• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.311-317
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• 1998

GIS is the system that has ability of integrating, managing, and analyzing the voluminous graphic and text data, which is adequate system to manage complex network of the underground utilities of urban area. A development of pipe safety management system is accomplished to construct efficiently a database of pipe line network and topographic data, create safety managing model, and estimate openly its safety by GIS. This system is constructed to evaluate easily pipe deterioration by the establishment of the geographic output system on it, search damaged objectives near surrounding area in a situation of destruction, and offer the information by which one can take quickly emergency. And also, it is constructed to prevent from accident occurring under work by presenting underground utilities and states of work.

• Journal of Applied Reliability
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• v.15 no.3
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• pp.207-215
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• 2015

Safety' can be used in a variety of ways and may also have different meanings when used in theoretical field and routinely used. In this paper, the 'safety' means that human injury, fire or physical accident condition does not occur while used by the end-user. The meaning of safety may be different by era and culture. Even in contemporary era, the meaning can be used differently by country, region and culture. As the rights of consumers are increasingly reinforced, we can expect the acceptable risk or safety level can rise higher. In this paper, the R-map of Japan and the European risk assessment guidelines (RAPEX) were reviewed considering domestic incidents database status and its applicability. Because it is difficult to make a model based on a R-map, a revised model was developed mainly based on European Assessment Model with a combination of the important characteristics of Japan model R-map. Also utilizing this revised model, the availability as a new risk assessment model was confirmed by comparing the test results for the same scenarios to the other risk assessment model (RAPEX/RAG).

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.4
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• pp.753-763
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• 2014

Recently financial institutions and large retailers have a large amount of personal information leakage accident occurred one after another, and the damage is a trend of increasing day by day. Regulation such as enforcing the encryption of the personal identification information are strengthened. Efficient technology to encrypt personal information is Format-preserving encryption. Typical encryption expand output data length than input data length and change a format. Format Preserving Encryption is an efficient method to minimize database and application modification, because it makes preserve length and format of input data. In this paper, to encrypt personal information efficiently, we propose newly Format Preserving Encryption using Block cipher mode of operation.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.44-52
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• 2019

In this study a safety evaluation method is presented for a ADAS vehicle to be tested in collision situation when multiple vehicles are present on a single lane. Test scenarios are developed based on Euro-NCAP assessment scenarios, accident database and related simulation results in previous works. An automated evaluation system that is called as the K-target mover is used for active safety evaluation experiments. The experiments are conducted with two types of tests. First, the rear-end collision tests with 25% and 50% overlap for the test vehicle and target vehicle are conducted with the two kinds of test vehicles. On the other hand, the rear-end collision tests which include multiple vehicles in a single lane with 25% and 50% overlaps, are also conducted. Experimental results show that the test vehicles with ADAS cannot recognize the collision situation sometimes in the developed test scenarios, even in the case that the test vehicle showed stable performance in the simple overlap scenarios.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.38-46
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• 2020

The accurate measurement of critical heat flux (CHF) in flow boiling is important for the safety requirement of the nuclear power plant to prevent sharp degradation of the convective heat transfer between the surface of the fuel rod cladding and the reactor coolant. In this paper, a System Engineering approach is used to develop a model that predicts the CHF using machine learning. The model is built using artificial neural network (ANN). The model is then trained, tested and validated using pre-existing database for different flow conditions. The Talos library is used to tune the model by optimizing the hyper parameters and selecting the best network architecture. Once developed, the ANN model can predict the CHF based solely on a set of input parameters (pressure, mass flux, quality and hydraulic diameter) without resorting to any physics-based model. It is intended to use the developed model to predict the DNBR under a large break loss of coolant accident (LBLOCA) in APR1400. The System Engineering approach proved very helpful in facilitating the planning and management of the current work both efficiently and effectively.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.67-77
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• 2020

