• Journal of the Korea Safety Management & Science
• /
• v.17 no.1
• /
• pp.169-177
• /
• 2015

We develop a model to predict typhoons in Korea. We collect data for typhoons and classify those depending on the severity level. Following a Bayesian approach, we develop a model that explains the relationship between different levels of typhoons. Through the analysis of the model, we can predict the rate of typhoons, the probability of approaching Korean peninsular, and the probability of striking Korean peninsular. We show that the uncertainty for the occurrence of various types of typhoons reduces dramatically by adaptively updating model parameters as we acquire data.

• Journal of the Korea Safety Management & Science
• /
• v.13 no.1
• /
• pp.91-98
• /
• 2011

We develop a model to predict traffic accidents in Korea. In contrast to the classical approach that mainly uses regression analysis, Bayesian approach is adopted. A dependent model that incorporates the data from different kinds of accidents is introduced. The rate of severe accident can be updated even with no data of the same kind. The data of minor accident that can be obtained frequently is efficiently used to predict the severe accident.

• IE interfaces
• /
• v.6 no.2
• /
• pp.79-89
• /
• 1993

We develop a statistical model to describe nuclear power plant accidents and predict time to next accident of various levels. We adopt Bayesian approach to obtain posterior and predictive distributions for the time to next accident. We also derive an approximation method to solve many dimensional numerical integration problems that we often encounter in a Bayesian approach. We introduce Influence Diagrams in modeling, and parameter updating, thereby the dependency or independency among model parameters are clearly shown. Also Separable Updating Theorem is utilized to easily obtain the posterior distributions.

• Journal of Astronomy and Space Sciences
• /
• v.31 no.2
• /
• pp.121-130
• /
• 2014

Essential ideas, successes, and difficulties of Areal Density Analysis (ADA) for color-magnitude diagrams (CMD's) of resolved stellar populations are examined, with explanation of various algorithms and strategies for optimal performance. A CMD-generation program computes theoretical datasets with simulated observational error and a solution program inverts the problem by the method of Differential Corrections (DC) so as to compute parameter values from observed magnitudes and colors, with standard error estimates and correlation coefficients. ADA promises not only impersonal results, but also significant saving of labor, especially where a given dataset is analyzed with several evolution models. Observational errors and multiple star systems, along with various single star characteristics and phenomena, are modeled directly via the Functional Statistics Algorithm (FSA). Unlike Monte Carlo, FSA is not dependent on a random number generator. Discussions include difficulties and overall requirements, such as need for fast evolutionary computation and realization of goals within machine memory limits. Degradation of results due to influence of pixelization on derivatives, Initial Mass Function (IMF) quantization, IMF steepness, low Areal Densities ($\mathcal{A}$), and large variation in $\mathcal{A}$ are reduced or eliminated through a variety of schemes that are explained sufficiently for general application. The Levenberg-Marquardt and MMS algorithms for improvement of solution convergence are contained within the DC program. An example of convergence, which typically is very good, is shown in tabular form. A number of theoretical and practical solution issues are discussed, as are prospects for further development.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.4
• /
• pp.1283-1289
• /
• 2014

The state transition matrix are obtained by solving state equations in terms of Laplace inverse transformation and Cayley-Hamilton theorem, and an establishment of a precise discrete-iterative mapping of the voltage-fed buck-boost converter operating in discontinuous conduction mode is made. On the basis of the mapping, the converter bifurcation diagrams and Lyapunov exponent diagrams with the input voltage, the resistance, the inductance and the capacitance as the bifurcation parameters are obtained, and the effect of the parameters on the system stability is deeply studied. The results obtained show that they have a great influence on the stability of the system, and the general trend is that the increase of either the voltage-fed coefficient, input voltage or the load resistance, or the decrease of the filtering inductance, capacitance will make the system stability become poorer, and that all the parameters have a critical value, and when they are greater or less than the values, the system will go through stable 1T orbits, stable 2T orbits, 4T orbits, 8T orbits and eventually approaches chaos.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.12
• /
• pp.3500-3513
• /
• 1999

It is recognized that object-oriented methods and formal methods are two different main streams that will influence on the future direction of software engineering. A merging effort on these two technologies, named "a formal approach on system specifications using object-oriented methods" emerges rapidly and produces remarkable research results LOTOS is well-suited to an object-based approach. However, to provide a full object-oriented approach, we need to model generalization (i.e. inheritance and polymorphism). Most authors who have examined this topic have proposed extensions to LOTOS. As an extension of such an effort, this paper proposes a method that generates LOTOS specification from static structure diagrams in UML.

