• Journal of Intelligence and Information Systems
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• v.25 no.2
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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 the Korean Society of Groundwater Environment
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• v.7 no.3
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• pp.103-115
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• 2000

The formation of brown-colored precipitates is one of the serious problems frequently encountered in the development and supply of groundwater in Korea, because by it the water exceeds the drinking water standard in terms of color. taste. turbidity and dissolved iron concentration and of often results in scaling problem within the water supplying system. In groundwaters from the Pajoo area, brown precipitates are typically formed in a few hours after pumping-out. In this paper we examine the process of the brown precipitates' formation using the equilibrium thermodynamic and kinetic approaches, in order to understand the origin and geochemical pathway of the generation of turbidity in groundwater. The results of this study are used to suggest not only the proper pumping technique to minimize the formation of precipitates but also the optimal design of water treatment methods to improve the water quality. The bed-rock groundwater in the Pajoo area belongs to the Ca-$HCO_3$type that was evolved through water/rock (gneiss) interaction. Based on SEM-EDS and XRD analyses, the precipitates are identified as an amorphous, Fe-bearing oxides or hydroxides. By the use of multi-step filtration with pore sizes of 6, 4, 1, 0.45 and 0.2 $\mu\textrm{m}$, the precipitates mostly fall in the colloidal size (1 to 0.45 $\mu\textrm{m}$) but are concentrated (about 81%) in the range of 1 to 6 $\mu\textrm{m}$in teams of mass (weight) distribution. Large amounts of dissolved iron were possibly originated from dissolution of clinochlore in cataclasite which contains high amounts of Fe (up to 3 wt.%). The calculation of saturation index (using a computer code PHREEQC), as well as the examination of pH-Eh stability relations, also indicate that the final precipitates are Fe-oxy-hydroxide that is formed by the change of water chemistry (mainly, oxidation) due to the exposure to oxygen during the pumping-out of Fe(II)-bearing, reduced groundwater. After pumping-out, the groundwater shows the progressive decreases of pH, DO and alkalinity with elapsed time. However, turbidity increases and then decreases with time. The decrease of dissolved Fe concentration as a function of elapsed time after pumping-out is expressed as a regression equation Fe(II)=10.l exp(-0.0009t). The oxidation reaction due to the influx of free oxygen during the pumping and storage of groundwater results in the formation of brown precipitates, which is dependent on time, $Po_2$and pH. In order to obtain drinkable water quality, therefore, the precipitates should be removed by filtering after the stepwise storage and aeration in tanks with sufficient volume for sufficient time. Particle size distribution data also suggest that step-wise filtration would be cost-effective. To minimize the scaling within wells, the continued (if possible) pumping within the optimum pumping rate is recommended because this technique will be most effective for minimizing the mixing between deep Fe(II)-rich water and shallow $O_2$-rich water. The simultaneous pumping of shallow $O_2$-rich water in different wells is also recommended.

• Journal of Aquaculture
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• v.19 no.2
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• pp.84-89
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• 2006

Effect of dietary inclusion of various sources of green tea on growth, immune system and challenging test of juvenile olive flounder Paralichthys olivaceus was investigated. Five experimental diets with triplicates were prepared: control, raw leaves, dry leaves, by-product and extract. Twenty five (an initial body weight of 52.5 g) were randomly distributed into 15 of 180 L flow-through tanks. Nutrient requirements of the experimental diets satisfied growth of juvenile olive flounder. The feeding trial lasted for 7 weeks. After 7-week feeding trial, blood were sampled from three randomly chosen fish for serum analysis of Iysozyme and bactericidal activity, and ten fish were infected with Edwardsiella tarda for challenging test from each tank. Weight gain (g/fish) of fish fed the diet containing extract and control diet was significantly higher than that of fish fed the other diets. Feed efficiency ratio for fish fed the diet containing extract and control diet was significantly higher than that for fish fed the diets containing raw leaves and by-product, but not significantly different from that for fish fed the diet containing dry leaves. Serum Iysozyme activity (units/ml) of fish fed the diets containing dry leaves and extract was significantly higher than that of fish fed the diets containing raw leaves and by-product, but not significantly different from that of fish fed the control diet. Serum bactericidal activity (${\times}10^6$ bacteria/ml) of fish fed the diet containing dry leaves and extract was significantly lower than that of fish fed the diets containing raw leaves, by-product and control diet in 3 hour. However, serum bactericidal activity of fish fed the diet containing extract was significantly lower than that of fish fed the other diets in 6 hour. And serum bacterial activity was low in fish fed the diets containing dry and raw leaves, by-product, and control in 6 hour in order. Accumulative mortality (%) of fish fed the control diet was low compared to that of fish fed the diets containing raw leaves and by-product, but high compared to that of fish fed the diets containing dry leaves and extract although no significant difference was found among treatments. In considering above results, dietary inclusion of extract and dry leaves of green tea seemed to be highly effective to improve immune system and endurance against E. tarda infection of juvenile olive flounder.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.2
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• pp.75-82
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• 2013

