• The Journal of Korean Society for Radiation Therapy
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• v.23 no.1
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• pp.21-29
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• 2011

Purpose: The purpose of this master's thesis is to utilize basic data in order to improve the quality of life of cancer patients who received radiation therapy after analysing related factors that influence patient's quality of life and obtaining information about physical, mental problems of patients. Materials and Methods: By using a structured questionnaire about various characteristics and forms of support, I carried out a survey targeting 107 patients that experienced radiation therapy at a university hospital in the Daejeon metropolitan area from July 15 to August 15, 2010 and analysed the factors influencing quality of life. Results: In case of pain due to disease, 65.15 and painless 81.87 showed a high grade quality of life. As body weight decreases, the quality of life become lower. When the grade of quality of life according to economic characteristics was compared, all items except treatment period showed a difference (P=0.000). When the score of social support, family support, medical support and self-esteem was low, the mark of quality of life showed respectively 61.71, 68.77, 71.31, and 69.39 on the basis of 128 points. When the score of support form was high, the mark of quality of life showed 90.47, 83.29, 90.40, and 90.36 (P<0.05). When analyzing the correlation between social support, family support, medical support and self-esteem and the degree of quality of life, social support was 0.768, family support 0.596, medical support 0.434, self-esteem 0.516. They indicated the correlation of meaningful quantity statistically (P<0.01). The factors that improved the quality of life were married state, having a job and painless status. As monthly income increases, the quality of life was also much improved (P<0.05). Among the factors related to quality of life, social support and medical support and higher self-esteem scores of the quality of life score increased 0.979 point, 0.508 points and 1.667 point, respectively. Conclusion: In conclusion, the quality of life of cancer patients that received radiation treatment is related to social support, medical support and self esteem. Self-esteem is an important factor that influenced quality of life, so if government offers works that doesn't affect patient's health, they are a useful method that maximize self-esteem and lessen their financial burden at the same time. Along with these policies, the developments of the attention of medical and the program for cancer patient's family are needed for the purpose of improving quality of life of cancer patients. Lastly, medical team, patients and family have to cooperate in harmony to overcome difficulties of cancer patients.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

• Korean Journal of Psychosomatic Medicine
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• v.26 no.1
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• pp.59-67
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• 2018

Objectives : The aims of this study were to know the frequency and the nature of cognitive dysfunction in type 2 diabetics, and to reveal influencing variables on it. Methods : From eighty type 2 diabetics (42 males and 38 females), demographic and clinical data were obtained by structured interviews. Cognitive functions were measured using the MMSE-K (Korean Version of the Mini-Mental State Examination) and the Korean Version of the Montreal Cognitive Assessment (MoCA-K) tests. Severity of depression was evaluated by the Korean Version of the Hamilton Depression Rating Scale (K-HDRS). Results : 1) Among eighty type 2 diabetics, 13.75% were below 24 on the MMSE-K, while 38.8% were below 22 on the MoCA-K. 2) The total scores and subtest scores of the MoCA-K including visuospatial/ executive, attention, language, delayed recall and orientation were significantly lower in type 2 diabetics with cognitive dysfunction (N=31) than those without cognitive dysfunction (N=49) (p<0.001, respectively). 3) There were significant difference between type 2 diabetics with and those without cognitive dysfunction in age, education, economic status, body mass index, duration of diabetes, total scores of the K-HDRS, the MMSE-K and the MoCA-K (p<0.05, respectively). 4) The total scores of the MoCA-K had significant correlation with age, education, body mass index, family history of diabetes, duration of diabetes, total scores of the K-HDRS (p<0.05, respectively). 5) The risks of cognitive dysfunction in type 2 diabetics were significantly influenced by sex, education, fasting plasma glucose and depression. Conclusions : The cognitive dysfunction in type 2 diabetics seemed to be related to multiple factors. Therefore, more comprehensive biopsychosocial approaches needed for diagnosis and management of type 2 diabetes.

