• Journal of Energy Engineering
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• v.21 no.1
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• pp.1-17
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• 2012

In Korea, there are increasing concerns on nuclear manpower demand and supply due to construction of domestic nuclear power plants and exporting nuclear power plant. In addition, aging of nuclear manpower is another important concern for stable nuclear manpower demand and supply. A shortage of skilled high-quality human resources resulted in massive retirements of senior workers may seriously undermine Korean nuclear competitiveness. This paper analyzed current state of aging of nuclear manpower based on statistical analysis on Korean nuclear organizations. The data used in this paper is manpower statistics of domestic nuclear organizations surveyed in 2001 and 2010. This paper analyzed trends of manpower change for 10 years and based on these analyses, has reviewed the level of the aging nuclear manpower by surveyed organization and integrated. Finally, this paper suggested to direction of manpower recruitment to cope with aging nuclear manpower and alternatives to find a solution to problems of nuclear manpower demand and supply.

• Journal of the Korean GEO-environmental Society
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• v.22 no.11
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• pp.31-37
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• 2021

To prevent accidents due to the cavities and loosened layers formed due to water leakage from the deteriorated buried pipes, evaluation of the changes in water contents around the buried pipes is required. As a method to evaluate the water contents of the soils, time domain reflectometry (TDR) system can be adopted. However, slender electrodes used in standard TDR probe may be damaged when buried in the ground. Thus, in this study, buried type TDR module was developed for the evaluation of the water contents with maintaining required shape of the electrodes in the ground. The TDR module is composed of three electrodes connected to the core conductor and outer conductor and a casing to prevent deformation and maintain alignment of the electrodes in the ground. For the verification of TDR waveforms measured using the TDR module, comparative analysis was conducted with the TDR waveforms measured using the standard TDR probe, and the relationship between the volumetric water content of the soils and the travel time of the guided electromagnetic wave was constructed. In addition, a model test was conducted to test the applicability of the buried type TDR module, and the experimental result shows that the TDR module clearly evaluates the changes in volumetric water contents due to the leakage from the modeled buried pipe. Therefore, the buried type TDR module may be effectively used for the health monitoring of the buried pipe and the evaluation of the water contents around the pipes buried in the urban pavements.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.3
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• pp.63-75
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• 2015

As forest therapy is getting more attention than ever, it is important to organize time for activity and location based on spatio-temporal distribution of weather condition in forest. This study aimed to analyze precise spatio-temporal distribution of weather condition by installing long-term weather monitoring device in Yonghyun national natural recreation forest and using acquired weather data in order to support forest recreation and therapy activity. First, we statistically compared 4 models of semi-variogram and the results were all similar. We selected and analyzed the circular model for this study because it was presumed to be the best model for this case. We derived 128 results from the circular model and through semi-variogram, we identified seasonal and temporal distributions of temperature and humidity. Then, we used boxplot, made of partial sill level, to identify significant differences in seasonal and temporal distributions. As a result, in spring and early morning, both temperature and humidity showed equalized result. On the other hand, in summer and early afternoon, both temperature and humidity showed uneven result. In spring and early morning, changes in weather condition are shown little from spatial shifting, it is ideal to perform recreational activities and forest therapy but in summer and early afternoon, it is unadvisable to do so as the changes in weather condition could be harmful unless any other means of preparations are made. This study proposes its significance by analyzing seasonal micro-weather of single recreation forest and presenting seasonal and temporal outcomes.

• Journal of the Korean earth science society
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• v.31 no.7
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• pp.720-737
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• 2010

This study is to analyze the temporal and spatial distributions of solar radiation in South Korea. Solar radiation data is observed every minute at 22 KMA (Korea Meteorological Administration) stations using pyranometer from January 2000 to August 2007. These data were calibrated using intensive comparative observation and solar radiation model. Intensive comparative observations are accomplished at 22 KMA stations between KNU (Kangnung (Gangneung-Wonju) National University) standard and station instruments during the month of August 2007. The solar radiation of a clear sky mainly is affected by precipitable water, solar altitude and geological height. Also old (raw) data is corrected by the solar radiation model only about clear day and is revised based on the temporal trend of instrument's sensitivity decrease. At all periods and all stations, differences between raw data (13.31 MJ/day) and corrected data (13.75 MJ/day) are 0.44 MJ/ day. So, the spatial distribution of solar radiation is calculated with seasonal and annual mean, and is the relationship with cloud amount is analyzed. The corrected data show a better consistency with the cloud amount than the old data.

• Tuberculosis and Respiratory Diseases
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• v.48 no.6
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• pp.837-852
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• 2000

Backgrounds : Today, tuberculosis cannot only be cured medically, but also controlled by public health. Despite the overall worldwide decline in tuberculosis, the disease continues to be a significant problem among developing countries and in the slums of large cities in some industrialized countries. Particularly, this communicable disease has come into the public health spotlight because of its resurgence in the 1990's. our country has been operating the Korean National Tuberculosis Control Program since 1962, focusing around public health centers. Therefore, this study aims to compare the effectiveness of tuberculosis control activities, one of the major public health activities in Korea, by producing indexes, such as the yearly registration rate per 100,000 population and treatment compliance of tuberculosis on in small areas (communities). Methods : This work was accomplished by constructing a time-series analytic model using data from "1980~2000: the Yearly Statistical Report" with patient registry data of 234 City. County. District public health centers and by identifying the factors influencing the tuberculosis indexes. Results : The trends of pulmonary tuberculosis positive point prevalence and pulmonary tuberculosis negative point prevalence on X-ray screening have declined steadily, beginning in 1981 and continuing to 1998 by region (city, county, district). Although the tuberculosis mortality rate steadily shows a declining trend by year and region, but Korea still ranks first among 29 OECD countries in 1998, with a tuberculosis mortality rate of 7.1 per 100,000 persons, according to the time-series analysis for fatal diseases. Conclusion : The results of the study will form the fundamental basis of future regional health care planning and the Korean Tuberculosis Surveillance System on 2000. Since the implementation of local autonomy through the Local Health Act of 1995, it has now become vita1 for each city, county, district public health centers to determine its own priorities for relevant health care management, including budget allocation and program goals.