Traditionally nuclear thermal hydraulic and nuclear safety has relied on numerical simulations to predict the system response of a nuclear power plant either under normal operation or accident condition. However, this approach may sometimes be rather time consuming particularly for design and optimization problems. To expedite the decision-making process data-driven models can be used to deduce the statistical relationships between inputs and outputs rather than solving physics-based models. Compared to the traditional approach, data driven models can provide a fast and cost-effective framework to predict the behavior of highly complex and non-linear systems where otherwise great computational efforts would be required. The objective of this work is to develop an AI algorithm to predict the peak fuel cladding temperature as a metric for the successful implementation of FLEX strategies under extended station black out. To achieve this, the model requires to be conditioned using pre-existing database created using the thermal-hydraulic analysis code, MARS-KS. In the development stage, the model hyper-parameters are tuned and optimized using the talos tool.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.96-102
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• 2020

The construction industry remains serious accidents, injuries, and fatalities due to it's unique, dynamic, and temporary nature. On workplace sites, Safety pre-task planning is one of the efforts to minimize injuries and help construction personnel to identify potential hazards. However, the working conditions are complicated. Many activities, including tasks or job steps, are executing at the same time and place. It may lead to an increase in the risks from simultaneous tasks. This paper contributes to addressing this issue by introducing a safety risk interaction analyzing framework. To accomplish this objective, accident reports of the Occupational Safety and Health Administration (OSHA) are investigated. The pairs of task incompatibility, which have time-space conflicts and lead to incidents, are found. Ontology technology is applied to build the risk database, in which the information is acquired, structuralized. The proposed system is expected to improve pre-task planning efficiency and relieve the burdens encountered by safety managers. A user scenario is also discussed to demonstrate how the ontology supports pre-task planning in practice.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.20 no.1
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• pp.32-38
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• 2024

The best estimate plus uncertainty methodologies for loss-of-coolant accident analyses make use of the best-estimate codes and relevant experimental databases. Inherently, best-estimate codes have various uncertainties in the model parameters, which can be quantified by the dedicated experimental database. Therefore, this study was devoted to establishing procedures for identifying the input parameters of predictive models and quantifying their uncertainty ranges. The rod bundle heat transfer experiments were employed as a representative reflood separate effect test, and the TRACE code was utilized as a best-estimate code. In accordance with the present procedure for uncertainty quantification, the integrated list of the influential input parameters and their uncertainty ranges was obtained through local sensitivity calculations and screening criteria. The validity of the procedure was confirmed by applying it to uncertainty analyses, which checks whether the measured data are within computed ranges of the variables of interest. The uncertainty quantification procedure proposed in this study is anticipated to provide comprehensive guidance for the conduct of uncertainty analyses.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.3
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• pp.183-190
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• 2008

The maintenance and management of each tunnel has been individually performed in depending on service, management agency, and tunnel size. The maintenance and management system for the existing tunnel consists of simple tunnel card and the computerization of basic tunnel data, now. There is not the systemic maintenance and management system for tunnel. Therefore, it has been impossible the systemic maintenance and management for tunnel due to loss of data obtained from each step, such as, plan, design, construction, or maintenance, with time. The objective of this study is to build the database system in combing the results of tunnel scanning with all data obtained from plan, design, construction, or maintenance step.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.4
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• pp.375-382
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• 2011

There is no system to obtain the basic data and proceed data and user input interface is complex, thus there are some limitation to utilize the oil spill prediction model. It is difficult to build the scientific response strategy in order to respond oil spill accident rapidly because it is impossible to operate the oil spill prediction model any time. In this study, the optimum operational system for oil spil prediction model has been developed considering the present system. External real time data has been linked because of impossibility of building all basic data and minimum database has been build in this study. Through this data system, real time oil spill prediction model can be utilized. And the user interface has been designed to reduce the error of the interface between user and model and the output interface has been proposed to analyze the result of modeling at multidimensional aspect. While the system for oil spill prediction model as the result of this study has some uncertainties because of depending on external data, the thing that we can predict oil spill using operate the model rapidly as soon as the accident occurred can be meaning in the response field.