• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.67-73
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• 2002

This paper presents a new design method of optimal continuous deadbeat controller by using second-order smoothing elements. The continuous deadbeat controller is made of a serial integral compensator and a local feedback compensator introduced into the state feedback loop. The decision method of the damping factor and the natural angular frequency of the smoothing element is described. A numerical example is given to show how well input-output characteristics are improved. Especially according to the variable input and disturbance, corresponding CDBC design method is suggested. By computer simulations, control inputs and system outputs are shown to have desirable property such as smoothness.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.7
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• pp.1007-1013
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• 2012

Modeling of photovoltaic power systems is significant to analytically predict its dynamics in practical applications. This paper presents a novel modeling algorithm of such system by using probability and statistic theories. We first establish a linear model basically composed of Fourier parameter sets for mapping the input/output variable of photovoltaic systems. The proposed model includes solar irradiation and ambient temperature of photovoltaic modules as an input vector and the inverter power output is estimated sequentially. We deal with these measurements as random variables and derive a parameter learning algorithm of the model in terms of statistics. Our learning algorithm requires computation of an expectation and joint expectation against solar irradiation and ambient temperature, which are analytically solved from the integral calculus. For testing the proposed modeling algorithm, we utilize realistic measurement data sets obtained from the Seokwang Solar power plant in Youngcheon, Korea. We demonstrate reliability and superiority of the proposed photovoltaic system model by observing error signals between a practical system output and its estimation.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1999.11a
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• pp.273-277
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• 1999

A cold cathode flourescent lamp for the backlight in the notebook computer requires high input voltage about 1300(V) when it turns on. But once a discharge starts, the input voltage can be dropped by about one-third for continued output. The equivalent impedance also varies from open to several dozens of kilo-ohms. The piezoelectric transformer converts electrical energy into mechanical energy and then converts it back to electrical energy at a high voltage. Its high output voltage, high efficiency and small size are suitable for driving the LCD backlight in the notebook computer. The piezoelectric transformer operates near the resonance frequency and the output waveform is close to sine wave with very little noise. This paper suggests an inverter for LCD backlight of notebook computer using piezoelectric transformer that includes voltage to frequency converter for gate signal which is useful for tracking of variable resonance frequency depending on load impedance.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.81-88
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• 1999

A conventional quarter-car suspension system is a single input system with one actuator. Thus, the performance enhancement for ride quality could be limited. In this paper, we propose a novel automotive suspension system for a quarter-car with two independent actuators to improve the control performance. The left eigenstructure assignment method for multi-variable systems has been applied to the proposed novel quarter-car model.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.686-691
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• 1994

For evaluating the response fluctuation of the actual environmental acoustic system excited by arbitrary random inputs, it is important to predict a whole probability distribution form closely connected with evaluation indexes Lx, Leq and so on. In this paper, a new type evaluation method is proposed by introducing three functional models matched to the prediction of the response probability distribution from a problem-oriented viewpoint. Because of the positive variable of the sound intensity, the response probability density function can be reasonably expressed theoretically by a statistical Laguerre expansion series form. The relationship between input and output is described by the regression relationship between the distribution parameters(containing expansion coefficients of this expression) and the stochastic input. These regression functions are expressed in terms of the orthogonal series expansion and their parameters are determined based on the least-squares error criterion and the measure of statistical independency.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.159-159
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• 2019

In this study, the simulation of sediment deposition at Sangju weir reservoir, South Korea, was carried out using artificial neural networks. The ANNs have typically been used in water resources engineering problems for their robustness and high degree of accuracy. Three basic variables namely turbid water inflow, outflow, and water stage have been used as input variables. It was found that ANNs were able to establish valid relationship between input variables and target variable of sedimentation. The R value was 0.9806, 0.9091, and 0.8758 for training, validation, and testing phase respectively. Comparative analysis was also performed to find optimum structure of ANN for sediment deposition prediction. 3-14-1 network architecture using BR algorithm outperformed all other combinations. It was concluded that ANN possess mapping capabilities for complex, non-linear phenomenon of reservoir sedimentation.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.159-168
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• 2022

