• Journal of Intelligence and Information Systems
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• 제25권2호
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Journal of Intelligence and Information Systems
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• 제24권4호
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• 제9권1호
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• pp.119-132
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• 2014

This study analyzed the failure prediction model of the firms listed on the KOSDAQ by considering whether there are embezzlement, malpractice and the largest shareholder changes or not. This study composed a total of 166 firms by using two-paired sampling method. For sample of failed firm, 83 manufacturing firms which delisted on KOSDAQ market for 4 years from 2009 to 2012 are selected. For sample of normal firm, 83 firms (with same item or same business as failed firm) that are listed on KOSDAQ market and perform normal business activities during the same period (from 2009 to 2012) are selected. This study selected 80 financial ratios for 5 years immediately preceding from delisting of sample firm above and conducted T-test to derive 19 of them which emerged for five consecutive years among significant variables and used forward selection to estimate logistic regression model. While the precedent studies only analyzed the data of three years immediately preceding the delisting, this study analyzes data of five years immediately preceding the delisting. This study is distinct from existing previous studies that it researches which significant financial characteristic influences the insolvency from the initial phase of insolvent firm with time lag and it also empirically analyzes the usefulness of data by building a firm's fail prediction model which considered embezzlement/malpractice and the largest shareholder changes as dummy variable(non-financial characteristics). The accuracy of classification of the prediction model with dummy variable appeared 95.2% in year T-1, 88.0% in year T-2, 81.3% in year T-3, 79.5% in year T-4, and 74.7% in year T-5. It increased as year of delisting approaches and showed generally higher the accuracy of classification than the results of existing previous studies. This study expects to reduce the damage of not only the firm but also investors, financial institutions and other stakeholders by finding the firm with high potential to fail in advance.

• Journal of Food Hygiene and Safety
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• 제20권1호
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• pp.22-35
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• 2005

A survey was conducted to investigate the perception of food sanitation officers toward the Genetically Modified Foods. They were mainly from Regional Agencies of KFDA, City/Province office, and National quarantine station. Some of them were professors of university and researchers of research institute. Most of respondents had experiences of hearing or reading GM foods (over $95\%$) and over $90\%$ of respondents much needed the label of GM foods. Although some of officers of city/province office and national quarantine station showed less knowledge than other respondent groups, most of respondents had basic knowledge about biology. The frequency of respondents worked over 20 years and worked in the general administration was higher than that of other groups in the question of unsafe of GM foods. The answer frequency of careless treatment of foods was highest in the question of risk factor, and the frequency of GM foods was lowest ($4.4\%$). It was concluded that food sanitation officers had positive opinion about GM foods, but there were some differences in the knowledge among agencies. Therefore, it is necessary more educations and informations are needed for food sanitation officers.

• Journal of the Korean Society of Environmental Restoration Technology
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• 제3권1호
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• pp.10-19
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• 2000

Due to the urbanization, concentrated population, and limited land exploitation in the modern society, the environment surrounding that we live in is getting polluted more and more, and it has become hard even to let urban children experience the nature. This research was conducted to help people recognize the importance of our natural resources through the environmental education of elementary school and to use school's practical open-space for the Indigenous Plants education. The results of this study are as follows : First, the status of a plant utilization in our institutional education : There were 362 species totally of 124 species of Trees, 156 species of Herbs, 63 species of Crops, and 19 species of Hydrophytes which appear in the elementary school text book. Of all, the most frequently appearing species of tree were the Malus pumila var. dulcissima, Pinus densijlora, Citrus unshiu, Diospyros kaki. Second, the effect of plant education using the land around schools : The result of research on the open-space of the 19 elementary schools located in Mapo-gu showed that most of the species planted are the Juniperus chinensisrose, Hibiscus syriacus. Pelargonium inquinans in the order of size, and the plants appearing in text book were grown in the botanical garden organized in 7 schools. Especially most of the Indigenous Plants were being planted in botanical garden, and Pinus densijlora, Abeliophyllum distichum, Polygonatum var. plurijlorum, Liriope platyphylla and so on. Last, the result of this research on recognition of Environment, Planting education and Indigenous plants : It showed that educational necessity of students and teachers about environment and Indigenous Plants was more than 80%. The management of botanical garden was conducted by some teachers and managers. The results of this study suggested that we needed the reconstruction of curriculum, the efficient application of plant education for effectiveness of using school environment and monitoring continually and construction information sources for the better environment education in the elementary schools.

