• Asia pacific journal of information systems
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• v.10 no.2
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• pp.51-69
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• 2000

Recently, as business problems become more complicated and require more precise quantitative results, large-scale model management systems are increasingly in demand for supporting the decision-making activities. In addition, as distributed computing over networks gains popularity, departmental computing systems are gradually adopted in an organization to facilitate collaboration of geographically dispersed multiple departments. In departmental collaborative model management systems, multiple departments share common models but approach them with different user-views depending on their departmental needs. Moreover, the shared models become evolved as their structures and the corresponding data sets change due to the dynamic nature of the operating environment and the inherent uncertainty associated with the problems. In such capacity, providing the multiple departmental users with synchronized and consistent views of the models is important to improve the overall productivity. In this paper, we propose a collaborative model management framework for coordinating model change and automatic user-view update in a departmental computing environment. To do so, we describes changes in the model and their effects occurred in departmental model management environments and identifies the constructs and processes for maintaining the consistency between a shared model and its departmental user-views. Especially, in this framework, generic model concept was adopted for accommodating diverse mathematical models in a uniform way in a modelbase and object-oriented database management systems(ODBMS) for combining the model management constructs and automatic user-view update mechanisms in a single formalism. A prototype object-oriented modeling environment was developed using an ODBMS called ObjectStore and $C^{++}$ programming language on Windows NT.

• Korean Management Science Review
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• v.33 no.1
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• pp.101-117
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• 2016

In 2000s, incidence of natural disaster is increasing continuously. Therefore, the necessity of research on the effective disaster response is emphasized. Korea is not safe from natural disaster. Natural disasters like torrential downpours, typhoons have occurred more frequently than before. In addition disasters like droughts and MERS has also occurred. Therefore, needs for effective systems and algorithms to respond disaster are increased. This study covers the vehicle routing problem for effective logistics in disaster situations caused by natural disasters. The emergency vehicle route problem has different property from the general vehicle route problem. It has the property of the importance of deadline, the uncertain and dynamic demand information, and the uncertainty in information transfer. In this study, a solution that focused on the importance of deadline. In this study, the heuristic solution using the genetic algorithm are suggested. Finally the simulation experiment which reflects the actual environment are conducted to verify the performance of the solution.

• KIEAE Journal
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• v.12 no.6
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• pp.85-92
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• 2012

The Korean government has introduced building regulations with improved energy conservation measures, including higher insulation levels for building envelope. However, there are many existing buildings that tend to consume more energy for heating and cooling than new buildings, as they were built under the former regulations with relatively higher U-values of walls and glazing. In order to improve energy efficiency in existing buildings, green remodelling of building envelope and building services are required. For existing buildings, building services improvements have been achieved through energy service company(ESCO), but much attention has not been paid to building envelope improvements with various reasons, such as uncertainty of energy saving effect design issues and costs. The aim of this study is to evaluate the impact of building envelope improvements in a typical commercial building on its heating and cooling energy loads. The results show that the improvement of glazing with lower U-values has the highest energy saving effects, followed by wall, roof and floor, under the condition of same level of insulation improvements. However, high insulated glazing increased LCC because of higher initial investment costs.

• Journal of Korea Water Resources Association
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• v.36 no.1
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• pp.105-115
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• 2003

The computation model which evaluates combined hydraulic and mechanical reliability, is developed to analyze the integrated reliability in water distribution system. The hydraulic reliability is calculated by considering uncertain variables like water demand, hydraulic pressure, pipe roughness as random variables according to proper distribution type. The mechanical reliability is evaluated by analyzing the effect of pipe network with sequential failure of network components. The result of this study model applied to the real pipe network shows that this model can be used to simulate the uncertain factors effectively in real pipe network. Therefore, The pipe-line engineers can design and manage the network system with more quantitative reliability, through applying this model to reliable pipe network design and diagnosis of existing systems.

• Earthquakes and Structures
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• v.20 no.1
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• pp.97-107
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• 2021

A comprehensive study on seismic performance of wood frame building in hilly regions is presented. Specifically, seismic fragility assessment of a typical wood frame building at various locations of the northeast region of India are demonstrated. A three-dimensional simplified model of the wood frame building is developed with due consideration to nonlinear behaviour of shear walls under lateral loads. In doing so, a trilinear model having improved capability to capture the force-deformation behaviour of shear walls including the strength degradation at higher deformations is proposed. The improved capability of the proposed model to capture the force-deformation behaviour of shear wall is validated by comparing with the existing experimental results. The structural demand values are obtained from nonlinear time history analysis (NLTHA) of the three-dimensional wood frame model considering the effect of uncertainty due to record to record variation of ground motions and structural parameters as well. The ground motion bins necessary for NLTHA are prepared based on the identified hazard level from probabilistic seismic hazard analysis of the considered locations. The maximum likelihood estimates of the lognormal fragility parameters are obtained from the observed failure cases and the seismic fragilities corresponding to different locations are estimated accordingly. The results of the numerical study show that the wood frame constructions commonly found in the region are likely to suffer minor cracking or damage in the shear walls under the earthquake occurrence corresponding to the estimated seismic hazard level; however, poses negligible risk against complete collapse of such structures.

