• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.782-789
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• 2010

Landslides cause enormous economic losses and casualties. Korea has mountainous regions and heavy slopes in most parts of the land and has consistently built new roads and large-scale housing complexes according to its industrial and urban growth. As a result, the damage from landslides becomes greater every year. In this study, performed a GIS-based landslide hazard analysis by SINMAP(Stability Index MAPping) model in Gyeonggi Icheon area coupling with geomorphological and geological data. SINMAP model has its theoretical basis in the infinite plane slope stability model with wetness obtained from a topographically based steady state model of hydrology. To Gyeonggi Icheon area landslides hazards evaluated, these SINMAP model were analysed results while simultaneously referring to the stability index map, where lines distinguish the zones categorized into the different stability classes and a table giving summary statistics.

• The KSFM Journal of Fluid Machinery
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• v.16 no.2
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• pp.42-47
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• 2013

Ship stability prediction is very complex in reality. In this paper, risk based approach is applied to predict the probability of a certified ship, which is effected by the forces of sea especially the wave loading. Safety assessment and risk analysis process are also applied for the probabilistic prediction of ship stability. The survival probability of ships encountering with different waves at sea is calculated by the existed statistics data and risk based models. Finally, ship capsizing probability is calculated according to single degree of freedom(SDF) rolling differential equation and basin erosion theory of nonlinear dynamics. Calculation results show that the survival probabilities of ship excited by the forces of the seas, especially in the beam seas status, can be predicted by the risk based method.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.31-45
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• 1995

In recent year, especially in the mode choice analysis, it has been perceived that the importance of individual performance data using stated preference(SP) experiments as well as revealed preference data . Since SP experiments present respondent with various hypothetical alternatives, which are produced by a combination of a number of different attribute levels, and ask them to indicate a preference, it is possible to analyze travel behavior under a situation of potential environment change such as proposed alternative mode of transportation. The basic problems, however, remains that SP are not consistent with the actual travel behaviors and the research reports for stability of mode choice model using SP data has not been sufficient. Under this background, this study is to examine the characteristics of mode choice model using the SP data by the following items. $\circled1$ Analysis of factors affecting the mode choice behavior by the variance analysis of orthogonal-arrays-table $\circled2$ The reliability of SP data by transfer intention data $\circled3$ The stability of SP responses obtained from repetitive question by the comparison of model coefficient specified by each repetitive data. $\circled4$ The stability of ranking data in mode choice model For the analysis, we assumed subway operations in the Gwang-Ju , and set up a choice-set of hypothetical options based on Experimental Design Method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.10
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• pp.41-49
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• 2013

There is a wide variety of system and applications in the power system. However, they have compatibility issues because they use different data standard and communication method. With the introduction of the smart grid, power system has been grow and diversified. Therefore power system need to be compatible with each other and the interoperability between applications is increasingly important. Thus, the IEC established IEC61970 and CIM Standard data exchange model for interoperability and system integration. Server-Client system was constructed which using CIM HSDA(Part4), a standard communication model, presented in IEC 619710. Also, self-developed real-time voltage stability analysis application and contingency analysis application was used. CIM HSDA was used for data input and real-time analysis. Tolerance of result which is in the range of allowable derived by Perform real-time voltage stability and contingency analysis of Jeju power system, and then compare it's result with PSS/E result.

• Geomechanics and Engineering
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• v.9 no.1
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• pp.83-100
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• 2015

Water and energy supplies are the key factors affecting the economic development and environmental improvement of Turkey. Given their important role and the fact that a large part of Turkey is in seismically active zones dams should be accurately analyzed since failure could have a serious impact on the local population environment and on a wider level could affect the economy. In this paper, a procedure is proposed for the static, slope stability, seepage and dynamic analysis of an earth dam and the Pamukcay embankment dam. The acceleration time history and maximum horizontal peak ground accelerations of the $Bing\ddot{o}l$ (2003) earthquake data was used based on Maximum Design Earthquake (MDE) data. Numerical analysis showed that, the Pamukcay dam is likely to experience moderate deformations during the design earthquake but will remain stable after the earthquake is applied. The result also indicated that, non-linear analysis capable of capturing dominant non-linear mechanism can be used to assess the stability of embankment dams.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.39-51
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• 2012

Cluster analysis has proven to be a useful tool for investigating the association structure among genes and samples in a microarray data set. We applied several cluster validation measures to evaluate the performance of clustering algorithms for analyzing microarray gene expression data, including hierarchical clustering, K-means, PAM, SOM and model-based clustering. The available validation measures fall into the three general categories of internal, stability and biological. The performance of clustering algorithms is evaluated using simulated and SRBCT microarray data. Our results from simulated data show that nearly every methods have good results with same result as the number of classes in the original data. For the SRBCT data the best choice for the number of clusters is less clear than the simulated data. It appeared that PAM, SOM, model-based method showed similar results to simulated data under Silhouette with of internal measure as well as PAM and model-based method under biological measure, while model-based clustering has the best value of stability measure.

