• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.6
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• pp.1353-1360
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• 2009

This study examines the effects of internal control system and Analysis of characteristics and Earning management in Vulnerable Cooperation. During research period 2005${\sim}$2007, Purpose of this study is to examines whether financial characteristics has exist or not. Second, Earning management also. As a result of analysis are as follows, First T-test and logistic regression has found explanatory with stastical significance about CURRENT, RNPS, and DEPT. Second, DA of Vulnerable Cooperation is significantly higher than Normal cooperation.

• IE interfaces
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• v.20 no.4
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• pp.448-457
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• 2007

The small & micro business has the characteristics of both consumer credit risk and business credit risk. In predicting the bankruptcy for small-micro businesses, the problem is that in most cases, the financial data for evaluating business credit risks of small & micro businesses are not available. To alleviate such problem, we propose a bankruptcy prediction mechanism using the credit card sales information available, because most small businesses are member store of some credit card issuers, which is the main purpose of this study. In order to perform this study, we derive some variables and analyze the relationship between good and bad signs. We employ the new statistical learning technique, support vector machines (SVM) as a classifier. We use grid search technique to find out better parameter for SVM. The experimental result shows that credit card sales information could be a good substitute for the financial data for evaluating business credit risk in predicting the bankruptcy for small-micro businesses. In addition, we also find out that SVM performs best, when compared with other classifiers such as neural networks, CART, C5.0 multivariate discriminant analysis (MDA), and logistic regression.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.827-831
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• 2010

홍수범람 또는 피해에 의해 발생한 인명피해 및 재산손실과 이를 치유하기 위해 구호 복구에 들어가는 노력 등 수해가 가져오는 여러 가지 사회경제적 역기능은 홍수의 특성을 정확하게 이해하고 이를 예방하기 위한 적절한 계획수립 및 시행을 포함하는 과학적인 홍수분석시스템을 도입해서 홍수를 사전에 예방하거나 경감할 수 있는 수방대책을 수립하는 것이 방안이 될 수 있다. 우리나라의 하천에 대한 홍수재해특성은 체계적인 하천정비의 미비, 하천제방, 호안시설의 붕괴 및 유실 등이 있을수 있으며, 또한 저수지 소류지 보 등의 파제가 홍수시 잦은 발생을 초래하고 있다. 하천부속시설물(수문, 갑문, 방수구 등)의 기능 및 제방과의 접속부실은 최근에 많이 발생하는 하천의 피해양상이 된다. 하천유역관리 및 방제의 비구조물적인 요인으로는 하천유역의 개발에 의한 유출요인의 증대가 있으며, 하천연안 저지대의 난개발로 인한 상습침수 지역조장 등이 요인이 될 수 있다. 또한 소하천, 지방하천 및 국가하천의 분리관리로 인한 일관성있는 하천관리가 미비한 점도 있다. 항상 피해가 발생한 후 원상복구에 치중하는 복구계획과 환경단체 및 방제조직 그리고 제도 및 법규의 미비도 홍수재해의 원인이 될 수 있다. 우리나라는 지역특성 및 강우특성에 따라 많은 차이를 나타내기 때문에 그 특성에 적합한 홍수재해대응시스템을 구축해야 하는 것도 충분히 고려해야 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.351-356
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• 2014

Although the demand for histopathological examinations has been increasing, medical accidents in management of specimens also have been increasing because most of the examinations are processed manually which can cause careless handing, confusing information and mismatching during the procedure. In the future, histopatological examination will be used frequently for handing incurable diseases and verification of new drug. Thus, efficient and error-free management system for handling personalized medical history and test results is infallibly necessary. In this paper, I have proposed an integrated printing system for informatization of histopathological examination that support the u-Healthcare environment based on RFID in near future. The proposed system supports systematization of whole examination process and information of pathological samples. This system will contribute to reduction of costs, improvement of operational efficiency, and mostly fundamental prevention of medical accidents.

• Journal of Distribution Science
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• v.17 no.11
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• pp.73-79
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• 2019