• Korean Journal of Agricultural Science
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• v.48 no.2
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• pp.311-331
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• 2021

Climate change with extreme hydrological events has become a significant concern for agricultural water systems. Climate change affects not only irrigation availability but also agricultural water requirement. In response, adaptation strategies with soft and hard options have been considered to mitigate the impacts from climate change. However, their implementation has become progressively challenging and complex due to the interconnected impacts of climate change with socio-economic change in agricultural circumstances, and this can generate more uncertainty and complexity in the adaptive management of the agricultural water systems. This study was carried out for the agricultural water supply system in Seongju dam watershed in Seonju-gun, Gyeongbuk in South Korea. The first step is to identify system disturbances. Climate variation and socio-economic components with historical and forecast data were investigated Then, as the second step, problematic trends of the critical performance were identified for the historical and future climate scenarios. As the third step, a system structure was built with a dynamic hypothesis (causal loop diagram) to understand Seongju water system features and interactions with multiple feedbacks across system components in water, agriculture, and socio-economic sectors related to the case study water system. Then, as the fourth step, a mathematical SD (system dynamics) model was developed based on the dynamic hypothesis, including sub-models related to dam reservoir, irrigation channel, irrigation demand, farming income, and labor force, and the fidelity of the SD model to the Seongju water system was checked.

• Journal of Distribution Science
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• v.20 no.4
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• pp.95-100
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• 2022

Purpose: This study aimed to investigate whether distribution and service companies maintained their accounting information quality and provided reliable information despite the economic changes occurring after the outbreak of the COVID-19 pandemic in Korea. The distribution industry has enjoyed increased demand as many companies expanded their untact distribution channels, including to online sales. However, as the pandemic drags on, their future prospects remain uncertain. Research design, data, and methodology: In this study, we define 2018-2019 as the "pre COVID-19 period" and 2020 as the "post COVID-19 period." An empirical analysis was performed using a regression model that includes POST, the independent variable, indicating the post COVID-19 period, and discretionary accruals(DA), a proxy for earnings management, as a dependent variable. Results: The analysis shows that the coefficient of POST is significantly positive (+) for the dependent variable DA. This finding suggests that distribution and service companies engaged in more earnings management during the post COVID-19 period than during the pre COVID-19 period, indicating their awareness of the uncertainty of future business performance as the pandemic persists. An additional analysis confirmed that smaller companies with fewer stakeholders and higher information asymmetry tend to engage more in earnings management than larger companies.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.121-132
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• 2022

The uncertainty regarding inventory may impart dynamic impacts on corporate-level financial decisions. Among others, a decision about capital investment is a crucial decision that requires overall financial stability. Following these theoretical notions, the current study aims to identify possible consequences of inventory volatility relating to corporate capital investment decisions. We employed ten years of data (2010-2019) of non-financial sector firms to achieve the objective. The Driscoll-Kraay model was used to quantify the regression. The statistical results imply that inventory volatility negatively influences capital investment decisions due to information asymmetry about the current financial position. Additionally, more volatility brings discrepancies in managers' investing decisions to fulfill the possible demand options of capital investment that require processing the inventory. However, based upon the statistical findings, it is suggested to corporate managers that they should consider the financial sensitivity of enterprises regarding inventory volatility. Thus, the current study introduces new thoughts regarding inventory volatility and its empirical role in determining capital investment.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.114-114
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• 2020

Water contamination in a water distribution network (WDN) is harmful since it directly induces the consumer's health problem and suspends water service in a wide area. Actions need to be taken rapidly to countermeasure a contamination event. A contaminant source ident ification (CSI) is an important initial step to mitigate the harmful event. Here, a CSI approach focused on determining the contaminant intrusion possible location and time (PLoT) is introduced. One of the methods to discover the PLoT is an inverse calculation to connect all the paths leading to the report specification of a sensor. A filtering procedure is then applied to narrow down the PLoT using the results from individual sensors. First, we spatially reduce the suspect intrusion points by locating the highly suspicious nodes that have similar intrusion time. Then, we narrow the possible intrusion time by matching the suspicious intrusion time to the reported information. Finally, a likelihood-score is estimated for each suspect. Another important aspect that needs to be considered in CSI is that there are inherent uncertainties, such as the variations in user demand and inaccuracy of sensor data. The uncertainties can lead to overlooking the real intrusion point and time. To reflect the uncertainties in the CSI process, the Monte-Carlo Simulation (MCS) is conducted to explore the ranges of PLoT. By analyzing all the accumulated scores through the random sets, a spread of contaminant intrusion PLoT can then be identified in the network.

• Korea Trade Review
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• v.47 no.2
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• pp.133-154
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• 2022

The Baltic Capesize Index (BCI), which is used as an indicator for marine transportation of steel raw materials, is one of the key economic indexes for managing the risk of loss due to rapid market fluctuations when steel companies establish business strategies and procuring plans for raw materials. Still, the conditions of supply and demand of steel raw materials has been extremely affected by volatility shocks from drastic events like the financial crisis such as the Lehman Brothers incident and changes in the external environment such as COVID-19. And, especially since the 2008 financial crisis, endeavors to predict the market conditions of the steel raw material is becoming more and more arduous for the deepening uncertainty and increased volatility of BCI, which has been used as a leading indicator of the real economy. This study investigates the correlation between the steel raw material market and the marine transportation market by estimating the spillover effect of information between markets. The vector error correction model (VECM) was used to analyze information transfer based on the correlation between the BCI and crude steel production, capesize fleet supply, raw material price, and cargo volume.