• Archives of design research
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• 제11권2호
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• pp.129-140
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• 1998

This study aimed to grqJe for and present guideline roodel when the qJerator of domestic small manufacturing industry try to introch1ce the first industrial design by easier and more effective method. As the method of study, first of aiL examined the necessary of introducing industrial design throogh coosidering about the role and importance of small business. And next, analysed and examined the result of researching by enquete that is for qJerators of cbnestic small business. As a result, preconditioos for effective introducing industrial design were found. And, based 00 the preconditioos that were found through researching by enquete, examined the approachable introducing methods. Finally, set up the effectivable introducing methods of industrial design for doo1estic small manufacturing industry as a graphical model. As a result of study, First, the operator of small business who try to introduce industrial design needs to be well aware of these six cooditions as a prenise of effective awroach.1) coosciousness of role and versus a nation and a people of own industry Cereative 2) managing coosideratim and examinatim of a necessity of introducing industrial design as a cata1yst 3) A certain understanding aIntt essence and value of industrial design 4) Study and examinatim about a case of sucessful introducing industrial design arxl common introducing method of small business.5) Befarehand examinatim of introducing method making use of professional design organization and consultatim wicket 6) Prodent examination about the appointlrent puprpose, method of designer and infonmtion about designer. Second, as the position of small bnsiness that introduce industrial design fur the first time, it is confirmed that the aroroach going with introducing types - preliminary introducing, partitial introducing, regular introducing, whole industry level introducing - considered necessity rate of introducing industrial design and introducing range at the same time. This method is able to approach step by step, but it is confinmed that there is a characteristic in being able to select the method freely, and understanding easily for being coostructed visual form.

• Biomedical Science Letters
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• 제4권1호
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• pp.65-72
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• 1998

Recently there have been frequent reports on human infection caused by the Diphyllobothridae in Korea. The adequate opportunities for Koreans to eat raw fish, the primary infection medium of cestodes and the human infection through drinking water by cyclops, the first intermediate host are believed to be main reasons for the infection. The first task of this study was to classify and diagnose the species by differentiating morphological characteristic between scolex and proglottids of cestodes. However, the initially available diagnosis was done with the patient's symptoms and the eggs obtained from his stool. It is important to differentiate the species by the eggs of Diphyllobothrium latum especially in that it can help get advance information for a more reliable analysis in the near future. The morphological and diagnostic results from proglottids and eggs of Diphyllobothrium latum, Diphyllobothrium latum parvum and Spirometra erinacei are as follows； In each kind of cestodes from the patient's stool, the shape and size of 50 eggs were measured. Eggs of Diphyllobothrium latum had an operculum and were ovoidal or ellipsoid to elliptical in shape. Eggs of Diphyllobothrium latum parvum were more ovoidal in shape and smaller in size than Diphyllobothrium latum. And eggs of Spirometra erinacei were asymmetrical in width and long and slender in shape. The average lengths and widths of Diphyllobothrium latum, Diphyllobothrium latum parvum and Spirometra erinacei were 61.4$\times$41.7 $\mu\textrm{m}$, 55.9$\times$41.4 $\mu\textrm{m}$ and 66.7$\times$36.4 $\mu\textrm{m}$, respectively. After the segments of each cestode were fixed, embedding and hematoxylin-eosin dyeing on a microtome-made specimen were done. The micrographs of the semicon's aceto-carmine dyed specimen showed that Diphyllobothrium latum and Diphyllobothrium latum parvum had a centrally-located genital gland and an opened uterine pore. The yolks were observed on both sides of proglottids and had a typical rosette pattern. Yet, Diphyllobothrium latum parvum was shown smaller than Diphyllobothrium latum in the micrograph. Proglottids of Spirometra erinacei displayed that the uterus was rolled spirally more than five to seven times, and connected successively to the seminal vesicle in the cirrus sac. Shown above, this study was performed to measure the size of eggs and analyze the morphological characteristics of proglottids and provided the measurements of three types of cestodes obtained by a light microscope.

• The Korean Journal of Nuclear Medicine Technology
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• 제20권2호
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• pp.32-35
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• 2016

Purpose The goal for this study is to figure out that medical staff except Nuclear Medicine Department could be exposed to radiation from the patients who take Nuclear Medicine examination. Materials and Methods Total 250 patients (Bone scan 100, Myocardial SPECT 100, PET/CT 50) were involved from July to October in 2015, and we measured patient dose rate two times for every patients. First, we checked radiation dose rate right after injecting an isotope (radiopharmaceutical). Secondly, we measured radiation dose rate after each examination. Results In the case of Bone scan, dose rate were $0.0278{\pm}0.0036mSv/h$ after injection and $0.0060{\pm}0.0018mSv/h$ after examination (3 hrs 52 minutes after injection on average). For Myocardial SPECT, dose rate were $0.0245{\pm}0.0027mSv/h$ after injection and $0.0123{\pm}0.0041mSv/h$ after examination (2 hrs 09 minutes after injection on average). Lastly, for PET/CT, dose rate were $0.0439{\pm}0.0087mSv/h$ after examination (68 minutes after injection on average). Conclusion Compared to Nuclear Safety Commission Act, there was no significant harmful effect of the exposure from patients who have been administered radiopharmaceuticals. However, we should strive to keep ALARA(as low as reasonably achievable) principle for radiation protection.

