• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.2
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• pp.121-125
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• 2010

Carbon Capture and Storage (CCS) technology mitigates the emission amount of carbon dioxide into the atmosphere and can reduce green house effect which causes the climate change. Deep saline aquifer or obsolete oil/gas storage etc. in the marine geological structure are considered as the candidates for the storage. The injection and storage relating technology have been interested in the global society, however the adverse effect caused by leakage from the system failure. Even the safety level of the CCS is very high and there is almost no possibility to leak but, still the risk to marine ecosystem of the high concentrated carbon dioxide exposure is not verified. The present study introduces the system and environmental risk assessment methods. The feature, event and process approach can be a good starting point and we found the some possibility from the fault tree analysis for evaluation. From the FEP analysis, we drove the possible scenario which we need to concentrate on the construction and operation stages.

• Journal of the Korean Society of Safety
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• v.36 no.4
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• pp.12-19
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• 2021

This paper presents a safety assessment method for FTA-based induction heating systems; the failures and causes of electrical fire are first analyzed for each part and module qualitatively, and methods to manage high probabilities of failure and electrical fire are considered, thereby improving the reliability of the induction heating system. The cumulative importance value (ACC) of the minimal cut set is drawn by setting failure as the top event, and STACK and SMPS are observed to account for about 70% of the induction heating system failures. Thus, intensively managing the basic events contained in the minimal cut set of failures for STACK and SMPS is expected to provide effective and stable operation of the induction heating system. When electrical fire is set as the top event, the STACK percentage is 90%. Accordingly, the current IGBT is changed to a FET to increase the applied voltage and prevent induction heating system failure, and a heat sink plane is installed to prevent FET heating caused by switching, thereby preventing an electrical fire. By classifying the parts and modules of the induction heating system in detail and by applying FTA based on actual failure rates and relevant data, more practical and reasonable results may be expected. Hence, continuous research must be conducted to ensure safety when using induction heating systems.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.426-433
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• 2017

This paper describes the development process, the innovative techniques used and insights gained from the latest integrated, full scope, multistate Level 2 PSA analysis conducted at the Leibstadt Nuclear Power Plant (KKL), Switzerland. KKL is a modern single-unit General Electric Boiling Water Reactor (BWR/6) with Mark III Containment, and a power output of $3600MW_{th}/1200MW_e$, the highest among the five operating reactors in Switzerland. A Level 2 Probabilistic Safety Assessment (PSA) analyses accident phenomena in nuclear power plants, identifies ways in which radioactive releases from plants can occur and estimates release pathways, magnitude and frequency. This paper attempts to give an overview of the advanced modeling techniques that have been developed and implemented for the recent KKL Level 2 PSA update, with the aim of systematizing the analysis and modeling processes, as well as complying with the relatively prescriptive Swiss requirements for PSA. The analysis provides significant insights into the absolute and relative importances of risk contributors and accident prevention and mitigation measures. Thanks to several newly developed techniques and an integrated approach, the KKL Level 2 PSA report exhibits a high degree of reviewability and maintainability, and transparently highlights the most important risk contributors to Large Early Release Frequency (LERF) with respect to initiating events, components, operator actions or seismic component failure probabilities (fragilities).

• The Journal of Engineering Geology
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• v.21 no.4
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• pp.281-293
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• 2011

We investigated the causes and characteristics of a landslide at Hwangryeong Mountain, Busan, based on aerial photos, annual precipitation data, rock fracture patterns, and geomorphic features using GIS Software, and a statistical analysis of tilted trees. The analyzed slope shows evidence of a previous slope failure event and the possibility of future failures. Although the NW-SE trending slope was relatively stable until 1975, a large-scale slope failure occurred between 1975 and 1985 due to complex factors, including favorably oriented geologic structures, human activity, and heavy rain. This indicates that a detailed study of geologic structures, slope stability, and rainfall characteristics is important for slope cuttings that could be a major factor and cause of urban landsliding events. The statistic analysis of tilted trees shows a slow progressive creeping type of mass wasting with rock falls oblique to the dip of the slope, with the slope having moved towards the west since 1985. A concentration of tree tilting has developed on the northwestern part of the slope, which could reach critical levels in the future. The analysis of deformed trees is a useful tool for understanding landslides and for predicting and preventing future landslide events.

• Journal of Advanced Navigation Technology
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• v.20 no.2
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• pp.148-154
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• 2016

Safety assessment is necessary to develop safety related CNS/ATM system. It includes functional hazard assessment (FHA), effects eliciting system safety requirement that mitigates system's hazardous event. This paper performs a case study for functional hazard assessment of A-SMGCS. To do this, related A-SMGCS studies from Eurocontrol and EMMA are surveyed, and assessment schemes of functional hazard from Eurocontrol and EMMA are combined. Not only FHA scope but also several assumptions for FHA are defined for Incheon airport. 29 hazards are identified and their severities are assessed. And exposures and safety objectives from hazards are analyzed using event tree analysis method. Differences between result of this study and result of EMMA are analysed, and assessment results in this study are also reviewed.

