• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.401-408
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• 2001

Object-oriented software development methods are used to develop object-oriented software systems. Object-oriented systems are believed to habe better modularity, reusability, maintainability, and extensibility than systems modeled in conventional methods. Current object-oriented software development methods, however, are modeled in terms of procedural, functional, and structural models. There models cause problems such as tight coupling among activities, and uncontrolled access to global artifacts. In this paper, were introduce OMOS(Object-oriented software development Method for Object-oriented software System), an object-oriented modeling of object-oriented software development methods. Artifacts and their related activities are modeled as classes and objects. Development lifecycles are modeled as interactions among the objects. By modeling the software development method in an object-oriented way, OMOS achieves better reusability, flexibility, extensibility, and maintainability.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.299-313
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• 2009

As domestic logistics environment has changed into global logistics, various logistics parties are participating in processing logistics business. Goods is packed into container and delivered to consignee in steps. The goods may be damaged or lost since it has not directly delivered to consignee by single entity during the delivery process. Therefore, all parties want to know the flow of export/import cargos. However, it is very difficult to follow cargo flow consistently delivered from consignor to consignee. Because cargo flow does not be matched up information flow and information systems are based on neither standard business processes nor standard data, which makes it very difficult to associate logistics data among various logistic parties. This paper performs business process modeling for cargo tracking with international standard modeling methodology released by UN/CEFACT. And then, the standard data is defined for cargo tracking business process of unified and integrated business collaboration. The resulting business process model and data model will support international interoperability.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.7-15
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• 2017

This paper presents the results of the parametric study to investigate the effects of several analysis modeling parameters such as support conditions, member connectivities and cable member stiffness on the main mode shapes and natural frequencies of a representative disaster resilient greenhouse structure. In addition, an ambient vibration test was performed on the representative greenhouse structure and its main mode shapes and natural frequencies were obtained. By comparing the experimental and analysis results, a proper analysis modeling method of the representative greenhouse structure was proposed.

• Nuclear Engineering and Technology
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• v.42 no.6
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• pp.620-635
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• 2010

In this paper we describe current activities on the project Multi-Scale Modeling and Analysis of convective boiling (MSMA), conducted jointly by the Paul Scherrer Institute (PSI) and the Swiss Nuclear Utilities (Swissnuclear). The long-term aim of the MSMA project is to formulate improved closure laws for Computational Fluid Dynamics (CFD) simulations for prediction of convective boiling and eventually of the Critical Heat Flux (CHF). As boiling is controlled by the competition of numerous phenomena at various length and time scales, a multi-scale approach is employed to tackle the problem at different scales. In the MSMA project, the scales on which we focus range from the CFD scale (macro-scale), bubble size scale (meso-scale), liquid micro-layer and triple interline scale (micro-scale), and molecular scale (nano-scale). The current focus of the project is on micro- and meso-scales modeling. The numerical framework comprises a highly efficient, parallel DNS solver, the PSI-BOIL code. The code has incorporated an Immersed Boundary Method (IBM) to tackle complex geometries. For simulation of meso-scales (bubbles), we use the Constrained Interpolation Profile method: Conservative Semi-Lagrangian $2^{nd}$ order (CIP-CSL2). The phase change is described either by applying conventional jump conditions at the interface, or by using the Phase Field (PF) approach. In this work, we present selected results for flows in complex geometry using the IBM, selected bubbly flow simulations using the CIP-CSL2 method and results for phase change using the PF approach. In the subsequent stage of the project, the importance of effects of nano-scale processes on the global boiling heat transfer will be evaluated. To validate the models, more experimental information will be needed in the future, so it is expected that the MSMA project will become the seed for a long-term, combined theoretical and experimental program.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.113-124
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• 2019

Today many companies are offering IoT-enabled products and place emphasis on security from the planning stage to protect their products and user information from external threats. The present security levels, however, remain low because the time and resources invested in developing security requirements for each device are far from enough to meet the needs of a wide range of IoT products. Nevertheless, vulnerabilities of IoT devices have been reported continuously, which calls for more detailed security requirements for home IoT devices. In this context, this research identified threats of home IoT systems by using Microsoft Threat Modeling Tool. It then suggested measures to enhance the security of home IoT devices by developing security assessment items through comparative analysis of the identified threats, domestic and global vulnerability assessment standards and related research. It also verified the effectiveness of the developed security requirements by testing them against the existing ones, and the results revealed the security requirements developed in this research proved to be more effective in identifying vulnerabilities.

