• Journal of Korean Society for Quality Management
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• v.19 no.2
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• pp.96-107
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• 1991

At the design stage of a plant, the plausible causes and pathways of release of hazardous materials are not clearly known. Thus there exist large amount of uncertainties on the consequences resulting from the operation of a fusion plant. In order to better handle such uncertain circumstances, we utilize the Probabilistic Risk Assessment(PRA) for the safety analyses on fusion power plant. In this paper, we concentrate on the tritium release accident. We develop a simple model that describes the process and flow of tritium, by which we figure out the locations of tritium inventory and their vulnerability. We construct event tree models that lead to various levels of tritium release from abnormal initiating events. Branch parameters on the event tree are assessed from the fault tree analysis. Based on the event tree models we construct influence diagram models which are more useful for the parameter updating and analysis. We briefly discuss the parameter updating scheme, and finally develop the methodology to obtain the predictive distribution of consequences resulting from the operating a fusion power plant. We also discuss the way to utilize the results of testing on sub-systems to reduce the uncertain ties on over all system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.55-65
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• 2020

With the development of display hardware, image interpolation techniques have been used in various fields such as image zooming and medical imaging. Traditional image interpolation methods, such as bi-linear interpolation, bi-cubic interpolation and edge direction-based interpolation, perform interpolation in the spatial domain. Recently, interpolation techniques in the discrete cosine transform or wavelet domain are also proposed. Using these various existing interpolation methods and machine learning, we propose decision tree classification-based image interpolation methods. In other words, this paper is about the method of adaptively applying various existing interpolation methods, not the interpolation method itself. To obtain the decision model, we used Weka's J48 library with the C4.5 decision tree algorithm. The proposed method first constructs attribute set and select classes that means interpolation methods for classification model. And after training, interpolation is performed using different interpolation methods according to attributes characteristics. Simulation results show that the proposed method yields reasonable performance.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.39-45
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• 2014

This paper proposes an architecture of a sensor network for gathering data under a powerful beam cluster tree architecture. This architecture is used when there is a need to gather data from sensor node where there is no sink node connected to an existing network, or it is required to get a series of data specific to an event or time. The transmit distance of the beam signal is longer than that of the usual sensor node. The nodes of the network make a tree network when receiving a beam message transmitting from the powerful root node. All sensor nodes in a sink tree network synchronize to the superframe and know exactly the sequence value of the current superframe. When there is data to send to the sink node, the sensor node sends data at the corresponding allocated channel. Data sending schemes under the guaranteed time slot are tested and the delay and jitter performance is explained.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.39-53
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• 2010

In this paper, we suggest an XML Development Support(XDS) System as a good developing tool to solve the problems that related with the database integration, increased to the developing terms and costs when the developing of XML programming base on the web server. XDS System is designed for the purpose of easily coding the XML program, of simply changing the programming structure and of completely maintaining the program environment. According to the predefined policy, XDS System provides necessary informations such as tables, columns, or relational keys from Database for developer. The developer step by step selects or sets what he needs. And XDS System creates an XML Tree with the result of selected information. The XML Tree includes all information of making an XML Schema and some XML Stylesheet. XDS System creates an XML Schema for all clients and creates many XML Stylesheets for each client using the XML Tree.

• Korean Management Science Review
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• v.23 no.1
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• pp.75-85
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• 2006

The rectilinear Steiner tree problem (RSTP) is to find a minimum-length rectilinear interconnection of a set of terminals in the plane. It is well known that the solution to this problem will be the minimal spanning tree(MST) on some set Steiner points. The RSTP is known to be NP-complete. The RSTP has received a lot of attention in the literature and heuristic and optimal algorithms have been proposed. A key performance measure of the algorithm for the RSTP is the reduction rate that is achieved by the difference between the objective value of the RSTP and that of the MST without Steiner points. A hybrid evolutionary strategy on RSTP based upon nodes set is presented. The computational results show that the hybrid evolutionary strategy is better than the previously proposed other heuristic. The average reduction rate of solutions from the evolutionary strategy is about 11.14%, which is almost similar to that of optimal solutions.

