• Journal of the Ergonomics Society of Korea
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• v.26 no.4
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• pp.121-125
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• 2007

The objective of this study is to develop short-term prevention measures for minimizing possible human error in nuclear power facilities. To accomplish this objective, a group of subject matter experts (SMEs) were formed, which is consisting of those from regulatory bodies, academia, industries and research institutes. Prevention measures were established for urgent execution in nuclear power facilities on a short-term basis. This study suggests short-term measures for reducing human error on three different areas; (1) strengthening worker management, (2) enhancing workplace environments and working methods, and (3) improving the technologies regulating human factors. Under the leadership of the Ministry of Science and Technology, these short-term measures will be pursued and implemented systematically by utility and regulatory agencies. The details of prevention measures are presented and discussed.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.120-131
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• 2020

In order to solve the problem of point clouds coordinate conversion of non-directional scanners, this paper proposes a basic Rodrigues rotation method. Specifically, we convert the 6 degree-of-freedom (6-DOF) rotation and translation matrix into the uniaxial rotation matrix, and establish the equation of objective vector conversion based on the basic Rodrigues rotation scheme. We demonstrate the applicability of the new method by using a bar-shaped emboss point clouds as experimental input, the three-axis error and three-term error as validate indicators. The results suggest that the new method does not need linearization and is suitable for optional rotation angle. Meanwhile, the new method achieves the seamless splicing of point clouds. Furthermore, the coordinate conversion scheme proposed in this paper performs superiority by comparing with the iterative closest point (ICP) conversion method. Therefore, the basic Rodrigues rotation method is not only regarded as a suitable tool to achieve the conversion of point clouds, but also provides certain reference and guidance for similar projects.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.249-255
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• 2014

We present a simple method to watermark three-dimensional (3D) triangular meshes that have been generated from the depth data of the Kinect sensor. In contrast to previous methods, which maintain the shape of 3D triangular meshes and decide the embedding place, requiring calculations of vertices and their neighbors, our method is based on selecting one of the coordinate axes. To maintain shape, we use discrete wavelet transform and constant regularization. We know that the watermarking system needs the information to be embedded; we used a text to provide that information. We used geometry attacks such as rotation, scales, and translation, to test the performance of this watermarking system. Performance parameters in this paper include the vertices error rate (VER) and bit error rate (BER). The results from the VER and BER indicate that using a correction term before the extraction process makes our system robust to geometry attacks.

• Journal of the Korean Solar Energy Society
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• v.39 no.5
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• pp.41-52
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• 2019

The purpose of the work is to develop a simple solar irradiance prediction model using a deep learning method, the LSTM (long term short term memory). Other than existing prediction models, the proposed one uses only the cloudiness among the information forecasted from the national meterological forecast center. The future cloudiness is generally announced with four categories and for three-hour intervals. In this work, a daily irradiance pattern is used as an input vector to the LSTM together with that cloudiness information. The proposed model showed an error of 5% for learning and 30% for prediction. This level of error has lower influence on the load prediction in typical building cases.

• Journal of Power Electronics
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• v.14 no.4
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• pp.704-711
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• 2014

This paper proposes a combined fuzzy adaptive sliding-mode voltage controller (FASVC) for a three-phase UPS inverter. The proposed FASVC encapsulates two control terms: a fuzzy adaptive compensation control term, which solves the problem of parameter uncertainties, and a sliding-mode feedback control term, which stabilizes the error dynamics of the system. To extract precise load current information, the proposed method uses a conventional load current observer instead of current sensors. In addition, the stability of the proposed control scheme is fully guaranteed by using the Lyapunov stability theory. It is shown that the proposed FASVC can attain excellent voltage regulation features such as a fast dynamic response, low total harmonic distortion (THD), and a small steady-state error under sudden load disturbances, nonlinear loads, and unbalanced loads in the existence of the parameter uncertainties. Finally, experimental results are obtained from a prototype 1 kVA three-phase UPS inverter system via a TMS320F28335 DSP. A comparison of these results with those obtained from a conventional sliding-mode controller (SMC) confirms the superior transient and steady-state performances of the proposed control technique.

