• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.33-40
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• 2003

Criticality prediction models that determine whether a design entity is fault-prone or non fault-prone play an important role in reducing system development costs because the problems in early phases largely affect the quality of the late products. Real-time systems such as telecommunication systems are so large that criticality prediction is mere important in real-time system design. The current models are based on the technique such as discriminant analysis, neural net and classification trees. These models have some problems with analyzing causes of the prediction results and low extendability. This paper builds a new prediction model, GAM, based on Genetic Algorithm. GAM is different from other models because it produces a criticality function. So GAM can be used for comparison between entities by criticality. GAM is implemented and compared with a well-known prediction model, BackPropagation neural network Model(BPM), considering Internal characteristics and accuracy of prediction.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.605-613
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• 2007

In order to overcome the difficulties of quantitative risk analysis such as complexity of model, we propose a systematic methodology for risk quantification of railway system which consists of 6 steps: The identification of risk factors, the determination of major scenarios for each risk factor by using event tree, the development of supplementary fault trees for evaluating branch probabilities, the evaluation of event probabilities, the quantification of risk, and the analysis in consideration of accident situation. In this study, in order to address the feasibility of the propose methodology, this framework is applied to the prototype risk model of nation-wide railway level crossings. And the quantification result based on the data of 2005 in Korea will also be presented.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1401-1408
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• 2000

Critical prediction models that determine whether a design entity is fault-prone or non fault-prone play an important role in reducing system development cost because the problems in early phases largely affected the quality of the late products. Real-time systems such as telecommunication system are so large that criticality prediction is more important in real-time system design. The current models are based on the technique such as discriminant analysis, neural net and classification trees. These models have some problems with analyzing cause of the prediction results and low extendability. In this paper, we propose a criticality prediction model using fuzzy rulebase constructed by genetic algorithm. This model makes it easy to analyze the cause of the result and also provides high extendability, high applicability, and no limit on the number of rules to be found.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07a
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• pp.468-471
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• 2003

Fault of under ground power cable occurs usually from the water tree such as the vented tree, the bow tree and the water-rich halo. The water tree penetrates to the polyethylene cable insulations. Sometimes, the water tree also diffuses to mother cable in the substation. In this paper, instead of replacement of the faulty cable, we tried to cure an electrical power cable degraded by the water trees with silicon injection method. And measured the results with the isothermal relaxation current analysis method. After cable cure, Chonil line was improved from 2.27 to 1.96 in a phase, from 2.148 to 2.020 in b phase, and from badness to 2.192 in c phase. And Keumam line was also improved from 2.419 to 1.920 in a phase, from 2.301 to 2.000 in b phase, and from badness to 1.957 in c phase.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.10C
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• pp.902-911
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• 2002

A wireless ad-hoc network is a collection of wireless mobile hosts forming a temporary network without the aid of any centralized adminstration or standard support services. Wireless ad-hoc networks may be quite useful in that they can be instantly deployable and resilient to change. In this environment, for many crucial distributed applications, it is necessary to design robust virtual infrastructures that are fault-tolerant, self-stabilized, and resource-efficient. For this task this paper proposes a scheme of maintaining robust spanning trees which are little affected by topological changes. By maintaining such a spanning tree and adapting it to the environments with frequent topological changes, one can improve the reliability and efficiency of many applications that use the spanning tree.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.644-654
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• 2024

After the Tohoku earthquake and tsunami (Japan, 2011), regulatory efforts to mitigate external hazards have increased both the safety requirements and the total capital cost of nuclear power plants (NPPs). In these circumstances, identifying not only disaster robustness but also cost-effective capacity setting of NPPs has become one of the most important tasks for the nuclear power industry. A few studies have been performed to relocate the seismic capacity of NPPs, yet the effects of multiple hazards have not been accounted for in NPP capacity optimization. The major challenges in extending this problem to the multihazard dimension are (1) the high computational costs for both multihazard risk quantification and system-level optimization and (2) the lack of capital cost databases of NPPs. To resolve these issues, this paper proposes an effective method that identifies the optimal multihazard capacity of NPPs using a multi-objective genetic algorithm and the two-stage direct quantification of fault trees using Monte Carlo simulation method, called the two-stage DQFM. Also, a capacity-based indirect capital cost measure is proposed. Such a proposed method enables NPP to achieve safety and cost-effectiveness against multi-hazard simultaneously within the computationally efficient platform. The proposed multihazard capacity optimization framework is demonstrated and tested with an earthquake-tsunami example.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2534-2546
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• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.2
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• pp.62-72
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• 2019

Due to the difficulties in forecasting the intensity and the source location of tsunami the countermeasures prepared based on the deterministic approach fail to work properly. Thus, there is an increasing demand of the tsunami hazard analyses that consider the uncertainties of tsunami behavior in probabilistic approach. In this paper a fundamental study is conducted to perform the probabilistic tsunami hazard analysis (PTHA) for the tsunamis that caused the disaster to the east coast of Korea. A logic tree approach is employed to consider the uncertainties of the initial free surface displacement and the tsunami height distribution along the coast. The branches of the logic tree are constructed by reflecting characteristics of tsunamis that have attacked the east coast of Korea. The computational time is nonlinearly increasing if the number of branches increases in the process of extracting the fractile curves. Thus, an improved method valid even for the case of a huge number of branches is proposed to save the computational time. The performance of the discrete weight distribution method proposed first in this study is compared with those of the conventional sorting method and the Monte Carlo method. The present method is comparable to the conventional methods in its accuracy, and is efficient in the sense of computational time when compared with the conventional sorting method. The Monte Carlo method, however, is more efficient than the other two methods if the number of branches and the number of fault segments increase significantly.

• Journal of KIISE:Information Networking
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• v.34 no.2
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• pp.120-133
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• 2007

A multicast tree includes several, possibly a large number of, paths connecting source-receiver pairs, and network failure may disable part of the multicast tree. Reconstruction of the entire multicast tree to recover from a component failure is highly undesirable, because some group members have to suffer service disruptions even though the communication paths to/from them are not affected by the failure. To limit reconfiguration region and to maximize the likelihood of successful reconfiguration, we propose and evaluate a pre-planned reconfiguration policy for QoS multicast sessions. Specifically, we equip a reconfiguration path (RP) with each end-to-end path that connects a source-receiver pair in the multicast tree, and reserve resources in advance along the RPs. Efficient resource-sharing techniques are applied to reduce the amount of resources reserved for RPs but not used in the absence of failures. This way, we prevent uncontrolled competition among different multicast sessions which may simultaneously try to recover from failures. We evaluate the performance of the proposed scheme using simulation on randomly-generated networks. We use the shortest-path routing for QoS multicast sessions, and simulate both source-based and shared multicast trees. The evaluation results indicates that successful pre-planned reconfiguration can be achieved for all group members with reasonable overhead. Our scheme is also shown to adapt well to dynamic changes of group membership.

• Journal of KIISE:Information Networking
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• v.31 no.5
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• pp.450-459
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• 2004

This paper studies the collective communication in the grid computing environment, which is characterized by the combination of heterogeneous networks as well as uneven, long communication delay. Efficient collective communication requires communication schedule, which in turn requires network information. When the network information is not accurate or network faults occur, the performance of collective communication can be markedly degraded. This paper proposes TTCC(Two-Tree Collective Communication) for scheduling collective communication in the grid. It Provides an efficient and reliable schedule even In this unfavorable network condition by maintaining two disjoint communication trees. Benefits of the proposed method are manifested via simulation, where the performance degradation with TTCC is much slower than those using conventional scheduling algorithms.