• Journal of Radiation Protection and Research
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• v.33 no.2
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• pp.67-76
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• 2008

As the first comprehensive attempt at a national implementation, this study aims at assessing the external costs of major electricity generation technologies in Korea, particularly an evaluation of the impacts on human health resulting from exposures to atmospheric radiological emissions from nuclear power plants, and a monetary quantification of their damages. The methodology used for the assessment of the externalities of the selected fuel cycles has been developed by the International Atomic Energy Agency (IAEA), namely the SimPacts Model Package. The model is internationally recognized as a tool which can be applied to a wide range of fuels, different technologies and locations, for an externalities study. In this study, the relevant emissions are quantified first and then their impacts on human health are evaluated and compared. The study focused on all the nuclear power plants for the last 6 years ($2001{\sim}2006$) in Korea. With respect to nuclear power, the impact analysis only focuses on a power generation, however the front- and back-end nuclear fuel cycles are not included, namely uranium mining, conversion, enrichment, reprocessing, conditioning, etc., because these facilities are not present in Korea. The analysis results show that nuclear power in general, generates low external costs. The highest damage costs from the nuclear power plants among the 4 sites in Korea were estimated to be 3.9 mills/MWh, which is about 1/20th of the result for a similar case study conducted in the U.K., implemented through the ExternE project. This difference is largely due to the number of radionuclides included in the study and the amount of released radioactive emissions based on up-to-date information in Korea. In this study, the sensitivities of the major factors for nuclear power plants were also calculated. The analysis indicates that there was around a ${\pm}3%$ damage costs variation to a ${\pm}15%$ change of the reference population density and a ${\pm}1%$ damage cost variation to a $1{\sim}30$ meters change of the effective release height, respectively. These sensitive calculations show that there is only a minor difference when the reference costs are compared.

• Journal of Korean Library and Information Science Society
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• v.30 no.3
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• pp.97-116
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• 1999

The purpose of this paper is to develop a model of the strategic management of university library in Korea. The model from this study is summarized as follows: 1. External environment is divide into opportunities and threats. 2) Internal environment is divide into strengths and weakness. We can formulate a management strategy on the basis of library environment element from environment analysis and library situation. 2. Formulation of strategic management are formulated through three stages. 1) Library strategy: $\circled1$Growth strategy $\circled2$Stability $\circled3$Retrenchment 2) Business(competition) strategy 3) Functional strategy: $\circled1$Material organization strategy $\circled2$Collection strategy $\circled3$Reference service strategy $\circled4$Human resource management strategy $\circled5$marketing strategy 3. Implementation of strategic management 1) The chief of strategy implementation 2) Programs, budgets and procedures 3) Structure and strategy implementation 4) culture and strategy implementation 4. Evaluation and control of strategy implementation.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.85-86
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• 2006

In this paper, a nonlinear controller based on adaptive sliding-mode method which has a sliding surface vector including new boundary function is proposed and applied to a two-wheeled voiding mobile robot (WMR). This controller makes the welding point of WMR achieve tracking a reference point which is moving on a smooth curved welding path with a desired constant velocity. The mobile robot is considered in view of a kinematic model and a dynamic model in Cartesian coordinates. The proposed controller can overcome uncertainties and external disturbances by adaptive sliding-mode technique. To design the controller, the tracking error vector is defined, and then the new sliding is proposed to guarantee that the error vector converges to zero asymptotically. The stability of the dynamic system will be shown through the Lyapunov method. The simulations is shown to prove the effectiveness of the proposed controller.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.940-945
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• 2009

This paper presents the design method of low order controller for the active pantograph of electric train system. The pantograph is the most playa role to supply constant current to the train. The design objectives are to have good tracking performance about reference contact force despite the stiffness variation that is like sinusoidal function concerned in train speed or span length of contact wire. In this paper, we consider stiffness variation from external disturbance of active pantograph to simplify model equation, and propose simple second-order controller which is designed by Characteristic ratio assignment(CRA) control method. Finally, we verify time response appling to model equation of real system and frequency response about parameter uncertainty like stiffness variation. it is performed by Matlab version 6.5 and Matlab simulink simulation.

• Korean Journal of Radiology
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• v.23 no.3
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• pp.343-354
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• 2022

Objective: To develop and evaluate a deep learning-based artificial intelligence (AI) model for detecting skull fractures on plain radiographs in children. Materials and Methods: This retrospective multi-center study consisted of a development dataset acquired from two hospitals (n = 149 and 264) and an external test set (n = 95) from a third hospital. Datasets included children with head trauma who underwent both skull radiography and cranial computed tomography (CT). The development dataset was split into training, tuning, and internal test sets in a ratio of 7:1:2. The reference standard for skull fracture was cranial CT. Two radiology residents, a pediatric radiologist, and two emergency physicians participated in a two-session observer study on an external test set with and without AI assistance. We obtained the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity along with their 95% confidence intervals (CIs). Results: The AI model showed an AUROC of 0.922 (95% CI, 0.842-0.969) in the internal test set and 0.870 (95% CI, 0.785-0.930) in the external test set. The model had a sensitivity of 81.1% (95% CI, 64.8%-92.0%) and specificity of 91.3% (95% CI, 79.2%-97.6%) for the internal test set and 78.9% (95% CI, 54.4%-93.9%) and 88.2% (95% CI, 78.7%-94.4%), respectively, for the external test set. With the model's assistance, significant AUROC improvement was observed in radiology residents (pooled results) and emergency physicians (pooled results) with the difference from reading without AI assistance of 0.094 (95% CI, 0.020-0.168; p = 0.012) and 0.069 (95% CI, 0.002-0.136; p = 0.043), respectively, but not in the pediatric radiologist with the difference of 0.008 (95% CI, -0.074-0.090; p = 0.850). Conclusion: A deep learning-based AI model improved the performance of inexperienced radiologists and emergency physicians in diagnosing pediatric skull fractures on plain radiographs.