This study was carried out to contribute to the self-help and sustainability of grassroots business in Gangwon-do. To achieve this, after setting up the concept of community business, understanding the current designating status of community business and analyzing the business content and the business promotion system, I tried to analyze the continuing factors of businesses and shops, which are more than hundred years old, in Japan and seek a solution to the sustainability of community business in the province. The community business in the province, which is designated and operated, is like this; 86 preliminary social businesses, 62 town businesses, 38 social businesses. The total comes to 186. The preliminary social businesses and the social businesses are assigned more in urban area and the manufacturing sector and educational field have a lot of business contents. When it comes to the business promotion system, there are many incorporated companies and limited companies. While the town businesses are assigned more in county area, the agricultural food field and cultural world have a lot of business contents. When it comes to the main participant of business, the agricultural corporations took the first place overwhelmingly. Especially, I found out that the main participants of community business consist of 38 voluntary associations, which is 20.4 %, and we need to make up for the specialty deficiency in business management. In order to keep the continuity of community business in the province, we could achieve the results of manpower development through the case analysis research, securing good materials which can give the consumers confidence, increasing the quality of the products, maintaining high technical skills, keeping up the tradition of business and demanding forecasting. I think a successive research efforts will be required for securing good materials and increasing the quality of the products in tandem with the local community. And also we need to establish a supporting & operating system through the liaison between the business & academic world, business & administration, and business & business for securing a management specialty as an industrialist.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.667-673
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• 2010

Organic agriculture of especially medicinal crops has been interested and focused in taking the qualitative and safety agricultural products in order to maintain and improve the health and happiness of people. With respect to the organic agriculture relating to cropping system, objectives of this study were to examine the seedling establishment after seed germination and emergence and to investigate the early seedling growths of Astragalus membranaceus Bunge with treating two green manure crops, hairy vetch of legume and rye of gramineae, two different conditions of green manures, fresh and dry, and different seeding times. When the seeds were planted at once after treating the green manures with the fresh condition into the soil, the ratios of seedling establishment were very poor, less than 10% in hairy vetch and 20% in rye, respectively. They were increased gradually with delaying the seeding times after the treatments. With treating the green manures of dry conditions, the ratios of seedling establishment were up more than 50% in both hairy vetch and rye crops, showing that the damages of seedling establishment were more in hairy vetch than those in rye. The early seedling growths were slower in treating the green manures than those in the control, showing slow growth with fresh green manures compared to the dry. It would be very important and considered more to evaluate and utilize well the seed germination and the seedling establishment in cultivation of the organic agriculture using the green manure crops relating to the cropping system.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.624-630
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• 2010

In order to investigate the effects of continual pre-plant application of liquid pig manure (LPM) on growth and quality of rice in double cropping system of rice and malting barley, the liquid pig manure was applied after harvesting rice and malting barley for 3 years. Field experiment was designed with non-fertilizer, chemical fertilizer (CF) 100% recommended by soil testing, rice (LPM 50%+CF 50%)+malting barley (CF 100%), rice (LPM 50%+CF 50%)+malting barley (LPM 50%+CF 50%), rice (LPM 100%)+malting barley (CF 100%) and rice (LPM 100%)+malting barley (LPM 100%). The yield of rice was increased by 13% with increasing culm length and No. of panicle per hill as 482 kg $10a^{-1}$ in rice (LPM 100%)+malting barley (LPM 100%) plot compare with 427 kg $10a^{-1}$ in rice (CF 100%)+malting barley (CF 100%) plot. Whereas, lodging index was high in rice (LPM 100%)+malting barley (LPM 100%) plot by increasing of internodes length from 3rd to 4th and decreasing of breaking strength. When the quality of milled rice was compare with rice (CF 100%)+malting barley (CF 100%) plot, it was decreased by increasing of protein contents and decreasing of rate of perfect grain in rice (LPM 100%)+malting barley (LPM 100%) plot. The content of amylose was not significant by 19.4~22.0%. Toyo-taste value was not different in LPM 100% and CF 100% plot. Rice could be grown with only liquid pig manure 100%, but considering yield and quality of rice and lodging risk, basal fertilization by LPM 50% and top-dressing by CF 50% application was recommended for rice cultivation.

