• Proceedings of the Korea Concrete Institute Conference
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• 2001.11a
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• pp.859-864
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• 2001

An effective live load model for analyzing probable maximum live load effects such as moment and shear in transverse direction was developed. The main procedure of this live load model is composed of four parts, i.e., firstly, determination of the appropriate influence lines in longitudinal direction, secondly, application of the characteristics of vehicles and traffic patterns in longitudinal direction, thirdly, determination of the appropriate influence lines in transverse direction, and fourthly, application of the characteristics of vehicles and traffic patterns in transverse direction. Through this procedure, the probabilistic distributions of maximum probable load effects are deduced in the form of probability density function (PDF) and/or cumulative density function(CDF). This live load model is able to consider local or global deterioration of bridges in the structural analysis.

• Proceedings of the Korea Concrete Institute Conference
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• 2001.11a
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• pp.865-870
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• 2001

An effective live load model for analyzing probable maximum live load effects in longitudinal direction such as moment and shear was developed. The main procedure of this live load model is composed of two parts. Firstly, determination of the appropriate influence lines, and secondly, application of the characteristics of vehicles and traffic patterns. Through this procedure, probabilistic distributions of maximum probable load effects are deduced in the form of probability density function (PDF) or cumulative density function (CDF). The proposed live load model is not limited by bridge types(number of spans or girders) and can consider local or global deterioration of bridges in the analysis. Besides, load effects can be determined at any section without restrictions.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1276-1282
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• 2013

This paper proposes a stochastic modeling of plug-in electric vehicles (PEVs) distribution in power systems, and analyzes the corresponding clustering characteristic. It is essential for power utilities to estimate the PEV charging demand as the penetration level of PEV is expected to increase rapidly in the near future. Although the distribution of PEVs in power systems is the primary factor for estimating the PEV charging demand, the data currently available are statistics related to fuel-driven vehicles and to existing electric demands in power systems. In this paper, we calculate the number of households using electricity at individual ending buses of a power system based on the electric demands. Then, we estimate the number of PEVs per household using the probability density function of PEVs derived from the given statistics about fuel-driven vehicles. Finally, we present the clustering characteristic of the PEV distribution via case studies employing the test systems.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.10 no.1
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• pp.51-55
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• 2014

Based on the results of Probabilistic Safety Assessment(PSA) for a Nuclear Power Plant (NPP), Common Cause Failure(CCF) events have been recognized as one of the main contributors to the risk. Also, the CCF data and estimation method used in domestic PSA models have been pointed out as an issue with respect to the quality. The existing method of MGL and non-staggered testing even widely used were considered conservative in estimating the safety and had a limited capability in uncertainty analyses. Therefore, this paper presents the CCF estimation using a new generic data source and Alpha factor method. The analyses showed that Alpha factor and staggered method are effective in estimating the CCF contribution and risk insights of reference plant. This method will be a common bases for the optimization of new design for the construction plants as well as for the updating of safety assessment on the operating nuclear power plants.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.663-667
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• 2009

본 논문에서는 인접블록간의 움직임 유사도를 이용하여 불필요한 후보블록을 보다 빠르게 제거하는 PDE기반의 고속 블록매칭 알고리즘을 제안한다. 제안한 방법은 기존의 방법보다 불필요한 계수를 효율적으로 제거하기 위하여 인접 블록간의 영상의 유사성에 기초하여 인접한 네개의 매크로블록 가운데 최대 복잡도를 가지는 서브블록의 누적된 비율(cumulative distribution function-CDF)을 사용하고 서브블록별 복잡도가 집중되지 않도록 하기위하여 normalized 기반 매칭스캔 방법을 사용하여 효율적으로 계산량을 줄였다. 제안한 알고리즘은 화질의 저하 없이 기존의 PDE 알고리즘에 비해 60% 이상의 계산량을 줄였으며, MPEG-2 및 MPEG-4 AVC를 이용하는 비디오 압축 응용분야에 유용하게 사용될 수 있을 것이다.

• KIEE International Transactions on Power Engineering
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• v.5A no.4
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• pp.371-377
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• 2005

Congestion problems of transmission lines are very important research issues in power system operations. Load curtailment is one of the ways to solve congestion problems by a major contingency. A systematic and effective mechanism for load shedding has been developed by investigating congestion distribution factors and the direct load control program. In this paper, a load shedding algorithm using linear programming for congestion problems by a major contingency is presented. In order to show the effectiveness of the proposed algorithm, it has been tested on the 6-bus sample system and the power system of Korea, and their results are presented.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.761-764
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• 2000

This paper presents a Fuzzy Neural Network (FNN) system to decide whether or not the right information of lanes can be extracted from gray-level images of road scene. The decision of noisy level of input images has been required because much noises usually deteriorates the performance of feature detection based on image processing and lead to erroneous results. As input parameters to FNN, eight noisiness indexes are constructed from a cumulative distribution function (CDF) and proved the indexes being classifiers of images as the good and the bad corrupted by sources of noise by correlation analysis between input images and the indexes. Considering real-time processing and discrimination efficiency, the proposed FNN is structured by eight input parameters, three fuzzy variables and single output. We conduct much experiments and show that our system has comparable performance in terms of false-positive rates.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.427-432
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• 2005

This paper is concerned with a simultaneous design of TSK (Takagi-Sugeno-Kang)-linguistic fuzzy models with uncertain model output and the computationally efficient representation. For this purpose, we use the fundamental idea of linguistic models introduced by Pedrycz and develop their comprehensive design framework. The design process consists of several main phases such as (a) the automatic generation of the linguistic contexts by probabilistic distribution using CDF (conditional density function) and PDF (probability density function) (b) performing context-based fuzzy clustering preserving homogeneity based on the concept of fuzzy granulation (c) augment of bias term to compensate bias error (d) combination of TSK and linguistic context in the consequent part. Finally, we contrast the performance of the enhanced models with other fuzzy models for automobile MPG predication data and coagulant dosing process in a water purification plant.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.973-974
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• 2008

As radar signal environments become denser and more complex, the capability of high-speed and accurate signal analysis is required for ES(Electronic warfare Support) system to identify individual radar signals at real-time. In this paper, we propose the new novel clustering algorithm of radar pulses to alleviate the load of signal analysis process and support reliable analysis. The proposed algorithm uses KDE(Kernel Density Estimation) and its CDF(Cumulative Distribution Function) to compose clusters considering the distribution characteristics of pulses. Simulation results show the good performance of the proposed clustering algorithm in clustering and classifying the emitters.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.09a
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• pp.51-60
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• 2002

In this study we developed the visualization scheme of spatial ground-motion measurements in real time by using DSS data. Even though this scheme itself is useful for national earthquake mitigation plans, this scheme could be served as the crucial core for constructing rapid earthquake damage evaluation system. DSS is the abbreviation of Data Subscription Service and this is the pre-assigned request for the seismic stations to send very limited brief data with high priority and negligible transmission load. In addition to visualize the damage area with intensity, the corresponding epicenter can be estimated roughly for quick event alarm. For the interpolation of spatially irregular PGA data, the program, named as surface. of GMT was used with NetCDF grid file format. Since the grid file is similar to a postscript file, the program, called as shading, was coded with C language by using Matpak library in order to convert grid files into image files.