• Asian Journal of Atmospheric Environment
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• v.11 no.4
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• pp.330-343
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• 2017

Climate change is an important issue, with many researches examining not only future climatic conditions, but also the interaction of climate and air quality. In this study, a new version of the emissions processing software tool - Python-based PRocessing Operator for Climate and Emission Scenarios (PROCES) - was developed to support climate and atmospheric chemistry modeling studies. PROCES was designed to cover global and regional scale modeling domains, which correspond to GEOS-Chem and CMAQ/CAMx models, respectively. This tool comprises of one main system and two units of external software. One of the external software units for this processing system was developed using the GIS commercial program, which was used to create spatial allocation profiles as an auxiliary database. The SMOKE-Asia emissions modeling system was linked to the main system as an external software, to create model-ready emissions for regional scale air quality modeling. The main system was coded in Python version 2.7, which includes several functions allowing general emissions processing steps, such as emissions interpolation, spatial allocation and chemical speciation, to create model-ready emissions and auxiliary inputs of SMOKE-Asia, as well as user-friendly functions related to emissions analysis, such as verification and visualization. Due to its flexible software architecture, PROCES can be applied to any pregridded emission data, as well as regional inventories. The application results of our new tool for global and regional (East Asia) scale modeling domain under RCP scenario for the years 1995-2006, 2015-2025, and 2040-2055 was quantitatively in good agreement with the reference data of RCPs.

• Journal of Soil and Groundwater Environment
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• v.20 no.3
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• pp.51-64
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• 2015

In the present study, we develop two history matching techniques based on Markov chain Monte Carlo method where radial basis function and Gaussian distribution generated by unconditional geostatistical simulation are employed as the random walk transition kernels. The Bayesian inverse methods for aquifer characterization as the developed models can be effectively applied to the condition even when the targeted information such as hydraulic conductivity is absent and there are transient hydraulic head records due to imposed stress at observation wells. The model which uses unconditional simulation as random walk transition kernel has advantage in that spatial statistics can be directly associated with the predictions. The model using radial basis function network shares the same advantages as the model with unconditional simulation, yet the radial basis function network based the model does not require external geostatistical techniques. Also, by employing radial basis function as transition kernel, multi-scale nested structures can be rigorously addressed. In the validations of the developed models, the overall predictabilities of both models are sound by showing high correlation coefficient between the reference and the predicted. In terms of the model performance, the model with radial basis function network has higher error reduction rate and computational efficiency than with unconditional geostatistical simulation.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.3
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• pp.343-350
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• 2012

A planar solid oxide fuel cell (PSOFC) is studied in its application in a high-temperature stationary power plant. Even though PSOFCs with external reformers are designed for application from the distributed power source to the central power plant, such PSOFCs may sacrifice more system efficiency than internally reformed SOFCs. In this study, modeling of the PSOFC with an external reformer was developed to analyze the feasibility of thermal energy utilization for the external reformer. The PSOFC system model includes the stack, reformer, burner, heat exchanger, blower, pump, PID controller, 3-way valve, reactor, mixer, and steam separator. The model was developed under the Matlab/Simulink environment with Thermolib$^{(R)}$ modules. The model was used to study the system performance according to its configuration. Three configurations of the SOFC system were selected for the comparison of the system performance. The system configuration considered the cathode recirculation, thermal sources for the external reformer, heat-up of operating gases, and condensate anode off-gas for the enhancement of the fuel concentration. The simulation results show that the magnitude of the electric efficiency of the PSOFC system for Case 2 is 12.13% higher than that for Case 1 (reference case), and the thermal efficiency of the PSOFC system for Case 3 is 76.12%, which is the highest of all the cases investigated.

• Journal of Adhesion and Interface
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• v.13 no.1
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• pp.9-16
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• 2012

In order to describe external effects on the behavior of the adhesive tape, the semi-rigid body cylinder chain model for adhesive tape has been proposed as follows. Firstly the behavior of the tape is in detail investigated while it's being pulled off from the plate, and subsequently a relevant phenomenological model is designed. Then all the contributors affecting the force to peel out the tape from plate (hereafter, the pull out force) are clearly defined and their sensitivity analyses are made to set up the experimental reference condition, under which the angular dependence of the pull out force is measured in every $10^{\circ}$. The experimental data turn out to be in good agreement with the theoretical ones by our model within the measurement error, and the effects due to other factors are proved to be well explained from the phenomenological viewpoint. From these results, the concept of this study might be expected to be very useful for the test and evaluation of PSA types of adhesive tape.

• Composites Research
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• v.33 no.3
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• pp.108-114
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• 2020

Piecewise Integrated Composite (PIC) beam is composed of different stacking against loading type depending upon location. The aim of current study is to assign robust stacking sequences against external loading to every corresponding part of the PIC beam based on the value of stress triaxiality at generated reference points using the k-NN (k-Nearest Neighbor) classification, which is one of representative machine learning techniques, in order to excellent superior bending characteristics. The stress triaxiality at reference points is obtained by three-point bending analysis of the Al beam with training data categorizing the type of external loading, i.e., tension, compression or shear. Loading types of each plane of the beam were classified by independent plane scheme as well as total beam scheme. Also, loading fidelities were calibrated for each case with the variation of hyper-parameters. Most effective stacking sequences were mapped into the PIC beam based on the k-NN classification model with the highest loading fidelity. FE analysis result shows the PIC beam has superior external loading resistance and energy absorption compared to conventional beam.