• Fire Science and Engineering
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• v.33 no.5
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• pp.149-154
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• 2019

The stability of firefighting pipes is crucial in the event of an earthquake. In Korea, specification-based designs are used in accordance with NFSC. However, engineering performance-based designs are used for buildings that have special requirements. For firefighting pipes, tree type pipe networks are usually utilized in buildings; however, they are characterized by several limitations. Hence, grid type and loop type networks are being utilized lately. Earthquake-resistant designs for firefighting pipes in Korea utilize NFPA 13 as the cookbook. Nevertheless, an engineering analysis is required to verify its reliability. The NFPA 13 standard used in Korea is a design method for engineers who lack earthquake engineering analysis knowledge of pipes and adapt ASCE and ASME guidelines. Earthquake resistant designs in Korea review braces only. Hence, various analyses under load conditions, such as the internal pressure of a pipe, force exerted by a continuous load, and an earthquake, are required to ensure reliability. An engineering earthquake-resistance analysis showed that tree type pipe networks are less stable than grid and loop type pipe networks. A comparison of earthquake-resistance analysis based on stress and strain revealed that strain analysis exhibited a conservative result value in the range of over-stress. Therefore, for the earthquake-resistance analysis of pipes, it is rational that engineers perform analysis to achieve the required standards through engineering analysis rather than uniform calculations, which should also be analyzed considering various analysis conditions.

• The Journal of the Korea Contents Association
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• v.7 no.9
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• pp.176-182
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• 2007

The natural treasure is not only a product of nature and but also a heritage we need to protect. Among natural treasures, because an animal and a plant have lives, one of them are sure to be disappeared. The natural treasure, Sok-ri mountain's Jungyeepoomsong is unique. It is the only alive tree which secure a government position. Currently the Jungyeepoomsong gets into difficulty because of natural disasters and insect attacks. In addition, it is in a critical condition of dying old since the age of the tree is over 600 years. The purpose of this paper is to investigate plans for tourism resources of the Jungyeepoomsong. Because the Jungyeepoomsong is a rare variety, it can be commercialized as a plant resource. Also, it can be used as the method of creating income for local residents. To achieve research objective, this paper proposes the plans of a lineage certification using a genetic analysis technology, a genealogical table control system utilizing purebred preservation and storytelling, a database construction between producers, sellers, and owners, a tourism event, a method of building Jungyeepoomsong's brand and preserving its value.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.390-399
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• 2022

Cyber security and resilience are phrases that describe safeguards of ICTs (information and communication technologies) from cyber-attacks or mitigations of cyber event impacts. The sole purpose of Risk models are detections, analyses, and handling by considering all relevant perceptions of risks. The current research effort has resulted in the development of a new paradigm for safeguarding services offered online which can be utilized by both service providers and users. customers. However, rather of relying on detailed studies, this approach emphasizes task selection and execution that leads to successful risk treatment outcomes. Modelling intelligent CSGs (Cyber Security Games) using MLTs (machine learning techniques) was the focus of this research. By limiting mission risk, CSGs maximize ability of systems to operate unhindered in cyber environments. The suggested framework's main components are the Threat and Risk models. These models are tailored to meet the special characteristics of online services as well as the cyberspace environment. A risk management procedure is included in the framework. Risk scores are computed by combining probabilities of successful attacks with findings of impact models that predict cyber catastrophe consequences. To assess successful attacks, models emulating defense against threats can be used in topologies. CSGs consider widespread interconnectivity of cyber systems which forces defending all multi-step attack paths. In contrast, attackers just need one of the paths to succeed. CSGs are game-theoretic methods for identifying defense measures and reducing risks for systems and probe for maximum cyber risks using game formulations (MiniMax). To detect the impacts, the attacker player creates an attack tree for each state of the game using a modified Extreme Gradient Boosting Decision Tree (that sees numerous compromises ahead). Based on the findings, the proposed model has a high level of security for the web sources used in the experiment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.229-249
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• 2022

This paper investigates machine learning models for predicting the designation of administrative issues in the KOSDAQ market through various techniques. When a company in the Korean stock market is designated as administrative issue, the market recognizes the event itself as negative information, causing losses to the company and investors. The purpose of this study is to evaluate alternative methods for developing a artificial intelligence service to examine a possibility to the designation of administrative issues early through the financial ratio of companies and to help investors manage portfolio risks. In this study, the independent variables used 21 financial ratios representing profitability, stability, activity, and growth. From 2011 to 2020, when K-IFRS was applied, financial data of companies in administrative issues and non-administrative issues stocks are sampled. Logistic regression analysis, decision tree, support vector machine, random forest, and LightGBM are used to predict the designation of administrative issues. According to the results of analysis, LightGBM with 82.73% classification accuracy is the best prediction model, and the prediction model with the lowest classification accuracy is a decision tree with 71.94% accuracy. As a result of checking the top three variables of the importance of variables in the decision tree-based learning model, the financial variables common in each model are ROE(Net profit) and Capital stock turnover ratio, which are relatively important variables in designating administrative issues. In general, it is confirmed that the learning model using the ensemble had higher predictive performance than the single learning model.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.198-206
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• 2019

A new methodology to analyze the nuclear material accountability for pyroprocessing system is developed. The $Pu-to-^{244}Cm$ ratio quantification is one of the methods for Pu accountancy in pyroprocessing. However, an uncertainty in the $Pu-to-^{244}Cm$ ratio due to the non-uniform composition in used fuel assemblies can affect the accountancy of Pu. A random variable, LOPu, is developed to analyze the probability of detection for Pu diversion of hypothetical scenarios at a pyroprocessing facility considering the uncertainty in $Pu-to-^{244}Cm$ ratio estimation. The analysis is carried out by the hypothesis testing and the event tree method. The probability of detection for diversion of 8 kg Pu is found to be less than 95% if a large size granule consisting of small size particles gets sampled for measurements. To increase the probability of detection more than 95%, first, a new Material Balance Area (MBA) structure consisting of more number of Key Measurement Points (KMPs) is designed. This multiple KMP-measurement for the MBA shows the probability of detection for 8 kg Pu diversion is greater than 96%. Increasing the granule sample number from one to ten also shows the probability of detection is greater than 95% in the most ranges for granule and powder sizes.