• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.126-136
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• 2018

The purpose of this study was to develop a severity-adjustment model for predicting mortality in acute stroke patients using machine learning. Using the Korean National Hospital Discharge In-depth Injury Survey from 2006 to 2015, the study population with disease code I60-I63 (KCD 7) were extracted for further analysis. Three tools were used for the severity-adjustment of comorbidity: the Charlson Comorbidity Index (CCI), the Elixhauser comorbidity index (ECI), and the Clinical Classification Software (CCS). The severity-adjustment models for mortality prediction in patients with acute stroke were developed using logistic regression, decision tree, neural network, and support vector machine methods. The most common comorbid disease in stroke patients were hypertension, uncomplicated (43.8%) in the ECI, and essential hypertension (43.9%) in the CCS. Among the CCI, ECI, and CCS, CCS had the highest AUC value. CCS was confirmed as the best severity correction tool. In addition, the AUC values for variables of CCS including main diagnosis, gender, age, hospitalization route, and existence of surgery were 0.808 for the logistic regression analysis, 0.785 for the decision tree, 0.809 for the neural network and 0.830 for the support vector machine. Therefore, the best predictive power was achieved by the support vector machine technique. The results of this study can be used in the establishment of health policy in the future.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2283-2286
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• 2003

This paper presents conservation of electrical energy in building with harmonics analysis and compensation which occur in electrical system. We use load controlling and management system in order to adjust load factor of system.The maximum demand limiting and controlling are used ,then the system can acquire the prediction and compare it to the maximum demand set point.The electrical signal analysis based on FFT technique. The harmonics are compensated by using harmonic filters.This system consists computer which works as controller, processor , analysis and database unit together with digital power meter in form of multidrop network through serial communication via RS-485.The load control system uses PLC to control load via serial communication RS-485. The A/D converter is used for sampling the electrical signals via parallel port of computer.The harmonic filters are controlled by a computer.The data of measurement such as voltage, current, power, power factor, total harmonic distortion, energy, etc., can be saved as database and analysis. The load factor is adjusted by limiting and controlling maximum demand. The load factor adjustment can reduce the cost of electric consumption and energy generation together with harmonics compensation in order to increase high efficiency of electrical system.

• Journal of the Korean Vacuum Society
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• v.12 no.1
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• pp.64-69
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• 2003

Using a high fewer electron beam gun (max. power 20 kW), Gadolinium (Gd, atomic number 64) metal was melted and the temperature distribution of melted surface was measured. With proper optical filters and the adjustment of aperture of lens, the radiation of melted surface was received by a ccd camera and its signal transferred to a computer. The real time monitoring of melted surface with a variation of electron beam Power was Possible and stable operation of electron beam was achieved. It was found that the max. temperature measured by a ccd camera with an assumption of blackbody radiation of melted Gd surface and adaption of Planet's law was above 100~$200^{\circ}C$ compared to that measured by a pyrometer in the same e-beam power.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.550-558
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• 2014

Direct Torque controlled induction motor (DTC-IM) drives use stator resistance of the motor for stator flux estimation. So, stator resistance estimation properly is very important for a stable and effective operation of the induction motor. Stator resistance variations because of changing in temperature make DTC operation difficult mainly at low speed. A method based on artificial neural network (ANN) to estimate the stator resistance online of IM for DTC drive is modeled and verified in this paper. To train the neural network a back propagation algorithm is used. Weight adjustment of neural network is done by back propagating the error signal between measured and estimated stator current. An extensive simulation has been carried out in MATLAB/SIMULINK to prove the efficacy of the proposed stator resistance estimator. The simulation & experimental result reveals that proposed method is able to obtain precise torque and flux control at low speed.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2435-2443
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• 2022

The once-through steam generator used in the small modular reactor needs to consider the stability of the outlet steam pressure and steam superheat of the secondary circuit to achieve better operating efficiency. For this reason, this paper designs a controllable operation scheme for the steam pressure and superheat of the small reactor once-through steam generator. On this basis, designs a variable universe fuzzy controller, first, design the fuzzy control rules to make the controller adjust the PI controller parameters according to the change of the error; secondly, use the domain adjustment factor to further subdivide the input and output domain of the fuzzy controller according to the change of the error, to improve the system control performance. The simulation results show that the operation scheme proposed in this paper have better system performance than the original scheme of the small reactor system, and controller proposed in this paper have better control performance than traditional PI controller and fuzzy PI controller, what's more, the designed control system also showed better anti-disturbance performance in lifting experiment between 100% and 80% working conditions. Finally, the experimental platform formed by connecting the digital small reactor with Matlab/Simulink through OPC(OLE for Process Control) communication technology also verified the feasibility of the proposed scheme.