• The Korean Journal of Franchise Management
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• v.13 no.4
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• pp.1-12
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• 2022

Purpose: In 2020, the franchise industry accomplished a significant growth compared to the previous year, as the number of franchise companies increased by 9.0% while the number of franchise brands increased by 12.5%. Despite growth in size, the Korean franchise industry underwent many negative incidents, such as franchise ownership sales to private equity funds, that led to deterioration of businesses. From this point of view, this study aims to make various proposals to help policy makers develop franchise industry policies by analyzing trends of the current and previous presidential administrations' franchise policies and regulations using newspaper articles. Research design, data and methodology: A total of 7,439 articles registered in Naver API from February 25, 2013 to November 29, 2021 were extracted. Among them, 34 unrelated video articles were deleted, and a total of 7,405 articles from both administrations were used for analysis. The R package was used for word frequency analysis, word clouding, word correlation analysis, and LDA (Latent Dirichlet Allocation) topic modeling. Results: The keyword frequency analysis shows that the most frequently mentioned keywords during the previous administration include 'no-brand', 'major company', 'bill', 'business field', and 'SMEs', and those mentioned during the current administration include 'industry' and 'policy'. As a result of LDA topic modeling, 9 topics such as 'global startups' and 'job creation' from the previous administration, and 10 topics such as 'franchise business' and 'distribution industry' from the current administration were derived. The results of LDAvis showed that the previous administration operated a policy based on mutual growth of large and small businesses rather than hostile regulations in the franchise business, whereas the current administration extended the regulation related to franchise business to the employment sector. Conclusions: The analysis of past two administrations' franchise policy, it can be suggested that franchisors and franchisees may complement each other in developing the Fair Transactions in Franchise Business Act and achieving balanced growth. Moreover, political support is needed for sound development of franchisors. Limitations and future research suggestions are presented at the end of this study.

• Journal of Climate Change Research
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• v.7 no.4
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• pp.451-463
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• 2016

We explore the impact of Chinese future air pollutant emissions on ozone air quality in Northeast Asia (NEA) and health in South-Korea using an assessment framework including ICAMS (The Integrated Climate and Air Quality Modeling System) and BenMAP (The Environmental Benefits Mapping and Analysis Program). The emissions data sets from the climate change scenarios, the Representative Concentration Pathways (RCPs) (emission scenarios, EMSO), are used to simulate ozone air quality in NEA in the current (1996~2005, 2000s), the near future (2016~2025, 2020s) and the distant future (2046~2055, 2050s). Furthermore, the simulated ozone changes in the 2050s are used to analyze ozone-related premature mortality and economic cost in South-Korea. While different EMSOs are applied to the China region, fixed EMSO are used for other country regions to isolate the impacts of the Chinese emissions. Predicted ozone changes in NEA are distinctively affected by large changes in NOx emission over most of China region. Comparing the 2020s with the 2000s situation, the largest increase in mean ozone concentrations in NEA is simulated under RCP 8.5 and similarly small increases are under other RCPs. In the 2050s in NEA, the largest increase in mean ozone concentrations is simulated under RCP 6.0 and leads to the occurrence of the highest premature mortalities and economic costs in South-Korea. Whereas, the largest decrease is simulated under RCP 4.5 leads to the highest avoided premature mortality numbers and economic costs. Our results suggest that continuous reduction of NOx emissions across the China region under an assertive climate change mitigation scenario like RCP 4.5 leads to improved future ozone air quality and health benefits in the NEA countries including South-Korea.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.1-24
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• 2014