• KDI Journal of Economic Policy
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• v.38 no.3
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• pp.53-77
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• 2016

Financial soundness in the household sector matters for financial stability and for the real economy. The level of household debt in Korea raises concern about the financial soundness of the household sector due to its size, growth rate and quality. Against this backdrop, we assess the financial vulnerability of borrowers based on an analysis of credit bureau (CB) data, in which the actual credit activities of most individuals are recorded at a high frequency in Korea. We construct over-indebtedness indicators from the CB data and then assess the predictability of forthcoming defaults. Based on the over-indebtedness indicators, we show how borrowers are distributed in terms of over-indebtedness and how the over-indebted differ from average borrowers in terms of their characteristics. Furthermore, we show how the aggregate credit risk in the household sector would change under macroeconomic distress by analyzing how each borrower's credit quality would be affected by adverse shocks. The findings of this paper may contribute to assessing household debt vulnerability and to enhancing regulatory and supervisory practices for financial stability.

• Journal of Astronomy and Space Sciences
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• v.19 no.4
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• pp.367-376
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• 2002

As of September 2002, there are more than 60 operational permanent Global Positioning System (GPS) stations in South Korea. Their data are being used for a variety of purposes: geodynamics, geodesy, real-time navigation, atmospheric science, and geography. Especially, many of the sites are reference stations for DGPS (Differential GPS). However, there has been no comprehensive and qualitative analysis published to evaluate the data quality. In this study, we present preliminary results of our assessment of the permanent GPS sites in South Korea. We have analyzed the multi-path characteristics of each station using a quality-checking software package called TEQC. Another multipath analysis tool based on post-fit phase residuals was used to check the repeating patterns and the amount of the multipath at each site. The long-term stability of each station was analyzed using the root-mean-square (RMS) error of the estimated site positions for one year, which enabled us to evaluate the mount stability. In addition, the number of cycle slips at each site was derived by TEQC. Based on these series of tests, we compared the stability and data quality of permanent GPS stations in South Korea.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1783-1784
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• 2008

This paper presents a novel control technique to deal with networked control systems with neutral timedelay, which is known to highly degrade the control performance of the controlled system. The stability analysis and design method for a sampled-data fuzzy controller for discrete networked control systems (NCS). The neutral time-delay and sampling activity will complicate the NCS. And it make the stability analysis much more difficult than that for a continuous-time NCS. Based on the fuzzy control approach, linear matrix inequality (LMI)-based stability conditions are derived to guarantee the neutral T-S fuzzy system stability. The simulation results and practical experiments illustrate that the proposed controller design is realistic.

• Geomechanics and Engineering
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• v.13 no.2
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• pp.237-254
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• 2017

Estimation of slope stability is a very important task in geotechnical engineering. However, its estimation using conventional and soft computing methods has several drawbacks. Use of conventional limit equilibrium methods for the evaluation of slope stability is very tedious and time consuming, while the use of soft computing approaches like Artificial Neural Networks and Fuzzy Logic are black box approaches. Multiple Regression (MR) analysis provides an alternative to conventional and soft computing methods, for the evaluation of slope stability. MR models provide a simplified equation, which can be used to calculate critical factor of safety of slopes without adopting any iterative procedure, thereby reducing the time and complexity involved in the evaluation of slope stability. In the present study, a multiple regression model has been developed and tested its accuracy in the estimation of slope stability using real field data. Here, two separate multiple regression models have been developed for dry and wet slopes. Further, the accuracy of these developed models have been compared and validated with respect to conventional limit equilibrium methods in terms of Mean Square Error (MSE) & Coefficient of determination ($R^2$). As the developed MR models here are not based on any region specific data and covers wide range of parametric variations, they can be directly applied to any real slopes.