• The Journal of Information Systems
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• v.33 no.3
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• pp.175-185
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• 2024

Purpose This study aims to analyze the relationship between consumption patterns and default risk among financially vulnerable households in a rapidly changing economic environment. Financially vulnerable households are more susceptible to economic shocks, and their consumption patterns can significantly contribute to an increased risk of default. Therefore, this study seeks to provide a systematic approach to predict and manage these risks in advance. Design/methodology/approach The study utilizes data from the Korea Welfare Panel Study (KOWEPS) to analyze the consumption patterns and default status of financially vulnerable households. To address the issue of data imbalance, sampling techniques such as SMOTE, SMOTE-ENN, and SMOTE-Tomek Links were applied. Various machine learning algorithms, including Logistic Regression, Decision Tree, Random Forest, and Support Vector Machine (SVM), were employed to develop the prediction model. The performance of the models was evaluated using Confusion Matrix and F1-score. Findings The findings reveal that when using the original imbalanced data, the prediction performance for the minority class (default) was poor. However, after applying imbalance handling techniques such as SMOTE, the predictive performance for the minority class improved significantly. In particular, the Random Forest model, when combined with the SMOTE-Tomek Links technique, showed the highest predictive performance, making it the most suitable model for default prediction. These results suggest that effectively addressing data imbalance is crucial in developing accurate default prediction models, and the appropriate use of sampling techniques can greatly enhance predictive performance.

• Journal of Radiation Protection and Research
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• v.33 no.1
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• pp.27-34
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• 2008

A Korean urban contamination model METRO-K (${\underline{M}}odel$ for ${\underline{E}}stimates$ the ${\underline{T}}ransient$ Behavior of ${\underline{R}}adi{\underline{O}}active$ Materials in the ${\underline{K}}orean$ Urban Environment, which is capable of calculating the exposure doses resulting from radioactive contamination in an urban environment, is taking part in a model testing program EMRAS (${\underline{E}}nvironmental$ ${\underline{M}}odelling$ for ${\underline{RA}}diation$ ${\underline{S}}afety$) oragnized by the IAEA (${\underline{I}}nternational$ ${\underline{A}}tomic$ ${\underline{E}}nergy$ ${\underline{A}}gency$). For radioactive contamination scenarios of Pripyat districts and a hypothetical RDD (${\underline{R}}adiological$ ${\underline{D}}ispersal$ ${\underline{D}}evice$), the predicted results using METRO-K were submitted to the EMRAS's Urban Contamination Working Group. In this paper, the predicted results for the contamination scenarios of a Pripyat district were shown in case of both without remediation measures and with ones. Comparing with the predictied results of the models that have taken part in EMRAS program, a feasibility for decision-making support of METRO-K was investigated. As a predicted result of METRO-K, to take immediately remediation measures following a radioactive contamination, if possible, might be one of the best ways to reduce exposure dose. It was found that the discrepancies of predicted results among the models are resulted from 1) modeling approaches and applied parameter values, 2) exposure pathways which are considered in models, 3) assumptions of assessor such as contamination surfaces which might affect to an exposure receptor and their sizes, 4) parameter values which are related with remediation measures applied through literature survey. It was indentified that a Korean urban contamination model METRO-K is a useful tool for dicision-making support through the participation of EMRAS program.

• Perspectives in Nursing Science
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• v.7 no.1
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• pp.23-35
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• 2010

Purpose: The purpose of this paper is to analyze the demand and supply of advanced practice nurses and suggest alternative benefit strategies in the Korean national health insurance. Methods: A revised demand & supply model was used to estimate the excess supply of APNs, and policy making process and key actors in the Korean health insurance were considered to develop a political approach to the APN issue. Results: The social demand for APNs is currently estimated to be less than 50% of its supply and the APN education program fell into difficulties in recruits. No reimbursement mechanism for APN's services in the national health insurance has given no economic incentive to hospital managers who have monopsony power in nursing labor market, which has caused the demand shortage of APNs in hospital industry. Payment for APN's services recognized as one of the most significant strategies to booster the social demand for APN's services should be carefully designed and implemented in the national health insurance. In line with this, key actors in health insurance policy decision-making include government, national assembly, labor unions, NGOs, civic groups, medical associations, and academia. Conclusion: The basic researches for APN's activities and cost-effectiveness analysis in clinical settings are required to support the strategies aforementioned. Constructing a policy network among key actors is able to make the payment strategy feasible, which will increase the socal demand for APNs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2067-2077
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• 2011

The recent trend in technology development is characterized as technology convergence, mainly between IT, BT and NT and also more and more industries are starting to use several technologies simultaneously or in a combined way theses days. As a result, the needs on technology interaction analysis is increasing for strategic technology management and policy-making. Responding to the needs, this research deals with technology innovation process in terms of technology competition, particularly focusing on the 17 new growth drivers in 3 areas, which has been announced by the Korean government as a new growth vision for Korean economy, and analyzing their co-evolutionary process. For the analysis, patent data, a representative data on technology innovation, is adopted. Then, Lotka-Volterra Competition model, a model frequently used to describe the dynamism of competitive innovation is applied to the data. The research results are expected to support strategic decision-makings such as effect policy-making or R&D priority-setting, by analyzing the relationship between the 3 areas, the 17 new growth drivers, or the particular technologies in the drivers.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.438-441
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• 2002

Korean construction firms have been continuing investment of IT for last ten years. However, manager did not support a decision-making of IT because there is no evaluation and feedback system of IT investment. This study is a preceding research of making IT evaluation model as a part of MOCT(the Ministry of Construction and Transportation)'s construction CALS/EC policy and makes a basic frame through a trend and state of IT survey. As a result of survey, To encourage them, IT development to be balanced in each members for successful stabilization of CALS/EC as well as IT evaluation will be conducted in accordance with one's environment, such as a role and level of companies.

