• Journal of Korean Ophthalmic Optics Society
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• v.7 no.2
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• pp.169-174
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• 2002

Make Photochromic lens Photochromism estimation method, and gouge photochromic lens and investigated UV light source to apply. UV light source irradiation ago and after wavelength dependence of photo-transmittance (T%) of darkening and fading state by do optical equipment which is consisted of spectrophotometer, light source, power meter and detecter. Use relative ratio value of maximum $T%{\times}{\lambda}$ area and saturated state area in light off. Dependences estimation introduced darkening efficiency $(K_d)=(1-C_1/A_1)/t_{on}$ relationship value course fading efficiency$(K_f)=(C_2/A_2)/t_{on}$ value during Photochromism's irradiation time in Photochromic lens. Wavelength dependence of transmittance (T%) has form of $T_m+T_1{\exp}[-(x_0-t)/a]$ in Darkening course fading state. Can receive each estimation parameter value as result that apply Photochromism's estimation parameter Z, $K_d$, $K_f$ in Photochromic lens.

• Journal of Astronomy and Space Sciences
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• v.27 no.2
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• pp.123-128
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• 2010

This paper analyzes that the global positioning system (GPS) receiver differential code bias (DCB) has effect on the estimation the ionosphere total electron content (TEC). The data from nine permanent GPS sites of the Korea Astronomy and Space Science Institute (KASI) were used for the estimation of the receiver DCB before (Trimble 4000 SSi) and after (Trimble NetRS) the receiver replacement, using the singular value decomposition method. The results showed that the estimated mean value of the receiver DCB varied from 0.11 ns (nanosecond) to 7.54 ns before the receiver replacement, but the receiver DCBs shoed large values than 20 ns except some stations after the replacement. The receiver DCB showed a relatively large difference by types of the receivers, and, as a result, it had a great effect on the estimation the ionosphere TEC using GPS.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.506-509
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• 2006

Extended Kalman Filter iterate the prediction and the filtering based on Initial state for the next time step. EKF method for the estimation of nonlinear parameters of a structural dynamic system is necessary that initial of state vector and error covariance matrix. Because those are unknown exactly, generally selected random values. That occasion observability problem appear because of unknown initial values. In this study, for the estimation of the nonlinear parameters, a simple one degree of Freedom example is carried out by Extended Kalman Filter. And initial value assumption for Parameter Estimation of Dynamic System are developed. The result of analysis is compared with calculated standard values.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.439-446
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• 2011

Frequency is an important operating parameter for the protection, control, and stability of a power system. Thus, it must be maintained very close to its nominal frequency. Due to the sudden change in generation and loads or faults in a power system, however, frequency deviates from its nominal value. An accurate monitoring of the power frequency is essential for optimum operation and prevention of wide area blackout. Most conventional frequency estimation schemes are based on the DFT filter. In these schemes, the gain error could cause defects when the frequency deviates from the nominal value. We present an advanced frequency estimation technique using gain compensation to enhance the DFT filter-based technique. The proposed technique can reduce the gain error caused when the frequency deviates from the nominal value. Simulation studies are performed using both the data from EMTP-RV software and the user-defined arbitrary signals to demonstrate the effectiveness of the proposed algorithm. Results show that the proposed algorithm achieves good performance under both steady state tests and dynamic conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1529-1547
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• 2015

Establishment of trust is important in wireless sensor networks for security enhancement and successful collaboration. Basically, a node establishes trust with other nodes by estimating a trust value based on monitored behavior of the other nodes. Since a malicious/misbehaving node might launch different attack strategies and might demonstrate random misbehavior, a trust estimation method should be robust against such attacks and misbehavior. Otherwise, the operation of trust establishment will be meaningless, and performance of an application that runs on top of trust establishment will degrade. In this paper, we propose a robust and novel trust estimation method. Unlike traditional trust estimation methods, we consider not only the weight of misbehavior but also the frequency of misbehavior. The frequency-of-misbehavior component explicitly demonstrates how frequently a node misbehaves during a certain observed time period, and it tracks the behavior of nodes more efficiently, which is a main factor in deriving an accurate trust value. In addition, the weight of misbehavior is comprehensively measured to mitigate the effect of an on-off attack. Frequency and weight of misbehavior are comprehensively combined to obtain the trust value. Evaluation results show that the proposed method outperforms other trust estimation methods under different attacks and types of misbehavior.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.2
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• pp.35-48
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• 2017

