• Journal of the Korean Society for Railway
• /
• v.12 no.6
• /
• pp.936-943
• /
• 2009

In this study, a risk assessment model based on the ETA (Event Tree Analysis) and FTA (Fault Tree Analysis) is developed according to the procedure of hazard analysis and risk assessment in order to estimate the risk quantitatively. The FTA technique is applied to estimate the branch probability (frequency) and the ETA technique is applied to estimate the consequence for each branch path on the ET (Event Tree). A risk assessment model is developed by the combination of those ETA and FTA. In addition, the reliability and the validity of the risk assessment model are verified by comparing the risk estimated through the developed model with the actual equivalent fatality.

• New & Renewable Energy
• /
• v.9 no.2
• /
• pp.40-50
• /
• 2013

Government spending on research and development increased continuously is much more important to decision-making methodology for rational investment. Rely on a group of minority experts in the application of a general methodology, a tipping effect occur in specific technology field or difficult balanced procedure and objective control to maintain. This paper presents a qualitative-quantitative methodology to avoid such risks by utilizing Technology-Tree pertaining to energy R&D planning of the government Energy Technology Development program. Especially Energy Technology Development program "energy storage system" is applied to the analysis of Technology-Tree, mapping and analysis of existing government-supported projects during the recent 5 years, is derived essential missing elements of the technology value chain. This study suggests that significant evidence is utilized for improving efficiency of government R&D budget considering the importance of technology, domestic research-based and so forth, could be used to implement the R&D project planning.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.5
• /
• pp.56-62
• /
• 2008

This paper proposes the use of decision tree classification for the measuring pattern recognition from industrial Computed Radiography(CR) images used in nondestructive evaluation(NDE) of steel-tubes. It appears that NDE problems are naturally desired to have machine learning techniques identify patterns and their classification. The attributes of decision tree are taken from NDE test procedure. Geometric features, such as radiative angle, gradient and distance, are estimated from the analysis of input image data. These factors are used to make it easy and accurate to classify an input object to one of the pre-specified classes on decision tree. This algerian is to simplify the characterization of NDE results and to facilitate the determination of features. The experimental results verify the usefulness of proposed algorithm.

• Nuclear Engineering and Technology
• /
• v.52 no.10
• /
• pp.2238-2249
• /
• 2020

In a seismic PSA, dependency among seismic failures of components has not been explicitly modeled in the fault tree or event tree. This dependency is separately identified and assigned with numbers that range from zero to unity that reflect the level of the mutual correlation among seismic failures. Because of complexity and difficulty in calculating combination probabilities of correlated seismic failures in complex seismic event tree and fault tree, there has been a great need of development to explicitly model seismic correlation in terms of seismic common cause failures (CCFs). If seismic correlations are converted into seismic CCFs, it is possible to calculate an accurate value of a top event probability or frequency of a complex seismic fault tree by using the same procedure as for internal, fire, and flooding PSA. This study first proposes a methodology to explicitly model seismic dependency by converting correlated seismic failures into seismic CCFs. As a result, this methodology will allow systems analysts to quantify seismic risk as what they have done with the CCF method in internal, fire, and flooding PSA.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.25 no.3
• /
• pp.17-33
• /
• 2000

We consider the Steiner tree packing problem. For a given undirected graph G =(V, E) with positive integer capacities and non-negative weights on its edges, and a list of node sets(nets), the problem is to find a connection of nets which satisfies the edge capacity limits and minimizes the total weights. We focus on the switchbox routing problem in knock-knee model and formulate this problem as an integer programming using Steiner tree variables. The model contains exponential number of variables, but the problem can be solved using a polynomial time column generation procedure. We test the algorithm on some standard test instances and compare the performances with the results using cutting plane approach. Computational results show that our algorithm is competitive to the cutting plane algorithm presented by Grotschel et al. and can be used to solve practically sized problems.