No one denies the importance of online courses, which provide a very important alternative, especially for students who have jobs that prevent them from attending face-to-face in traditional classes; Engagement is one of the most important fundamental variables that indicate the course's success in achieving its objectives. Therefore, the current study aims to build a model using machine learning to predict student engagement in online courses. An online questionnaire was prepared and applied to the students of Jouf University in the Kingdom of Saudi Arabia, and data was obtained from the input variables in the questionnaire, which are: specialization, gender, academic year, skills, emotional aspects, participation, performance, and engagement in the online course as a dependent variable. Multiple regression was used to analyze the data using SPSS. Kegel was used to build the model as a machine learning technique. The results indicated that there is a positive correlation between the four variables (skills, emotional aspects, participation, and performance) and engagement in online courses. The model accuracy was very high 99.99%, This shows the model's ability to predict engagement in the light of the input variables.

• The Korean Journal of Health Service Management
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• v.9 no.1
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• pp.17-29
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• 2015

This study, an examination of the plan for effective resource management for national university hospitals, was performed to determine the relationship between the effectiveness of patient output by considering input personnel using the DEA model and Management Performance, in which 4 years of data from 12 national university hospitals were analyzed. Among the components of the effectiveness, utilizing properly imput components from the application of VRS(Variable Returns to Scale), the Management Performance of national university hospitals was found to be affirmatively influenced by PTE(Pure Technical Efficiency). Regarding the Management Performance of national university hospitals in their attempts to establish a plan for effective human resource management, the management of patient numbers on the basis of calculation level with input is more recommendable than the controlling of personnel input using patient numbers. Thus, the establishment of a strategy plan for the proper allocation of administrative staff and sickbeds, considering the variation of patient numbers, is suggested.

• Earthquakes and Structures
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• v.8 no.5
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• pp.1241-1254
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• 2015

Spatially variable ground motions can be significant on the seismic response of a structure due to the incoherency of the incident wave. Incoherence of the incident wave is resulted from wave passage and wave scattering. In this study, wave passage effect on the response spectrum of a building structure built on a soft soil layer was investigated utilizing a finite element program of P3DASS (Pseudo 3-dimensional Dynamic Analysis of a Structure-soil System). P3DASS was developed for the axisymmetric problem in the cylindrical coordinate, but it is modified to apply anti-symmetric input earthquake motions. Study results were compared with the experimental results to verify the reliability of P3DASS program for the shear wave velocity of 250 m/s and the apparent shear wave velocities of 2000-3500 m/s. Studied transfer functions of input motions between surface mat foundation and free ground surface were well-agreed to the experimental ones with a small difference in all frequency ranges, showing some reductions of the transfer function in the high frequency range. Also wave passage effect on the elastic response spectrum reduced the elastic seismic response of a SDOF system somewhat in the short period range.

• Journal of Applied Reliability
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• v.15 no.2
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• pp.131-138
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• 2015

In modern warfare, the number of unmanned systems grow faster than any other weapon systems. Therefore, it is very important to predict and measure the combat effectiveness (CE) of unmanned weapon systems in battlefield for deciding defense budget to acquire those systems. In general, quantitative calculation of weapon effectiveness under complicated battlefield is difficult based on the future network centric warfare. Hence, many papers studied how to measure the combat effectiveness and tried to study a lot of related issues about it. However, there are few papers dealing with the relationship between the UGV (Unmanned Ground Vehicle)'s performance and CE in a ground battlefield. In this paper, we do the sensitivity analysis based on a given scenario in a small unit battle. In order to do that, we developed simulation model using AnyLogic and changed the input parameters such as detection and hitting probabilities. We also assess the simulation outputs according to the variation of input parameters. The MOE used in this simulation model output is survival ratio for Blue force. We hope that this paper will be useful to find which input variable is more effective to increase combat effectiveness in a small unit ground battlefield.