• Journal of Korean Institute of Industrial Engineers
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• v.7 no.1
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• pp.21-31
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• 1981

This paper develops a short term forecasting model for household electric power consumption in Seoul, which can be used for the effective planning and control of utility management. The model developed is based on exponentially weighted moving average model and incorporates monthly average temperature as an exogeneous factor so as to enhance its forecasting accuracy. The model is empirically compared with the Winters' three parameter model which is widely used in practice and the Box-Jenkins model known to be one of the most accurate short term forecasting techniques. The result indicates that the developed hybrid exponential model is better in terms of accuracy measured by average forecast error, mean squared error, and autocorrelated error.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.647-654
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• 2021

This study examines the non-performing loans of rural banks and macroeconomic factors in Indonesia, including inflation, exchange rates, and interest rates. Theoretically, the existence of erratic macroeconomic conditions can affect the level of non-performing credit risk in rural credit banks in Indonesia. The effect of macroeconomic conditions on non-performing loans has a different response for each economic sector. The main objective of this study is to determine the effect of macroeconomic factors (inflation, exchange rates, and interest rates) and bank-specific factors (credit) on the Non-Performing Loans (NPL) of Rural Banks in Indonesia for the period from January 2015 to December 2018. This study uses a Vector Error Correction Model (VECM) estimation to determine the effect of independent variables consisting of macroeconomic factors and bank-specific factors. Based on the estimation results of the Vector Error Correction Model, three variables that have a positive and significant effect on long-term non-performing loans are credit, inflation, and interest rates. Meanwhile, in the short term, there are only two variables that have a positive and significant effect on non-performing loans, namely, credit and interest rates. Inflation and exchange rate variables have a negative and insignificant effect on bad credit in the short term.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.213-222
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• 2023

This paper mainly studies the relationship between financial development, inbound tourism development, and economic growth rate in Fujian Province, China. This study uses the data of real GDP, foreign exchange income from international tourism, and financial interrelations ratio from 1994 to 2019. In the analysis process, the Johansen cointegration test is first used to analyze whether the three have a long-term equilibrium relationship. Then the vector error correction model is established to test the restrictive relationship among the three. Next, the Granger causality test assesses whether the three have a causal relationship. Finally, the contribution rate of the three is analyzed by variance decomposition. The above methods show the following conclusions: first, the three have a long-term equilibrium relationship. Secondly, in the short term, local economic growth is constrained by inbound tourism and financial development. Thirdly, there is a causal relationship between economic growth and inbound tourism in Fujian, while there is a unidirectional causal relationship between financial development and economic growth, financial development, and inbound tourism. Fourthly, the contribution rate of inbound tourism to economic growth fluctuations in Fujian is higher than that of financial development.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.4
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• pp.482-488
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• 2013

Load forecasting is essential to the economical and the stable power system operations. In general, the forecasting days can be classified into weekdays, weekends, special days and special light-load periods in short-term load forecast. Special light-load periods are the consecutive holidays such as Lunar New Years holidays, Korean Thanksgiving holidays and summer special light-load period. For the weekdays and the weekends forecast, the conventional methods based on the statistics are mainly used and show excellent results for the most part. The forecast algorithms for special days yield good results also but its forecast error is relatively high than the results of the weekdays and the weekends forecast methods. For summer special light-load period, none of the previous studies have been performed ever before so if the conventional methods are applied to this period, forecasting errors of the conventional methods are considerably high. Therefore, short-term load forecast for summer special light-load period have mainly relied on the experience of power system operation experts. In this study, the trends of load profiles during summer special light-load period are classified into three patterns and new forecast algorithms for each pattern are suggested. The proposed method was tested with the last ten years' summer special light-load periods. The simulation results show the excellent average forecast error near 2%.

• Journal of applied mathematics & informatics
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• v.6 no.1
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• pp.31-50
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• 1999

We revisit the problems of testing three-factor classifica-tion models with a single observation per cell. A common approach in analyzing such nonreplicated data is to omit the highest order in-teraction and regard it as error. This paper discusses the use of a multiplicative model(See and Smith 1996 and 1998) which is applied on residuals in order to separate the variablility due to three-factor interaction from what is counted as random error. in particualr to test the significance of the interaction term we derived an approxi-mated distribution of the likelihood ratio test statistic based on the quadrilinear model known as Tucher's three-mode principal compo-nent model. The derivation utilizes the distribution of the eignevalues of the Wishart matrix.