• Journal of the Korea Institute of Building Construction
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• v.17 no.3
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• pp.287-294
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• 2017

Recently the construction project is becoming large-sized, complicated, and modernize. This has increased the uncertainty of construction risk. Therefore, studies should be followed regarding scientifically identifying the risk factors, quantifying the frequency and severity of risk factors in order to develop a model that can quantitatively evaluate and manage the risk for response the increased risk in construction. To address the problem, this study analyze the probability distribution of risk causes, the probability of occurrence and frequency of the specific risk level through Monte Carlo simulation method based on the accident data caused at construction sites. In the end, this study derives quantitative analysis by analyzing the amount of risk and probability distributions of accident causes. The results of this study will be a basis for future quantitative risk management models and risk management research.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.541-548
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• 2016

The use of social media is already essential as a source of information for listening user's various opinions and monitoring. We define social 'risks' that issues effect negative influences for public opinion in social media. This paper aims to discriminate various linguistic features and reveal their effects for building an automatic classification model of social risks. Expecially we adopt a word embedding technique for representation of linguistic clues in risk sentences. As a preliminary experiment to analyze characteristics of individual features, we revise errors in automatic linguistic analysis. At the result, the most important feature is NE (Named Entity) information and the best condition is when combine basic linguistic features. word embedding, and word clusters within core predicates. Experimental results under the real situation in social bigdata - including linguistic analysis errors - show 92.08% and 85.84% in precision respectively for frequent risk categories set and full test set.

• Korean Journal of Construction Engineering and Management
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• v.22 no.5
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• pp.17-28
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• 2021

The construction industry has challenges and opportunities for Sustainable Development Goals (SDGs). The task of the construction industry is to improve the quality of construction, which is particularly necessary for the Fragile State. The construction industry's primary role is to provide jobs and maintain and improve the construction environment that affects the quality of life. Using the Delphi method and EFA in this study, [Pre-Execution] and [Execution] were derived as risk areas that require intensive hedge when penetrating the construction market in fragile states. It was concluded that the risk hedge to the master plan for the business conditions and infrastructure is the most important.

• Korean Journal of Construction Engineering and Management
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• v.17 no.4
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• pp.103-115
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• 2016

The 106 buildings of 200 meters' height or greater were completed around the world in 2015 (CTBUH, The Council on Tall Buildings and Urban Habitat). They beat every previous year on record, including the previous record high of 99 completions in 2014. This brings the total number of 200-meter-plus buildings in the world to 1,040, exceeding 1,000 for the first time in history and marking a 392% increase from the year 2000, when only 265 existed. South Korea recorded three completions during 2015 - improving slightly over 2014, in which it had one. This study focused on the fact that high-rise building development project risks have not reduced in Korea in spite of numerous studies and measures. And it attempted to examine whether existing studies and measures have been presented on the basis of the accurate analysis of existing studies and measures and classify and analyze the characteristics of each phase' s risk factors in the hope that its results would be one reference point as to the measure to prevent high-rise building development project risks in the future. A high-rise building development project is the high risk project as compared with the low-rise project. Because a high-rise development project takes long and is very sensitive to the changing environment. Therefore, in order to succeed the project it becomes necessary to effectively manage the risk involved in the process of the high-rise building development project. The result of this study can be used as the guideline to make the risk management system for the high-rise development project.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.485-490
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• 2003

Nowadays the rapid change in construction environment getting more globalized and complicated has caused lots of unexpected risks from inside and out of the country, so more sophisticated construction management strategies are being strongly needed. This paper suggests a risk management model with which we can estimate the appropriate contingency by quantifying the amount of probable risks immanent in large construction projects, which have a high degree of uncertainty in the anticipation of the total construction cost. To develop the model, the risk factors that make cost variations are elicited based on the real data of the contingencies assigned to the past projects. Furthermore, the influential relationship of risk factors is structured by applying the CRM(Cost Risk Model) which is the synthetic model of Monte Carlo Simulation, Influence Diagram and Decision Tree. The ultimate outcome of this research can by validated by tile case study with a large construction project performed.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.41-48
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• 2009

