Health care institutions should remove priorities through system improvement and training. For patients' safety, the five factors of the SHELL model should be managed in harmony.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.176-176
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• 2023

The Tonle Sap is the richest and diverseness of freshwater ecosystem in Southeast Asia, receiving nurturing water flows from the Mekong and its immediate basin. In addition, the rapid development in the Tonle Sap Lake (TSL) Basin, and flood inundation may threaten the natural diversities and characteristics. The impacts of flood inundation in 11 sub-basins contributing to the Tonle Sap Lake were assessed using the Rainfall-Runoff-Inundation (RRI) model to quantify the potential magnitude and extent of the flooding. The RRI model is set up by using gauged rainfall data to simulate the information of river discharge and flood inundation of huge possible flood events. Moreover, two satellite precipitation products (SPPs), CHIRPS and GSMaP, within respectively spatial resolutions of 0.05° and 0.1°, are utilized as an input for the RRI model to simulate river discharge, flood depth, and flood extent for the great TSL Basin of Cambodia. This study used statistical indicators such as NSE, PBIAS, RSR, and R2 as crucial indices to evaluate the performance of the RRI model. Therefore, the findings of this study could provide promising guidance in hydrological modeling and the significant implications for flood risk management and disaster preparedness in the region.

• Journal of Electrical Engineering and Technology
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• 제2권3호
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• pp.306-311
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• 2007

The transient fields generated during switching operations in a Gas Insulated Substation (GIS) are associated with high frequency components in the order of few tens of MHz. These transient fields leak into the external environment of the gas-insulated equipment and can interfere with the nearby electronics. Measurements of the transient fields are thus required to characterise the interference caused by switching phenomena in such substations. In view of the above, E-field emission measurement during a switching operation has been carried out for a 245 kV GIS model, using a resonant dipole antenna and D-dot sensor. The characteristics of the E-fields i.e., frequency spectra and their levels have been analysed and are reported in the paper. Suitability of the measurements has been confirmed by comparing frequency spectra of the measured and computed transient fields.

• 한국실천공학교육학회논문지
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• 제3권2호
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• pp.69-74
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• 2011

본 논문에서는 정보교육과정의 "문제해결방법과 절차" 영역에 필요한 알고리즘적 사고 문제 모델을 활용하고, 두리틀 프로그래밍 내용 요소를 적용하여 두리틀 프로그래밍 알고리즘적 사고 문제를 제안하였다. 그리고 개발된 두리틀 프로그래밍 알고리즘적 사고 문제들에 대해 실험수업을 실시하여 알고리즘적 사고에 따른 답안들의 다양성과 효율성 및 개발된 문제들의 난이도 적절성에 대한 분석을 통해 본 논문에서 제안된 문제들에 대한 두리틀 프로그래밍 알고리즘적 사고 문제로서의 적합성을 검증하였다.

• 한국정밀공학회지
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• 제31권10호
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• pp.947-954
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• 2014

Performance of next generation susceptor is affected by temperature uniformity in order to produce reliably large-sized flat panel display. In this paper, we propose a learning estimation model of susceptor to predict and appropriately assess the temperature uniformity. Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) are compared for the suitability of the learning estimation model. It is proved that SVMs provides more suitable verification of uniformity modeling than ANNs during each stage of temperature variations. Practical procedure for uniformity estimation of susceptor temperature was developed using the SVMs prediction algorithm.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1548-1555
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• 2017

This paper attempts to employ and investigate neural based approaches as interpolation tools for modeling of Switched Reluctance Motor (SRM) drive. Precise modeling of SRM is essential to analyse the performance of control strategies for variable speed drive application. In this work the suitability of Generalized Regression Neural Network (GRNN) and Extreme Learning Machine (ELM) in addition to conventional neural network are explored for improving the modeling accuracy of SRM. The neural structures are trained with the data obtained by modeling of SRM using Finite Element Analysis (FEA) and the trained neural network is incorporated in the model of SRM drive. The results signify the modeling accuracy with GRNN model. The closed loop drive simulation is performed in MATLAB/Simulink environment and the closeness of the results in comparison with the experimental prototype validates the modeling approach.

• 한국압력기기공학회 논문집
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• 제8권1호
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• pp.25-32
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• 2012

Korea Hydro & Nuclear Power Co. (KHNP) has developed and implemented the maintenance effectiveness monitoring (MR) programs for the operating nuclear power plants. The MR program is developed by reflecting design characteristics of the operating nuclear power plants to monitor the plant performance for improving the safety and reliability. Recently, KHNP has built a new nuclear power plant, and developed the MR program to establish the advanced maintenance system by reflecting unique design characteristics based on the OPR1000 standard model. So, the MR program developed in this study has another characteristics in comparison with the OPR1000 standard model, and we will verify the suitability of the MR program through evaluating initial performance of the plant. The safety and reliability of the new plant will be improved by developing and implementing the MR program.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 춘계학술대회 논문집
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• pp.1142-1147
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• 2004

In this study, two damage detection techniques are applied to the railway tunnel liner based on the static deformation data. Models based on uniform reduction of stiffness and smeared crack concept are both employed, and the efficiency and relative advantage are compared with each other. Numerical analyses are performed on the idealized tunnel structure and the effect of white noise, common in most measurement data, is also investigated to better understand the suitability of the proposed models. As a result, model 1 based on uniform stiffness reduction method is shown to be relatively insensitive to the noise, while model 2 with the smeared crack concept is proven to be easily applied to the field situation since the effect of stiffness reduction is rather small. Finally, real deformation data of a rail tunnel in which health monitoring system is in operation are introduced to find the possible damage and it is shown that the prediction shows quite satisfactory result.

• 산업기술연구
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• 제31권B호
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• pp.107-112
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• 2011

Recently, climate change around the world due to global warming has became an important issue and damages by climate change have a bad effect on human life. Changes of Sea Surface Temperature(SST) is associated with natural disaster such as Typhoon and El Nino. So we predicted daily future SST using Statistical Downscaling Method and CGCM 3.1 A1B scenario. 9 points of around Korea peninsular were selected to predict future SST and built up a regression model using Multiple Linear Regression. CGCM 3.1 was simulated with regression model, and that comparing Probability Density Function, Box-Plot, and statistical data to evaluate suitability of regression models, it was validated that regression models were built up properly.

• Smart Structures and Systems
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• 제4권2호
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• pp.137-152
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• 2008

The work presented in this paper includes material characterisation and an investigation of suitability in seismic dampers for two commercially available NiTi-alloys, along with a numerical analysis of a new damper system employing composite NiTi-wires. Numerical simulations of the new damper system are conducted, using Brinson's one-dimensional constitutive model for shape memory alloys, with emphasis on the system's energy dissipation capabilities. The two alloys tested showed some unwanted residual strain at temperatures higher than $A_f$, possibly due to stress concentrations near inclusions in the material. These findings show that the alloys are not ideal, but may be employed in a seismic damper if precautions are made. The numerical investigations indicate that using composite NiTi-wires in a seismic damper enhances the energy dissipation capabilities for a wider working temperature range.