• Proceedings of the Safety Management and Science Conference
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• 2005.05a
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• pp.279-290
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• 2005

The purpose of this study is to attempt a Analysis of a pointed-end Equipment Arm Safety-Accident for Fault Tree Analysis. Three major techniques were used first problem is Z-Model by which accident Analysis & prevention of a pointed-end Industry can be made, Fault Tree Analysis(FTA) bywhich quantification of a pointed-end Equipment accident Analysis can be made it 5 years in past and the third, manual-written by which minimal cut set to accident can be Identified. A example has been made of issue point a pointed-end Equipment that the Arm in loader happen to Injuries. According to the Analysis lack of safety knowledge, unsafety-behavior seem to be the primal cause of accident. Comparision of the accident cause to actual report demonstratesthat the FTA a efficient tool for Industrial Accident prevention.

• Journal of the Korea Safety Management & Science
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• v.4 no.1
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• pp.37-47
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• 2002

Risk analysis is a formal deductive procedure for determining combinations of component failures and human errors that could result in the occurrence of specified undesired events at the system level. This method can be used to analyze the vast majority of industrial system reliability problems. This study deals with the application of knowledge-engineering and a methodology for the assessment ＆ measurement of reliability, availability, maintainability, and safety of industrial systems using FTA(fault tree analysis), A fuzzy methodology for fault-tree evaluation seems to be an alternative solution to overcome the drawbacks of the conventional approach (insufficient Information concerning the relative frequencies of hazard events). To improve the quality of results, the membership functions must be approximated based on heuristic considerations, The purpose of this study is to describe the knowledge engineering approach, directed to integrate the various sources of knowledge involved in a FTA.

• Journal of the Korea Safety Management & Science
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• v.3 no.2
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• pp.113-121
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• 2001

Today, facilities are composed of many complex components or parts. Because of this characteristics, the frequency of failures is decreasing, but the strength of failures is increasing; therefore, the failure analysis about many complex components or parts was needed. In the former research about Fault Tree Analysis, failure data of similar facilities have been used for forecasting about target system or components, but in case that the system or components for forecasting failure is new or qualitative and quantitative data are given simultaneously, there are many difficulty in using Fault Tree Analysis with this incorrect failure data. Therefore, this paper deal with the Fault Tree Analysis method which be applied with Fuzzy theory in above case. In case that , therefore, if there is no the correct failure data, it is represented a system or components as qualitative variable. subsequently, it converted to the quantitative value using fuzzy theory, and the values used as the value for failure forecast.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.375-381
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• 2014

Data mining is a process of discovering useful patterns or information from large amount of data. Decision tree is one of the data mining algorithms that can be used for both classification and prediction and has been widely used for various applications because of its flexibility and interpretability. Decision trees for classification generally generate a number of rules that belong to one of the predefined category and some rules may belong to the same category. In this case, it is necessary to determine the significance of each rule so as to provide the priority of the rule with users. The purpose of this paper is to propose a rule selection method in classification tree models that accommodate the umber of observation, accuracy, and effectiveness in each rule. Our experiments demonstrate that the proposed method produce better performance compared to other existing rule selection methods.

• Korea Journal of Hospital Management
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• v.10 no.1
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• pp.71-92
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• 2005

The purpose of this study is to analyze the efficiency in management of general hospitals and investigate the major factors on efficiency. Specifically, the management of each general hospital is evaluated by using Data Envelopment Analysis(DEA) technique which is a nonparametric statistical method for measurement of efficiency. Then, the influencing factors are investigated through analyses of Decision-Tree Model and Tobit Regression. The target hospitals were general hospitals in which bed sizes are between 200 and 500 among a total of 276 general hospitals. The main data of financial indicators were collected from 48 hospitals, and it was analyzed by using two statistical models. For Model I, three input and two output variables were used for efficiency evaluation. In particular, three input variables were the number of medical doctors, the number of paramedical personnel, and the bed size. And, two output variables were the numbers of inpatients and outpatients per year, adjusted by bed-size. The results of DEA analysis showed that only seven out of 48 hospitals(15%) turned out to be efficient. The decision-tree analysis also showed that there were six significant influencing factors for Model I. Six factors for Model I were Bed Occupancy Rate, Cost per Adjusted Inpatient, New Visit Ratio of Outpatients, Retired Ratio, Net Profit to Gross Revenues, Net Profit to Total Assets. In addition, the management efficiency of hospital is proved to increase as profit and patient-induced indicators increase and cost-related indicators decrease, by the Tobit regression model of independent variables derived from the decision-tree analysis. This study may be contributable to the development of analytic methodology regarding the efficiency of hospital management in that it suggests the synthetic measures by utilizing DEA model instead of suggesting simple ratio-analyzing results.