As enactment and enforcement of capital markets integration law, investment banks are going to be appeared in our financial market and be able to provide payment services. To provide these kinds of services, investment banks need to be participated in the financial network. As the financial network enormously affect the economy, the operation of the network will require a variety of risk managements. In this paper we define operational risk management criteria for the financial network such as security, in-time response, economical efficiency and stability to be required for the healthy economy and propose the configuration of the financial network system based on virtual private networks for investment banks to provide payment services. Finally we analyze that the proposed VPN configuration for financial networks has high security and in-time response with the cost and operation effective.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.43-54
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• 2024

This study presented a cybersecurity risk management system in a smart factory environment. A smart factory refers to a factory that optimizes the production system and increases efficiency. However, this digitized environment is vulnerable to cyber attacks, and manufacturing companies can suffer serious damage from disruptions in production systems or information leaks. Therefore, a systematic approach to effectively managing cyber security risks is essential in smart factories. In this study, a continuous security risk management system for each stage of the smart factory was proposed along with business process-based security risk assessment. These studies will help to further improve cybersecurity risk management in smart factories. It will also play an important role in ensuring that smart factories operate safely and efficiently.

• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.697-708
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• 2008

Operational risk is defined as the risk of loss resulting from inadequate or failed internal processes, people and systems, or external events. The advanced measurement approach proposed by Basel committee uses loss distribution approach(LDA) which quantifies operational loss based on bank's own historical data and measurement system. LDA involves two distribution fittings(frequency and severity) and then generates aggregate loss distribution by employing mathematical convolution. An objective validation for the operational risk measurement is essential because the operational risk measurement allows flexibility and subjective judgement to calculate regulatory capital. However, the methodology to verify the soundness of the operational risk measurement was not fully developed because the internal operational loss data had been extremely sparse and the modeling of extreme tail was very difficult. In this paper, we propose a methodology for the validation of operational risk measurement based on bootstrap confidence intervals of operational VaR(value at risk). We derived two methods to generate confidence intervals of operational VaR.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.109-117
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• 2023

Schedule delays present a major risk factor, as they can adversely affect construction projects, such as through increasing construction costs, claims from a client, and/or a decrease in construction quality due to trims to stages to catch up on lost time. Risk management has been conducted according to the importance and priority of schedule delay risk, but quantification of risk on the depth of schedule delay tends to be inadequate due to limitations in data collection. Therefore, this research used the BERT (Bidirectional Encoder Representations from Transformers) language model to convert the contents of aconstruction log, which comprised unstructured data, into WBS (Work Breakdown Structure)-based structured data, and to form a model of classification and quantification of risk. A process was applied to eight highway construction sites, and 75 cases of rain schedule delay risk were obtained from 8 out of 39 detailed work kinds. Through a K-S test, a significant probability distribution was derived for fourkinds of work, and the risk impact was compared. The process presented in this study can be used to derive various schedule delay risks in construction projects and to quantify their depth.

• The Journal of shipping and logistics
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• v.34 no.4
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• pp.565-581
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• 2018

The purpose of this study is evaluate factor for risk management of hazardous substance at ports. The analysis was conducted by applying Fuzzy-AHP methodology, through a questionnaire for hazardous substance experts from Busan, Gwangyang, Incheon, and Ulsan, which are the major Korean ports. Three measurement areas and nine sub-factors were selected for the study. The results of this analysis showed that "human resource management" (HR) was the most important factor (0.445) in the three measurement areas. After applying the conversion weight, the sub-factors were ranked according to their priority as follows: "a secure of administrator skill" (0.158) had the first rank, "an improvement in administrator duty" (0.150) had the second, and "consolidation of safety education" (0.136) had the third rank.