Purpose: The purpose of this study was evaluated to compare the predictive power of distress prediction models by using discriminant analysis method and logit analysis method for food service franchise industry in Korea. Research design, data and methodology: Forty-six food service franchise industry with high sales volume in the 2017 were selected as the sample food service franchise industry for analysis. The fourteen financial ratios for analysis were calculated from the data in the 2017 statement of financial position and income statement of forty-six food service franchise industry in Korea. The fourteen financial ratios were used as sample data and analyzed by t-test. As a result seven statistically significant independent variables were chosen. The analysis method of the distress prediction model was performed by logit analysis and multiple discriminant analysis. Results: The difference between the average value of fourteen financial ratios of forty-six food service franchise industry was tested through t-test in order to extract variables that are classified as top-leveled and failure food service franchise industry among the financial ratios. As a result of the univariate test appears that the variables which differentiate the top-leveled food service franchise industry to failure food service industry are income to stockholders' equity, operating income to sales, current ratio, net income to assets, cash flows from operating activities, growth rate of operating income, and total assets turnover. The statistical significances of the seven financial ratio independent variables were also confirmed by logit analysis and discriminant analysis. Conclusions: The analysis results of the prediction accuracy of each distress prediction model in this study showed that the forecast accuracy of the prediction model by the discriminant analysis method was 84.8% and 89.1% by the logit analysis method, indicating that the logit analysis method has higher distress predictability than the discriminant analysis method. Comparing the previous distress prediction capability, which ranges from 75% to 85% by discriminant analysis and logit analysis, this study's prediction capacity, which is 84.8% in the discriminant analysis, and 89.1% in logit analysis, is found to belong to the range of previous study's prediction capacity range and is considered high number.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.411-425
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• 2013

The importance and necessity of the credit loan are increasing over time. Also, it is a natural consequence that the increase of the risk for borrower increases the risk of non-performing loan. Thus, we need to predict accurately in order to prevent the loss of a credit loan company. Our final goal is to build reliable and accurate prediction model, so we proceed the following steps: At first, we can get an appropriate sample by using several resampling methods. Second, we can consider variety models and tools to fit our resampling data. Finally, in order to find the best model for our real data, various models were compared and assessed.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.548-553
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• 2006

Activity-based productivity data can be used as an significant reference in many areas of project management such as performance evaluation and project planning. However, the existence of various factors influencing construction productivity makes it difficult to collect and analyze the productivity data. In the most of the domestic construction sites, there is no systematic method to collect and analyze the productivity data along with information on influencing factors; it is common to heavily rely on experience and intuition of field managers when dealing with construction productivity data. Therefore it is necessary to develop a management system for collecting and utilizing the productivity data as well as the factors influencing construction productivity. The main objective of this research is to define the construction productivity and its influencing factors at the activity level. In addition, methodologies on how to analyze the productivity data and to estimate productivity of future projects are proposed.

• Fire Science and Engineering
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• v.31 no.2
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• pp.82-88
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• 2017

Manpower will need to be increased to conduct special fire inspections. The aim of this study was to predict the manpower required. According to the estimate, 20,332 inspectors will be needed to conduct special fire inspection on a two-person team basis for a year. If the entire object is to be inspected for five-years, it will be inspected at 20% per year. The currently manpower is not enough to inspect all the objects, which will result in a poor inspection. Therefore, the adoption of a full and partial inspection system will be considered. If 10% full inspection and 10% partial inspection will be conducted, 2,734 inspectors will be needed, whereas if 2% of full inspection and 18% partial inspection are conducted, 1,669 inspectors will be needed.

• Journal of Family Resource Management and Policy Review
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• v.26 no.3
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• pp.19-34
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• 2022

There are growing concerns about debt insolvency among youth and low-income households. The deterioration in household debt quality among young people is due to a combination of sluggish employment, an increase in student loan burden and an increase in high-interest loans from the secondary financial sector. The purpose of this study was to explore the possibility of household debt default among young borrowers in Korea and to predict the factors affecting this possibility. This study utilized the 2021 Household Finance and Welfare Survey and used random forest algorithm to comprehensively analyze factors related to the possibility of default risk among young adults. This study presented the importance index and partial dependence charts of major determinants. This study found that the ratio of debt to assets(DTA), medical costs, household default risk index (HDRI), communication costs, and housing costs the focal independent variables.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.66-71
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• 2019

In this paper, a study was conducted on the method of using GPR data to predict rebar thickness inside a facility. As shown in the cases of poor construction, such as the use of rebars below the domestic standard and the construction of reinforcement, information on rebar thickness can be found to be essential for precision safety diagnosis of structures. For this purpose, the B-scan data of GPR was obtained by gradually increasing the diameter of rebars by making specimen. Because the B-scan data of GPR is less visible, the data was converted into the heatmap image data through migration to increase the intuition of the data. In order to compare the results of application of commonly used B-scan data and heatmap data to CNN, this study extracted areas for rebars from B-scan and heatmap data respectively to build training and validation data, and applied CNN to the deployed data. As a result, better results were obtained for the heatmap data when compared with the B-scan data. This confirms that if GPR heatmap data are used, rebar thickness can be predicted with higher accuracy than when B-scan data is used, and the possibility of predicting rebar thickness inside a facility is verified.