• Journal of the Korean Solar Energy Society
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• v.35 no.3
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• pp.65-71
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• 2015

A solar thermal simulator is suitable for indoor experiments of solar receivers and reactors when solar insolation and weather conditions are not favorable. Moreover, due to the easy control of electric power input, the solar thermal simulator allows the adjustment of power input incident on solar receivers and reactors and thus the implementation of accurate experiments. We manufactured a solar simulator, which is comprised of three sets of a xenon lamp and an elliptical reflector. In order to serve as a test facility, optical characterization of the solar simulator via radiation heat flux measurement is a critical prerequisite. We applied the flux mapping method to measuring the heat flux distribution of the three lamps. We presented the measurement results in terms of the heat flux distribution, the peak heat flux, the power distribution, the maximum power, and the efficiency for electric power conversion into radiation power. Characterization results show that our solar simulator provides the peak heat flux of $3,019kW/m^2$, the maximum power of 16.9 kW, and the conversion efficiency of 45%, additionally with a 10% operation margin for output increase.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.603-610
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• 2021

In this paper, we extract the user's power consumption patterns, and model the optimal consumption patterns by applying the user's environment and emotion. Based on the comparative analysis of these two patterns, we present an efficient power consumption method through changes in the user's power consumption behavior. To extract significant consumption patterns, vector standardization and binary data transformation methods are used, and learning about the ensemble's ensemble with k-means clustering is applied, and applying the support factor according to the value of k. The optimal power consumption pattern model is generated by applying forced and emotion-based control based on the learning results for ensemble aggregates with relatively low average consumption. Through experiments, we validate that it can be applied to a variety of windows through the number or size adjustment of clusters to enable forced and emotion-based control according to the user's intentions by identifying the correlation between the number of clusters and the consistency ratios.

• Journal of International Academy of Physical Therapy Research
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• v.3 no.2
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• pp.469-474
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• 2012

The purpose of this study is to analyze the correlation between the stature and the muscle performance ratings and the subjective discomfort rations at performing lower arm's pronation and supination according to change sin the height of working table for more efficient performance at designing a working table and performing a work. For the purpose, this study conducted an experiment targeting 40 people in their 20s, who were classified into 4 groups each group composing 10 people at intervals of 5cm from the standard stature of 166.5cm. The experiment measured the maximum isometric pronation and the supination muscular power, and at measuring the factors, the heights of working tables were set as 800mm, 850mm, and 900mm. From the measurement results, it was found that the stature and the maximum muscular power was correlated. That is, as the experiment groups's average stature is higher, the maximum muscular power was higher. For the correlation between the motion patterns(pronation and supination) and the maximum muscular power, it was seen that the maximum muscular power was higher at performing the pronation than the supination. In the correlation between motion patterns and the subjective discomfort ratings, it was seen that the subjective discomfort rating was higher at performing the supination than the pronation. For the correlation between height adjustment and the subjective discomfort ratings, as the height of working table was lower, the subject discomfort rating was lower. Therefore there was no difference in the maximum muscular power according to the height changes of working table, but it was found that as the working table was higher, the user felt more comfortable.

• Proceedings of the Korean System Dynamics Society
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• 2002.02a
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• pp.19-40
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• 2002

The intent of this study is to develop system dynamics model for assessment of organizational and human factors in nuclear power plant which can contribute to secure the nuclear safety. Previous studies are classified into two major approaches. One is engineering approach such as ergonomics and probability safety assessment(PSA). The other is social science approach such like sociology, organization theory and psychology. Both have contributed to find organization and human factors and to present guideline to lessen human error in NPP. But, since these methodologies assume that relationship among factors is independent they don't explain the interactions among factors or variables in NPP. To overcome these limits, we have developed system dynamics model which can show cause and effect among factors and quantify organizational and human factors. The model we developed is composed of 16 functions of job process in nuclear power, and shows interactions among various factors which affects employees' productivity and job quality. Handling variables such like degree of leadership, adjustment of number of employee, and workload in each department, users can simulate various situations in nuclear power plant in the organization side. Through simulation, user can get insight to improve safety in plants and to find managerial tools in the organization and human side. Analyzing pattern of variables, users can get knowledge of their organization structure, and understand stands of other departments or employees. Ultimately they can build learning organization to secure optimal safety in nuclear power plant.

• Journal of Korea Technology Innovation Society
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• v.17 no.2
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• pp.355-379
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• 2014

For the transition to the low carbon society, it is inevitable but difficult journey that the new energy technology spread co-exists with formal social system. The objective of offshore wind power plant that has been implemented by the government is to connect large capacity new renewable energy to the central electric power system. Therefore, for the successful introduction of offshore wind power system, the transition of the formal social technology system should be companied. This study analysis the energy system transition about niche strategy adjustment using Multiple Level Perspectives & Strategic Niche Management. It also multi level analyzes and structuralizes the process that new technology, as a research result, evolves through connecting and communicating with formal regime and landscape. Also, adjusting Strategic Niche Management, it diagnoses the obstructive factors in the initial stage of niche experiment and found the major reasons why offshore wind power test plant had been delayed. Through this study, it reaches to the practical implication that offshore niche technology could grow stably in the energy system and various policies.