• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.9
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• pp.487-493
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• 2004

The electric power industry throughout the world is undergoing considerable changes from the vertically integrated utility structure to the deregulated market. However, the deregulated electricity market is operated with respect to theory of economical efficiency, and therefore, the system operator requires data with fast contingency ranking for security of the bulk power system. This paper compares the weather dependant probabilistic risk index(PRI) with the system performance index for power flow in the IEEE-RTS. The system performance index for power flow presents the power system stability. This paper presents fast calculation method for determining contingency ranking using the weather dependant probabilistic risk index(PRI). The probabilistic risk index can be classified into the case of normal and adverse weather. This paper proposes calculation method using the probabilistic risk index in determining contingency ranking required for security under the deregulated electricity market.

• Spatial Information Research
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• v.23 no.6
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• pp.31-41
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• 2015

This research is primarily intended to explore a novel way to monitor desiccation of inland wetland by combining MNDWI (Modified Normalized Difference Water Index) and NDVI (Normalized Difference Vegetation Index). The changes for vegetation and water condition on Upo Wetland located at southeastern Korea were investigated by MNDWI and NDVI derived from 2002, 2010 and 2015 Landsat data. The integrated use of MNDWI and NDVI made it possible to identify area-wide vegetation cover changes and to assess water storage changes on multi-annual time scales simultaneously. Comparing MNDWI with NDVI reveals the quantitative evidences for anthropogenic and environmental influences (such as road, building, water) causing an accelerated wetland desiccation. In fact, our monitoring approach raises critical issues regarding the hydrological cycle and its inter-annual changes for inland wetland under threat of drying up and highlights the important role of MNDWI and NDVI integration for any urgent or long-term treatment plan. This research presents scientific and objective evidences to support integrated approach of NDVI and MNDWI in exploring drying up trends of wetlands.

• Journal of Sensor Science and Technology
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• v.29 no.3
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• pp.172-179
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• 2020

We studied an integrated-optic biosensor configuration that operates at a wavelength of 0.63 ㎛ based on the evanescent-wave and two horizontal mode power coupling of Si₃N₄ rib-optical waveguides formed on a Si/SiO₂/Si₃N₄/SiO₂ multilayer thin films. The sensor consists of a single-mode input waveguide, followed by a two-mode section which acts as the sensing region, and a Y-branch output for separating the two output waveguides. The coupling between the two propagating modes in the sensing region produces a periodically repeated optical power exchanges along the propagation. A light power was steered from one output channel to the other due to the change in the cladding layer (bio-material) refractive index, which affected the effective refractive index (phase-shift) of two modes through evanescent-wave. Waveguide analyses based on the rib optical waveguide dimensions were performed using various numerical computational software. Sensitivity values of 12~23 and 65~165 au/RIU, respectively for the width and length of 4 ㎛, and 3841.46 and 26250 ㎛ of the two-mode region corresponding to the refractive index range 1.36~1.43 and 1.398~1.41, respectively, were obtained.

• Asia pacific journal of information systems
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• v.11 no.4
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• pp.99-111
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• 2001

The prediction of stock price index is a very difficult problem because of the complexity of stock market data. It has been studied by a number of researchers since they strongly affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network(BPN). Finally, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.5
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• pp.632-638
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• 2005

Membrane fouling index such as Silt Density Index (SDI) and Modified Fouling Index (MFI) is an important parameter in design of the integrated RO/NF membrane processes for drinking water treatment. In this study, the effect of particle, membrane and feed water characteristics on membrane fouling index were investigated systematically. Higher fouling index values were observed when filtering suspensions with smaller particle size and higher feed particle concentration. Larger membrane resistance due to smaller pore size resulted in an increased membrane fouling index. The variations of feed water hardness and TDS concentrations did not show any impact on fouling index, suggesting that there were no significant colloidal interactions among particles and thus the porosity of particle cake layer accumulated on the membrane surface could be assumed to be 0.36 according to random packing density. Based on the experimental observations, fundamental membrane fouling index model was developed using Happel Cell. The effect of primary model parameters including particle size ($a_p$), particle concentration ($C_o$), membrane resistance ($R_m$), were accurately assessed without any fitting parameters, and the prediction of membrane fouling index such as MFI exhibited very good agreement with the experimental results.