• Proceedings of the KAIS Fall Conference
• /
• 2003.11a
• /
• pp.50-56
• /
• 2003

In the development of complex software system, it is important to use hierarchical use case model due to the complex scope of development procedure. The use case model is core factor of the OMG (Object Management Group)'s UML (Unified Modeling Language) diagrams. In this paper, we propose a novel method to check syntactic consistency automatically in use case models at the different level of abstraction. This method is a rule-based approach which utilizes actor tree, use case tree and use case description. The proposed method is simulated on ITS (Intelligent Transportation System) architecture for the verification.

• Communications for Statistical Applications and Methods
• /
• v.3 no.3
• /
• pp.125-133
• /
• 1996

In this paper, we present a algebraic technique for computing system reliability for complex system. The method was originally developed as an aid to fault tree analysis but it applies to general problems of reliability assessment. A success expression which directly gives the reliability expression is formed and simplified by the procedure. Several algorithms and examples are illustrated.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.42 no.4
• /
• pp.183-193
• /
• 2019

Process mining is an analytical technique aimed at obtaining useful information about a process by extracting a process model from events log. However, most existing process models are deterministic because they do not include stochastic elements such as the occurrence probabilities or execution times of activities. Therefore, available information is limited, resulting in the limitations on analyzing and understanding the process. Furthermore, it is also important to develop an efficient methodology to discover the process model. Although genetic process mining algorithm is one of the methods that can handle data with noises, it has a limitation of large computation time when it is applied to data with large capacity. To resolve these issues, in this paper, we define a stochastic process tree and propose a tabu search-genetic process mining (TS-GPM) algorithm for a stochastic process tree. Specifically, we define a two-dimensional array as a chromosome to represent a stochastic process tree, fitness function, a procedure for generating stochastic process tree and a model trace as a string of activities generated from the process tree. Furthermore, by storing and comparing model traces with low fitness values in the tabu list, we can prevent duplicated searches for process trees with low fitness value being performed. In order to verify the performance of the proposed algorithm, we performed a numerical experiment by using two kinds of event log data used in the previous research. The results showed that the suggested TS-GPM algorithm outperformed the GPM algorithm in terms of fitness and computation time.

• Journal of the Korea Safety Management & Science
• /
• v.6 no.2
• /
• pp.211-229
• /
• 2004

The basis of cyber trading has been sufficiently developed with innovative advancement of Internet Technology and the tendency of stock market investment has changed from long-term investment, which estimates the value of enterprises, to short-term investment, which focuses on getting short-term stock trading margin. Hence, this research shows a Short-term Stock Price Forecasting System on Learning Agent System using DTA(Decision Tree Algorithm) ; it collects real-time information of interest and favorite issues using Agent Technology through the Internet, and forms a decision tree, and creates a Rule-Base Database. Through this procedure the Short-term Stock Price Forecasting System provides customers with the prediction of the fluctuation of stock prices for each issue in near future and a point of sales and purchases. A Human being has the limitation of analytic ability and so through taking a look into and analyzing the fluctuation of stock prices, the Agent enables man to trace out the external factors of fluctuation of stock market on real-time. Therefore, we can check out the ups and downs of several issues at the same time and figure out the relationship and interrelation among many issues using the Agent. The SPFA (Stock Price Forecasting System) has such basic four phases as Data Collection, Data Processing, Learning, and Forecasting and Feedback.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.11
• /
• pp.435-440
• /
• 2018

This study was conducted to compare the effectiveness of the newly developed electrode pad of ECG with that of a conventional method. To accomplish this, participants who performed both methods on a 46 year old male model were queried and their satisfaction, time, and accuracy were measured by a specialist from 01/06/2018 to 15/06/2018. In the conventional method, a newly developed single pad employing a 12-lead ECG and SIM-Tree was employed. There were 104 total participants in this study (44% medical members). Evaluation of the total procedure time revealed that SIM (mean 65.39 seconds) was more rapid than C (mean 94.38 seconds) (p<0.05). When we evaluated the response after all process, satisfaction with SIM (mean 97.69 seconds) was greater than that with C (mean 68.5 seconds) (p<0.05). Moreover, the intra-class correlation coefficient (ICC) was 0.959 and accuracy was very high (p<0.05). In conclusion, the SIM-Tree was very effective based on procedure time, satisfaction and accuracy when compared with conventional methods.