• Journal of agricultural medicine and community health
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• v.34 no.1
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• pp.58-66
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• 2009

Objectives: Active participation of poultry breeder in surveillance system of Avian Influenza (AI) is very important. Therefore this study was conducted to present basis data for active report of AI that is affected by media's coverage in poultry breeder. Methods: Subjects were 88 persons, 28 who were poultry breeder at epidemic area of AI and 60 who were general person at non-epidemic area. Data were collected by the trained investigator from Jul. 1 to Aug. 31, 2008. Respondents were interviewed by means of a structured questionnaire. Results: The third-person effect among perceptions of influence in media's report on the AI was higher in breeder (32.1%) than in non-breeder (10.0%). However, Confidence to media report on the AI was lower in breeder than in non-breeder. Intention to report of the AI was 71.4% in breeder respectively, was 90.0% in non-breeder. There was statistically significant lower in breeder than non-breeder. The cause of avoidance of report was 'economic damage' for 87.5%, which acocounted for the majority of cases. Confidence to media report on the AI were positively correlated with concern on the AI and perception on seriousness of the AI, but negatively correlated with the third-person effect. Conclusions: These results showed that intention to report of the AI of breeder was susceptible to influenced by the third person effect and confidence in media's report on the AI. Therefore we should give a special attention to increase active report of poultry breeder during epidemic period of AI which is consideration of reasonable strategy of media's coverage, including mind and emotion state of poultry breeder.

• Korean Journal of Food Science and Technology
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• v.31 no.3
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• pp.619-624
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• 1999

This work was to study the potential health food use of germinated colored rice after germinating and drying using microwave under vacuum. Colored rice was soaked in water at $15^{\circ}C$ for 2 days and then germinated at $25^{\circ}C$ for $3{\sim}4\;days$. The germinated colored rice was dried by different drying methods: microwave vacuum drying 1, microwave vacuum drying $2\;(drying{\rightarrow}crushing{\rightarrow}drying)$, hot air drying, vacuum drying and freeze drying. Each drier except freeze drier was set to maintain the sample temperature at $60^{\circ}C$. During microwave vacuum drying 1 or 2, the sample reached $60^{\circ}C$ much faster (within 5 min) and was dried much faster ($2{\sim}3\;hrs$ than the other drying methods. The initial drying rate of microwave vacuum drying was ten times faster than that of hot air drying. The microwave vacuum drying 2 retained the highest ${\alpha}-amylase$ activity, followed by microwave vacuum drying 1, freeze drying, vacuum drying, and hot air drying.

• Clinical and Experimental Pediatrics
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• v.53 no.3
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• pp.300-306
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• 2010

Purpose : Recent changes in the population structure of Korea, such as rapid decline in birth rate and exponential increase in old-aged people, prompted us to prepare a new health improvement program in children and adolescents. Methods : We reviewed current health screenings applied for children and adolescents in Korea and other developed countries. We collected and reviewed population-based data focused on mortality and morbidity, and other health-related statistical data. We generated problem lists in current systems and developed new principles. Results : Current health screening programs for children and adolescents were usually based on laboratory tests, such as blood tests, urinalysis, and radiologic tests. Almost all of these programs lacked evidence based on population data or controlled studies. In most developed countries, laboratory tests are used only very selectively, and they usually focus on primary prevention of diseases and health improvement using anticipatory guidance. In Korea, statistics on mortality and morbidity reveal that diseases related to lifestyle, such as obesity and metabolic syndrome, are increasing in all generations. Conclusion : We recommend a periodic health screening program with anticipatory guidance, which is focused on growth and developmental surveillance in infants and children. We no longer recommend old programs that are based on laboratory and radiologic examinations. School health screening programs should also be changed to meet current health issues, such as developing a healthier lifestyle to minimize risk behaviors—or example, good mental health, balanced nutrition, and more exercise.

• Pediatric Infection and Vaccine
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• v.18 no.2
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• pp.154-162
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• 2011