This study uses geo-spatial crop modeling to quantify the biophysical impact of weather extremes. More specifically, the study analyzes the weather extreme which affected maize production in the USA in 2012; it also estimates the effect of a similar weather extreme in 2050, using future climate scenarios. The secondary impact of the weather extreme on food security in the developing world is also assessed using trend analysis. Many studies have reported on the significant reduction in maize production in the USA due to the extreme weather event (combined heat wave and drought) that occurred in 2012. However, most of these studies focused on yield and did not assess the potential effect of weather extremes on food prices and security. The overall goal of this study was to use geo-spatial crop modeling and trend analysis to quantify the impact of weather extremes on both yield and, followed food security in the developing world. We used historical weather data for severe extreme events that have occurred in the USA. The data were obtained from the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA). In addition we used five climate scenarios: the baseline climate which is typical of the late 20th century (2000s) and four future climate scenarios which involve a combination of two emission scenarios (A1B and B1) and two global circulation models (CSIRO-Mk3.0 and MIROC 3.2). DSSAT 4.5 was combined with GRASS GIS for geo-spatial crop modeling. Simulated maize grain yield across all affected regions in the USA indicates that average grain yield across the USA Corn Belt would decrease by 29% when the weather extremes occur using the baseline climate. If the weather extreme were to occur under the A1B emission scenario in the 2050s, average grain yields would decrease by 38% and 57%, under the CSIRO-Mk3.0 and MIROC 3.2 global climate models, respectively. The weather extremes that occurred in the USA in 2012 resulted in a sharp increase in the world maize price. In addition, it likely played a role in the reduction in world maize consumption and trade in 2012/13, compared to 2011/12. The most vulnerable countries to the weather extremes are poor countries with high maize import dependency ratios including those countries in the Caribbean, northern Africa and western Asia. Other vulnerable countries include low-income countries with low import dependency ratios but which cannot afford highly-priced maize. The study also highlighted the pathways through which a weather extreme would affect food security, were it to occur in 2050 under climate change. Some of the policies which could help vulnerable countries counter the negative effects of weather extremes consist of social protection and safety net programs. Medium- to long-term adaptation strategies include increasing world food reserves to a level where they can be used to cover the production losses brought by weather extremes.

• The Journal of Engineering Geology
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• v.27 no.4
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• pp.429-438
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• 2017

Monte Carlo N-Particle (MCNP) modeling algorithm based on the Monte Carlo method was used to perform the simulation of neutron logging in order to increase the reliability and utilization of neutron logs applied in geological and resource engineering fields. To perform the simulation using MCNP, we used a realistic three-dimensional configuration of neutron sonde and formation. Validation of the modeling was confirmed by comparing the calibration curves of sonde manufacture with those calculated by MCNP modeling. After the validation, lithology effects, pore fluid effects, borehole diameter change, casing effect, and effects of borehole water level were investigated through modeling experiments. Numerical tests indicate that changes in neutron count ratio according to the lithology were quantitatively understood. In case of a borehole with a diameter of 3 inches, ratio of counting rates was higher than expected to be interpreted as borehole fluid has small effects on neutron logging. Effect of casing was also small in general, particular when porosity increases. Since modeling results above the groundwater level showed a tendency opposite to those below the groundwater level, neutron logs can be used to detect groundwater level. The modeling results simulated in this study for various borehole environments are expected to be used for data processing and interpretation of neutron log.

• Coupled systems mechanics
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• v.7 no.5
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• pp.555-581
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• 2018

The moment-resistant steel frames are frequently used as a load-bearing structure of buildings. Global response of a moment-resistant frame structure strongly depends on connections behavior, which can significantly influence the response and load-bearing capacity of a steel frame structure. The analysis of a steel frame with included joints behavior is the main focus of this work. In particular, we analyze the behavior of two connection types through experimental tests, and we propose numerical beam model capable of representing connection behavior. The six experimental tests, under monotonic and cyclic loading, are performed for two different types of structural connections: end plate connection with an extended plate and end plate connection. The proposed damage-plasticity model of Reissner beam is able to capture both hardening and softening response under monotonic and cyclic loading. This model has 18 constitutive parameters, whose identification requires an elaborate procedure, which we illustrate in this work. We also present appropriate loading program and arrangement of measuring equipment, which is crucial for successful identification of constitutive parameters. Finally, throughout several practical examples, we illustrate that the steel structure connections are very important for correct prediction of the global steel frame structure response.