• Journal of Environmental Impact Assessment
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• v.16 no.6
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• pp.447-465
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• 2007

The purpose of this study is to assess the sustainability in 45 cities of all over Gyeongnam and Gyeongbuk using weights and assessment system developed in leading research. The materials of assessment used statistical data and spatial data were standardized for the systematic result. The assessment score was established using the normal distribution from 25 to 125 for removal of the very smallest and maximum value. According to the results, Tongyeong was assessed the highest by 82.5 score in environmental sustainability index. In economical sustainability index, Pohang, Gumi, Changwon, Yangsan were more than 79 score but Busan, Daegu, Andong were less than 70 score. Ulsan, Geoje, Yangsan were assessed higher in society-institutional sustainability index and Jinju, Munkyeong, Changnyeong were showed higher than other cities by more 79 score in quality of life(QOL)'s sustainability index. In case of integrated sustainability index, Jinju that was the highest sustainability in QOL was assessed by first city. However, Ulsan was assessed the lowest city among others. Therefore cities which have high sustainability will prepare a politic investment program for maintaining current conditions. Cities which have low sustainability will grasp closely the environmental characteristics of urban and present the improvement direction through monitoring continuously. Overall, these results can be used as tools to assess the current cities and predict the future one. It is also necessary to establish a systematic urban planning for livable and sustainable city.

• Korea Real Estate Review
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• v.27 no.3
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• pp.71-86
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• 2017

The purpose of this study was to apply the deep running method to real estate price index predicting and to compare it with the time series analysis method to test the possibility of its application to real estate market forecasting. Various real estate price indices were predicted using the DNN (deep neural networks) and LSTM (long short term memory networks) models, both of which draw on the deep learning method, and the ARIMA (autoregressive integrated moving average) model, which is based on the time seies analysis method. The results of the study showed the following. First, the predictive power of the deep learning method is superior to that of the time series analysis method. Second, among the deep learning models, the predictability of the DNN model is slightly superior to that of the LSTM model. Third, the deep learning method and the ARIMA model are the least reliable tools for predicting the housing sales prices index among the real estate price indices. Drawing on the deep learning method, it is hoped that this study will help enhance the accuracy in predicting the real estate market dynamics.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.95-104
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• 2013

This study developed three indices for evaluating regional brand value, i.e. awareness index, experience index, and attractiveness index. We used an AHP approach to estimate these indices for 151 rural regions (151 administrative jurisdictions in Korea). Our estimation results show that regional brand index varies considerably across regions by the individual characteristics of interviewee. First, the value of regional brand of local jurisdiction is higher than that of more integrated administrative jurisdiction. Second, the brand value of Gangwon and Jeolla region is higher than that of other regions. Third, the interviewees with school children in the age of 40-50 are likely to have higher regional brand value. The estimation results also show a need for different strategies to develop and improve regional brand.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.131-139
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• 2013

In recent years alternative navigation system such as a DBRN (Data-Base Referenced Navigation) system using geophysical information is getting attention in the military navigation systems in advanced countries. Specifically TRN (Terrain Referenced Navigation) algorithm research is important because TRN system is a practical DBRN application in South Korea at present time. This paper presents an integrated navigation algorithm that combines a linear profile-based TRN and INS (Inertial Navigation System). We propose a correlation analysis method between TRN performance and terrain roughness index. Then we propose a conditional position update scheme that utilizes the position output of the conventional linear profile type TRN depending on the terrain roughness index. Performance of the proposed algorithm is verified through Monte Carlo computer simulations using the actual terrain database. The results show that the TRN/INS integrated algorithm, even when the initial INS error is present, overcomes the shortcomings of linear profile-based TRN and improves navigation performance.

• Journal of Korean Society for Quality Management
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• v.44 no.4
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• pp.965-981
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• 2016

Purpose: This study aims to propose Kano-SERVQUAL integrated approach as an effective tool for evaluating auto service quality attributes to enhance the use of SERVQUAL. Methods: The Kano-SERVQUAL survey was conducted to evaluate customer perception for 28 auto service quality attributes which were obtained from auto service expert in 'H' company. The correlation analysis of SI(Satisfaction Index), DI(Dissatisfaction Index) and expectation values are conducted in this study. Results: The 28 auto service quality attributes are classified into attractive attributes and one-dimensional attributes. The results of this study show that the correlations between the customers' expectation values and DI is strongly positive correlation with 1% significance level, expectation values and SI is negative correlation with 10% significance level. Conclusion: The results show that the purposed Kano-SERVQUAL integrated approach provides a deeper understanding of service quality attributes in that it distinguishes the customers' expectation values between highly expected attributes(e.g. must-be attribute) and less expected attributes(e.g. attractive attribute).