Purpose : The aim of this study was to identify the clinical characteristics of lower respiratory tract infection due to respiratory syncytial virus (RSV) in young children and to provide information for an effective guideline for palivizumab administration in Korea. Methods : We reviewed medical charts of 167 patients under 3 years of age who were hospitalized in Dongguk University Ilsan Hospital for lower respiratory tract infection between January 2007 and February 2011. Diagnosis of the virus was made based on the multiplex real time polymerase chain reaction. Results : There were 113 patients who were infected by respiratory syncytial virus. 90 patients were term infants and 23 patients were preterm infants. No difference was shown between term and preterm infants except the days of admission which was 9.0${\pm}$6.0 days and 12.6${\pm}$21.0 days respectively. In the preterm group their mean age at the time of admission was 5.21${\pm}$4.9 months and the mean gestational age was 33.1${\pm}$4.3 weeks, and the mean birth weight was 2,152${\pm}$950 g. Only 4 patients were born under 28 weeks gestational age and were candidates for palivizumab administration. Conclusion : Most of the patients with severe RSV lower respiratory tract infection were term or near term infants who were not candidates for palivizumab prophylaxis. A nationwide study is needed to make a new risk stratified guideline for RSV prophylaxis for our country.

• The Korean Journal of Air & Space Law and Policy
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• v.18
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• pp.135-183
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• 2003

Aerospace force is a determining factor in a modem war. The combat field is expanding to space. Thus, the legitimacy of establishing aerospace force is no longer an debating issue, but "how should we establish aerospace force" has become an issue to the military. The standard limiting on the military use of space should be non-aggressive use as asserted by the U.S., rather than non-military use as asserted by the former Soviet Union. The former Soviet Union's argument is not even strongly supported by the current Russia government, and realistically is hard to be applied. Thus, the multi-purpose satellite used for military surveillance or a commercial satellite employed for military communication are allowed under the U.S. principle of peaceful use of space. In this regard, Air Force may be free to develop a military surveillance satellite and a communication satellite with civilian research institute. Although MTCR, entered into with the U.S., restricts the development of space-launching vehicle for the export purpose, the development of space-launching vehicle by the Korea Air Force or Korea Aerospace Research Institute is beyond the scope of application of MTCR, and Air Force may just operate a satellite in the orbit for the military purpose. The primary task for multi-purpose satellite is a remote sensing; SAR sensor with high resolution is mainly employed for military use. Therefore, a system that enables Air Force, the Korea Aerospace Research Institute, and Agency for Defense Development to conduct joint-research and development should be instituted. U.S. Air Force has dismantled its own space-launching vehicle step by step, and, instead, has increased using private space launching vehicle. In addition, Military communication has been operated separately from civil communication services or broadcasting services due to the special circumstances unique to the military setting. However, joint-operation of communication facility by the military and civil users is preferred because this reduces financial burden resulting from separate operation of military satellite. During the Gulf War, U.S. armed forces employed commercial satellites for its military communication. Korea's participation in space technology research is a little bit behind in time, considering its economic scale. In terms of budget, Korea is to spend 5 trillion won for 15 years for the space activities. However, Japan has 2 trillion won annul budget for the same activities. Because the development of space industry during initial fostering period does not apply to profit-making business, government supports are inevitable. All space development programs of other foreign countries are entirely supported by each government, and, only recently, private industry started participating in limited area such as a communication satellite and broadcasting satellite, Particularly, Korea's space industry is in an infant stage, which largely demands government supports. Government support should be in the form of investment or financial contribution, rather than in the form of loan or borrowing. Compared to other advanced countries in space industry, Korea needs more budget and professional research staff. Naturally, for the efficient and systemic space development and for the prevention of overlapping and distraction of power, it is necessary to enact space-related statutes, which would provide dear vision for the Korea space development. Furthermore, the fact that a variety of departments are running their own space development program requires a centralized and single space-industry development system. Prior to discussing how to coordinate or integrate space programs between Agency for Defense Development and the Korea Aerospace Research Institute, it is a prerequisite to establish, namely, "Space Operations Center"in the Air Force, which would determine policy and strategy in operating space forces. For the establishment of "Space Operations Center," policy determinations by the Ministry of National Defense and the Joint Chief of Staff are required. Especially, space surveillance system through using a military surveillance satellite and communication satellite, which would lay foundation for independent defense, shall be established with reference to Japan's space force plan. In order to resolve issues related to MTCR, Air Force would use space-launching vehicle of the Korea Aerospace Research Institute. Moreover, defense budge should be appropriated for using multi-purpose satellite and communication satellite. The Ministry of National Defense needs to appropriate 2.5 trillion won budget for space operations, which amounts to Japan's surveillance satellite operating budges.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."