• Asia pacific journal of information systems
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• 제17권4호
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• pp.187-206
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• 2007

The development of computer and information technology has been combined with the information superhighway internet infrastructure, so information widely spreads not only in special fields but also in the daily lives of people. Information ubiquity influences the traditional way of transaction, and leads a new E-commerce which distinguishes from the existing E-commerce. Not only goods as physical but also service as non-physical come into E-commerce. As the scale of E-Commerce is being enlarged as well. It keeps people from finding information they want. Recommender systems are now becoming the main tools for E-Commerce to mitigate the information overload. Recommender systems can be defined as systems for suggesting some Items(goods or service) considering customers' interests or tastes. They are being used by E-commerce web sites to suggest products to their customers who want to find something for them and to provide them with information to help them decide which to purchase. There are several approaches of recommending goods to customer in recommender system but in this study, the main subject is focused on collaborative filtering technique. This study presents a possibility of pre-evaluation for the prediction performance of customer's preference in collaborative filtering before the process of customer's preference prediction. Pre-evaluation for the prediction performance of each customer having low performance is classified by using the statistical features of ratings rated by each customer is conducted before the prediction process. In this study, MovieLens 100K dataset is used to analyze the accuracy of classification. The classification criteria are set by using the training sets divided 80% from the 100K dataset. In the process of classification, the customers are divided into two groups, classified group and non classified group. To compare the prediction performance of classified group and non classified group, the prediction process runs the 20% test set through the Neighborhood Based Collaborative Filtering Algorithm and Correspondence Mean Algorithm. The prediction errors from those prediction algorithm are allocated to each customer and compared with each user's error. Research hypothesis : Two research hypotheses are formulated in this study to test the accuracy of the classification criterion as follows. Hypothesis 1: The estimation accuracy of groups classified according to the standard deviation of each user's ratings has significant difference. To test the Hypothesis 1, the standard deviation is calculated for each user in training set which is divided 80% from MovieLens 100K dataset. Four groups are classified according to the quartile of the each user's standard deviations. It is compared to test the estimation errors of each group which results from test set are significantly different. Hypothesis 2: The estimation accuracy of groups that are classified according to the distribution of each user's ratings have significant differences. To test the Hypothesis 2, the distributions of each user's ratings are compared with the distribution of ratings of all customers in training set which is divided 80% from MovieLens 100K dataset. It assumes that the customers whose ratings' distribution are different from that of all customers would have low performance, so six types of different distributions are set to be compared. The test groups are classified into fit group or non-fit group according to the each type of different distribution assumed. The degrees in accordance with each type of distribution and each customer's distributions are tested by the test of ${\chi}^2$ goodness-of-fit and classified two groups for testing the difference of the mean of errors. Also, the degree of goodness-of-fit with the distribution of each user's ratings and the average distribution of the ratings in the training set are closely related to the prediction errors from those prediction algorithms. Through this study, the customers who have lower performance of prediction than the rest in the system are classified by those two criteria, which are set by statistical features of customers ratings in the training set, before the prediction process.

• Journal of Astronomy and Space Sciences
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• 제23권4호
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• pp.355-372
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• 2006

Mission opportunities and trajectory characteristics for the future Korean Mars mission have designed and analyzed using KSIV-III(Korea Space Launch Vehicle-III). Korea's first space center, 'NARO space center' is selected as a launch site. For launch opportunities, year 2033 is investigated under considering the date of space center's completion with KSLV series development status. Optimal magnitude of various maneuvers, Trans Mars Injection (TMI) maneuver, Trajectory Correction Maneuver (TCM), Mars Orbit Insertion (MOI) maneuver and Orbit Trim Maneuver(OTM), which are required during the every Mars mission phases are computed with the formulation of nonlinear optimization problems using NPSOL software. Finally, mass budgets for upper stage (launcher for KSIV-III and spacecraft are derived using various optimized maneuver magnitudes. For results, daily launch window from NARO space center for successful Korean Mars mission is avaliable for next 27 minutes starting from Apr. 16. 2033. 12:17:26 (UTC). Maximum spacecraft gross mass which can delivered to Mars is about 206kg, with propellant mass of 109kg and structure mass of 97kg, when on board spacecraft thruster's Isp is assumed to have 290 sec. For upper stage, having structure ratio of 0.15 and Isp value of 280 sec, gross mass is about 1293kg with propellant mass of 1099kg and structure mass of 194kg. However, including 10% margins to computed optimal maneuver values, spacecraft gross mass is reduced to about 148kg with upper stage's mass of 1352kg. This work will give various insights, requiring performances to developing of KSIV-III and spacecraft design for future Korean Mars missions.