• Journal of Korean Medical classics
• /
• v.36 no.1
• /
• pp.17-32
• /
• 2023

Objectives : This paper investigates the background, meaning and origin of the descriptions of the Heart such as 'seven orifices', 'sanmao', 'saw-toothed four layered lines' that are unique to the diagram in the Donguibogam. Methods : First the Heart diagram of the Donguibogam was compared with other Zhangfu diagrams of the past. Materials related to unique features in the descriptions of the Heart in the Donguibogam were collected, against which descriptive features were analyzed. Results : Of the many unique features, the descriptive basis of the 'seven orifices' could be found in the Qixingban[七星板] as a physical entity reflecting basic anatomical knowledge. The 'sanmao', which is compared to the Santaixing[三台星], could be understood as a non-physical entity whose descriptive basis could be found in the Xinxuetu of the Xinching. It could be assumed that the 'saw-toothed four layered lines' are likened to the multi-layered petals or calyx of a lotus flower bud to describe the Pericardium, or to the multiple walls of a mountain fortress surrounding a palace to describe the Danzhong, which is the chest cavity. These features could be understood as results of spiritualism influence. Conclusions : It could be concluded that Heo Jun, in his attempt to describe the Heart in more detail than previous diagrams of the Zangfu, referenced popular texts and images based on anatomical knowledge of previous texts, added varied descriptions resulting in a new diagram with a completely different origin.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.30 no.3
• /
• pp.37-43
• /
• 2007

We use influence diagrams to describe event trees used in safety analyses of low-probability high-risk incidents. This paper shows how the branch parameters used in the event tree models can be updated by a bayesian method based on the observed counts of certain well-defined subsets of accident sequences. We focus on the analysis of the shared branch parameters, which may frequently often in the real accident initiation and propagation to more severe accident. We also suggest the way to utilize different levels of accident data to forecast low-probability high-risk accidents.

• Structural Engineering and Mechanics
• /
• v.49 no.1
• /
• pp.23-40
• /
• 2014

In this article, using finite element method of analysis (FEM), behavior of the endplate moment connection subjected to axial force and bending moment is investigated. In the FEM model, all the nonlinear characteristics such as material, geometry, as well as contact have been included. First, in order to verify the numerical model of the connection, an analysis of the endplate moment connection conducted without the application of the axial force. Results obtained from FEM indicating a close and good correlation with the experimental results. Then to investigate the influence of the axial forces, the connections subjected to axial forces as well as the bending moment are analyzed. To observe the overall effect of these actions, the momentaxial force interaction diagrams are drawn. It is observed that the presence of axial force even in a small value can change the behavior of the connection significantly. It is also shown that the axial forces can alter the failure mode of the connection; and therefore it could result in a different than the predicted moment capacity of the connection.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.41 no.4
• /
• pp.171-178
• /
• 2018

Recently, the continuing operation of nuclear power plants has become a major controversial issue in Korea. Whether to continue to operate nuclear power plants is a matter to be determined considering many factors including social and political factors as well as economic factors. But in this paper we concentrate only on the economic factors to make an optimum decision on operating nuclear power plants. Decisions should be based on forecasts of plant accident risks and large and small accident data from power plants. We outline the structure of a decision model that incorporate accident risks. We formulate to decide whether to shutdown permanently, shutdown temporarily for maintenance, or to operate one period of time and then periodically repeat the analysis and decision process with additional information about new costs and risks. The forecasting model to predict nuclear power plant accidents is incorporated for an improved decision making. First, we build a one-period decision model and extend this theory to a multi-period model. In this paper we utilize influence diagrams as well as decision trees for modeling. And bayesian statistical approach is utilized. Many of the parameter values in this model may be set fairly subjective by decision makers. Once the parameter values have been determined, the model will be able to present the optimal decision according to that value.