• Korean Journal of Culture and Social Issue
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• v.9 no.spc
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• pp.123-147
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• 2003

This paper provides a comparative analysis of the probabilistic versus deterministic view of accident and safety using the indigenous and cultural perspectives. Death and injury due to accidents is the leading cause of preventable death in most countries, including Korea. The first part of this paper delineates the limitation of the linear, deterministic model that has been adopted in social and applied sciences. The transactional model, advocated by indigenous psychology, is provided to understand the probabilistic nature of accident and safety at home, in the workplace and in society. Second, factors related to accidents and safety are reviewed. Third, application of the probabilistic model for preventing accidents and promoting safety in Korea is outlined.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.703-704
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• 2013

• Structural Engineering and Mechanics
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• v.11 no.4
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• pp.373-392
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• 2001

The main idea behind the paper is to present two alternative methods of homogenization of the heat conduction problem in composite materials, where the heat conductivity coefficients are assumed to be random variables. These two methods are the Monte-Carlo simulation (MCS) technique and the second order perturbation second probabilistic moment method, with its computational implementation known as the Stochastic Finite Element Method (SFEM). From the mathematical point of view, the deterministic homogenization method, being extended to probabilistic spaces, is based on the effective modules approach. Numerical results obtained in the paper allow to compare MCS against the SFEM and, on the other hand, to verify the sensitivity of effective heat conductivity probabilistic moments to the reinforcement ratio. These computational studies are provided in the range of up to fourth order probabilistic moments of effective conductivity coefficient and compared with probabilistic characteristics of the Voigt-Reuss bounds.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.700-707
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• 2009

The application of renewable energy in electric power systems is growing rapidly in order to make provision for the inequality of the climate, the dwindling supplies of coal, oil and natural gas and a further rise in oil prices. Solar cell generators(SCG) is one of the fastest growing renewable energy. This paper presents a methodology on probabilistic production cost simulation of a power system including SCGs. The generated power by SCGs is variable due to the random variation of solar radiation. In order to solve this problem, the SCGs is modeled as multi-state operational model in this paper. Probabilistic production cost of a power system can be calculated by proposed method considering SCGs with multi-state. The results show that the impacts of SCGs added to a power system can be analyzed in view point of production cost using the proposed method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.49-56
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• 1999

In this paper, the general formula of disparity estimation based on Bayesian Maximum A Posteriori (MAP) algorithm is derived. The generalized formula is implemented with the plane configuration model and applied to multiple baselined stereograms. The probabilistic plane configuration model consists of independence and similarity among the neighboring disparities in the configuration. The independence probabilistic model reduces the computation and guarantees the discontinuity at the object boundary region. The similarity model preserves the continuity or the high correlation of disparity distribution. In addition, we propose a hierarchical scheme of disparity compensation in the application to multiple-view stereo images. According to the experiments, the derived formula and the proposed estimation algorithm outperformed other ones. The proposed probabilistic models are reasonable and approximate the pure joint probability distribution very well with decreasing the computations to O(n(D)) from O(n(D)4) of the generalized formula. And, the hierarchical scheme of disparity compensation with multiple-view stereos improves the performance without any additional overhead to the decoder.

• Journal of Industrial Technology
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• v.22 no.B
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• pp.231-240
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• 2002

The rational method of estimating peak flow is used largely for the simplicity. But the accuracy of rational method is not easy to estimate, because the rational method is analyzed by the deterministic point or view and the runoff coefficients of the rational method are proposed from other countries. In this study the rational method is analyzed by the probabilistic way to be a more reliable method. The runoff coefficient is regarded to parameter that changes the probabilistic rainfall to the peak flow. The runoff coeffient for each return period is analyzed to be a reliable index which is used to estimate the peak flow of ungauged natural catchments.

• Structural Engineering and Mechanics
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• v.21 no.5
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• pp.507-518
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• 2005

In the shear-lag analysis of structures deterministic procedure is insufficient to provide complete information. Probabilistic analysis is a holistic approach for analyzing shear-lag effects considering uncertainties in structural parameters. This paper proposes an efficient and accurate algorithm to analyze shear-lag effects of structures with parameter uncertainties. The proposed algorithm integrated the advantages of the response surface method (RSM), finite element method (FEM) and Monte Carlo simulation (MCS). Uncertainties in the structural parameters can be taken into account in this algorithm. The algorithm is verified using independently generated finite element data. The proposed algorithm is then used to analyze the shear-lag effects of a simply supported beam with parameter uncertainties. The results show that the proposed algorithm based on the central composite design is the most promising one in view of its accuracy and efficiency. Finally, a parametric study was conducted to investigate the effect of each of the random variables on the statistical moment of structural stress response.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2153-2160
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• 2008

This paper develops an algorithm for probabilistic production cost credit evaluation of wind turbine generators(WTG) with multi-state. Renewable energy resources such as wind, wave, solar, micro hydro, tidal and biomass etc. are becoming importance stage by stage because of considering effect of the environment. Wind energy is one of the most successful sources of renewable energy for the production of electrical energy. Case study demonstrates that the wind speed credit in view point of economics can be assessed by using the proposed methodology.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.275-278
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• 2006

This paper describes a probabilistic annual congestion cost assessment of a grid at a composite power system derived from a model. This probabilistic congestion cost assessment simulation model includes capacity limitation and uncertainties of the generators and transmission lines. In this paper, the proposed probabilistic congestion cost assessment model is focused on an annualized simulation methodology for solving long-term grid expansion planning issues. It emphasizes the questions of "how should the uncertainties of system elements (generators, lines and transformers, etc.) be considered for annual congestion cost assessment from the macro economic view point"? This simulation methodology comes essentially from a probabilistic production cost simulation model of composite power systems. This type of model comes from a nodal equivalent load duration curve based on a new effective load model at load points. The characteristics and effectiveness of this new simulation model are illustrated by several case studies of a test system.

• Journal of KIISE
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• v.41 no.11
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• pp.927-934
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• 2014

In this paper, we propose an effective method for recognizing daily human activities from a stream of three dimensional body poses, which can be obtained by using Kinect-like RGB-D sensors. The body pose data provided by Kinect SDK or OpenNI may suffer from both the view variance problem and the scale variance problem, since they are represented in the 3D Cartesian coordinate system, the origin of which is located on the center of Kinect. In order to resolve the problem and get the view-invariant and scale-invariant features, we transform the pose data into the spherical coordinate system of which the origin is placed on the center of the subject's hip, and then perform on them the scale normalization using the length of the subject's arm. In order to represent effectively complex internal structures of high-level daily activities, we utilize Hidden state Conditional Random Field (HCRF), which is one of probabilistic graphical models. Through various experiments using two different datasets, KAD-70 and CAD-60, we showed the high performance of our method and the implementation system.