As the technology convergence paradigm emerges, the need for "CIA techniques" to analyze the mutual effects of technology is increasing. However, since the CIA input parameter estimation is difficult, the present study suggests a "CIA input parameter setting model" to alleviate the difficulty of CIA input parameter estimation. This paper is focused on the difference of measurement difficulty by each scale which expert's estimation behavior was defined as measurement activity quantifying the judgment of future technology. Therefore, this model is designed to estimate the input variable as a sequence or isometric scale that is relatively easy to measure, and then converts it into a probability value. The input parameter setting model of the CIA technique consists of three sub-models : 'probability value derivation model', 'influence estimation model', and 'impact value calculation model', in order to develop a series of models the Thurstone V model, Regression Analysis, etc has been used.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.3
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• pp.253-257
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• 2010

The frequency is an important operation parameter for the control, protection, and stability of a power system. The frequency as a key index of power quality can be indicative of system abnormal conditions and disturbances. Due to the sudden change in generation and loads or faults in power system, the frequency is supposed to deviate from its nominal value. It is essential that the frequency must be maintained very close to its nominal frequency. An accurate monitoring of the power frequency is essential to optimal operation and prevention for wide area blackout. As most conventional frequency estimation schemes are based on DFT filter, it has been pointed out that the gain error could cause defects when the frequency is deviated from nominal value. This paper presents an advanced frequency estimation technique using gain compensation to improve the performance of DFT filter based techniques. To evaluate performance of the proposed algorithm, the 765kV T/L system in Korea is simulated by EMTP-RV software. The proposed technique can reduce the gain error caused when the power system frequency deviates from nominal value.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.553-558
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• 2003

The boundary estimation problem is used to estimate the shape of organic depend on the phase of the cardiac cycle or interested in the detection of the location and size of anomalies with resistivity values different from the background tissues such as nuclear reactor. And we can use the method to solve the optimal solution such as modified Newton raphson, kalman filter, extended kalman filter, etc. But, this method consumes much time and is sensitive to the initial value and noise in the estimation of the unknown shape. In the paper, we propose that multi-layer neural networks estimate the boundary of the unknown object using Fourier coefficient. This method can be used at the real time estimation and have strong characteristics at the noise and initial value. It uses voltage change; difference the homogeneous voltage to the non-homogeneous voltage, and change of Fourier coefficient change to train multi-layer neural network. After train, we can have real time estimation using this method.

• KIEAE Journal
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• v.16 no.3
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• pp.129-135
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• 2016

Purpose: Building figuration is imperative to perceive the its value, environmental clean status and form. Therefore, maintenance activities of the building exterior are required to keep the housing condition and value. Each household should pay the repair cost which is brought out in the future. For this repair cost, the estimation model would needed to forecast and provide the required cost. This study aimed at providing the estimation model of the repair cost, using the repair survey data between the 2011 and 2014 in Seoul. Method: For these, it took various estimation function of repair cost such as 1st function, inverse function and so on. These above functions would be applied into the building exterior and outdoor facilities which figure the building shape and characteristics. Result: Results of this study are shown ; First, among 11 estimation models, the power function has a better statistics and goodness-of-fit than any other models. Second, the estimation model with a variable of household has a pattern in upward to the right. On the contrary, the model with management area is little downward to the right. Both of them are depended on the estimated parameter of the power function and the parameter smaller than 1.

• Journal of Families and Better Life
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• v.7 no.1
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• pp.43-57
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• 1989

In the materialistic societies, individuals get money return according to the importance of their roles. But unlike wage workers who are engaged in market production , housewives engaged in home production do not get that return. It is because the result of home production is not transacted in the market and the price is not given to it, so the value of home production is not estimated. Hence this study trcognizes again the value of home production, suggests the estimation methods of it in input and output based on home production systems and attempts to actualize those methods socially. This home production develops the human attributes of family members to act as a member of a society and potentially contributes to home income and Gross National Products, so it has social and economic value. In spite of that significance, the value of home production is not estimated, so its nor recognized and housewives engaged in home production are not acknowledged their ability. Hence based on home production systems form input to output, this study suggested opportunity cost method and market cost method in input, method by saving money expenditure, hybrid method and method by comparing with market in output.