• Archives of design research
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• v.16 no.2
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• pp.57-66
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• 2003

In order to develop color image, color simulation based on data processing techniques has been developed and applied to data interpretation tools or product design supporting systems. It has been a commonmethod to use image key words to search for data and provide color coordination samples that determine computer combination in computerized support systems until recently. However, this method does not reflect system designers and users taste or preference on making final choices of color coordination samples because the database was designed based on an assumption of standardized group that was established database from large scaled image evaluation research. In this study, we suggest a color coordination simulator that supports designer's final decision-making procedure on sample groups through the simulation of various color combination. The simulator allows communications with the system to explore a designer's color combination taste and preference, and provides a user for an efficient environment to judge the optimum result. The color coordination simulator was designed based upon Dual mapping model derived from a designer's thought process, and four steps of operations longrightarrowdefining color concept longrightarrowmaking color sample groupslongrightarrow simulation-determining ranking among final combination samples - will be assisting color design process.

• International Journal of CAD/CAM
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• v.6 no.1
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• pp.9-17
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• 2006

Performing inspections for Hull Condition Monitoring and Assessment as stipulated in IACS unified requirements and IMO's Condition Assessment Scheme (CAS) IMO Resolution MEPC.94(46), 2001, Condition Assessment Scheme, IMO Resolution MEPC.111(50), 2003, Amendments to regulation 13G, addition of new regulation 13H involves a huge amount of measurement data to be collected, processed, analysed and maintained. Information to be recorded consists of thickness measurements and visual assessment of coating and cracks. The amount of data and increasing requirements with respect to condition assessment demand efficient computer support. Currently, due to the lack of standardization for this kind of data, the thickness measurements are recorded manually on ship drawings or tables. In this form, handling of the measurements is tedious and error-prone and assessment is difficult. Data reporting and analysis takes a long time, leading to some repairs being performed only at the next docking of the ship or making an additional docking necessary. The recently started ED funded project CAS addresses this topic and develops-as a first step-a data model for Hull Condition Monitoring and Assessment (HCMA) based on XML-technology. The model includes simple geometry representation to facilitate a graphically supported data collection as well as an easy visualisation of the measurement results. In order to ensure compatibility with the current way of working, the content of the data model is strictly confined to the requirements of the measurement process. Appropriate data interfaces to classification software will enable rapid assessment by the classification societies, thus improving the process in terms of time and cost savings. In particular, decision-making can be done while the ship is still in the dock for maintenance.

• Journal of Hydrogen and New Energy
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• v.20 no.1
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• pp.22-30
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• 2009

Energy environment has been changing rapidly such as the fluctuation of oil prices and the effect on UNFCCC. Oil price change affects Korea's economy heavily due to her poor natural resources and large dependence of consumed energy resources. Korea takes the 4th place of importing the crude oil and 9th place in $CO_2$ emissions with the 1st place of $CO_2$ emissions increasing rate. Considering the current statue of Korea including oil price change and UNFCCC, Korea will be expected to be the Annex I nation due to Korean energy environments and the quantity of $CO_2$ emission. Energy technology development is a crucial key to cope with Korea's national energy security and environments. In this study, we establish the framework, which allocates the relative weights of assessment criteria and sub-criteria, for assessing and selecting R&D programs of energy technologies strategically. We integrated fuzzy theory and analytic hierarchy process (AHP) approach since the fuzzy AHP approach reflects the vagueness of human thoughts and perception effectively as making pairwise comparisons of criteria and alternatives. The fundamental data of this research results will support R&D planning phase for policy-makers and the production of well focused R&D outcomes.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.4
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• pp.264-274
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• 2006

Recently, a variety of organizations including enterprises tend to try to use reporting tools as a data analysis tool for decision making support because reporting tools are capable of formatting data flexibly. Traditional reporting tools have thin-client structure in which all of dynamic documents are generated in the server side. This structure enables reporting tools to avoid repetitive process to generate dynamic documents, when many clients intend to access the same dynamic document. However, generating dynamic documents for data analysis doesn't consider a number of potential readers and increases requests to the server by making clients input various parameters at short intervals. In the structure of the traditional reporting tools, the increase of these requests leads to the increase of processing load in the server side. Thus, we present the reporting tool that can generate dynamic documents at the client side. This reporting tool has a processing mechanism to deal with a number of data despite the limited memory capacity of the client side.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.726-741
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• 2022

The purpose of this study is to provide instructive theoretical models for art (music) education institutions especially when unpredictable risks, such as pandemics, occur again. Based on the customer behavior theory of the business-to-business-to-customer (B2B2C) platform, and in combination with the technology acceptance model (TAM) and expectation confirmation model (ECM), this study proposes an online education model from the perspective of art education. The framework is based on the three decision-making processes of the customer, and includes the product owner, content owner, and customer area. This paper highlights the factors that influence customers in making decisions when art education institutions are product owners. Regression analysis was introduced to study the factors influencing the expectation confirmation, and the overall fitting testing and six hypotheses testing of 385 effective samples were performed using the structural equation modeling (SEM). The results show that the course-design and after-service positively influenced the expectation confirmation, and the domain image positively influenced the continuance behavior. Negative emotions skipped the mediator (expectation confirmation) and directly exerted a significant negative impact on customers' willingness to continue system usage (continuance behavior). In addition, expectation confirmation positively influenced continuance behavior. The paths of detailed items comprising course-design, after-service, and negative emotion were also analyzed and discussed. In this path analysis, ordinary art learners did not believe that AI partners can play a very good auxiliary role. The findings contribute to the scope of information systems acting as an art education platform academically, and provide effective and theoretical support for the actual operation of art education institutions.