• Journal of Korea Technology Innovation Society
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• v.16 no.1
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• pp.323-345
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• 2013

In this paper, problems with the Korean system regulating the use of university royalties are identified and investigated in order to suggest measures to improve the system in a way that provides a better R&D environment at universities. The Delphi technique was used to gather data from royalty specialists at universities and government ministries. The first Delphi survey conducted used open questions to identify problems in the use of university royalties. Then, closed questions were used for the second Delphi survey. The number of responses and the frequency of answers were analyzed after the first survey, and validity, stability, and reliability analyses were conducted for the second survey. The measures suggested to improve the system regulating the use of university royalties are as follows: First, bonuses for researchers, which are currently 50% or more of collected royalties, need to be decreased, as they are rather high compared to similar bonuses in developed countries, which are around 30% of collected royalties. The guideline for limiting the bonuses, which is explained as XX% or less of collected royalties, is suggested to prevent the excessive use of royalties. Second, rewards for those who contribute to technology transfer and commercialization should be increased. It is also important to build a consensus around the need to reward those who contribute to technology transfer and commercialization. Third, the scale of re-investment into R&D needs to increase. Regulations on royalties should be meaningfully applied to create a positive feedback structure for R&D, which can be described as the process of research, R&D outcomes, technology transfer, collecting royalties, rewarding researchers, and re-investing in R&D. To build a university's R&D capability, re-investment into R&D needs to be regularized as XX% or more of royalties. Fourth, regulations on the royalties of ministries and universities need to be unified. Each category for using royalties needs to be regularized, with detailed matters such as the guideline, process and method for using royalties specified. Also, universities need to make their own specific regulations. Fifth, specific priorities on the use of royalties need to be suggested. Regulation is necessary for the categories that do not have guideline and priorities for the use of royalties. It is hoped that the findings of this research will contribute to reinforcing the R&D capability of universities.

• Korean Security Journal
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• no.62
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• pp.35-63
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• 2020

As the frequency and intensity of catastrophic disasters increase, there is widespread public sentiment that government capacity for disaster response and recovery is fundamentally limited, and that the involvement of civil society and the private sector is ever more vital. That is, in order to strengthen national disaster response capacity, governments need to build disaster systems that are more participatory and function through the channels of civil society, rather than continuing themselves to bear sole responsibility for these "wicked problems." With the advancement of smart mobile technology and social media, government and society as a whole have been called upon to apply these new information and communication technologies to address the current shortcomings of government-led disaster management. As illustrated in such catastrophic disasters as the 2011 Tohoku earthquake and tsunami in Japan, the 2010 Haitian earthquake, and Hurricane Katrina in the United States in 2005, the realization of participatory potential of smart technologies for better disaster response has enabled citizen participation via new smart technologies during disasters and resulted in positive impact on the management of such disasters. In this context, this study focuses on the South Korean context, and aims to analyze Korean government officials' readiness for public participation using smart technologies. On this basis, it aims to offer policy suggestions aimed at promoting smart technology-enabled citizen participation. For this purpose, it proposes a particular model, termed SMART (System, Motivation, Ability, Response, and Technology).

• Tuberculosis and Respiratory Diseases
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• v.52 no.4
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• pp.338-345
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• 2002

Background : Coal workers' pneumoconiosis(CWP) is a fibrotic lung disease resulting from the chronic inhalation of coal dust. Various cytokines and growth factors secreted from macrophages and monocytes play a key role in the pathogenesis of pneumoconiosis. The platelet-derived growth factor (PDGF)-BB and the insulin-like growth factor(IGF)-1 secreated from the macrophages and monocytes are believed to stimulate the accumulation of mesenchymal cells and fibrosis of the lower respiratory tract that is observed in fibrotic lung disease. The serum concentraion of PDGF-BB and IGF-1 in 30 CWP patients and 10 healthy controls were measured in order to determine if PDGF-BB and IGF-1 can be used as sensitive biomarkers in CWP. Method : Serum was collected from 30 patients with CWP(13 with simple CWP and 17 with complicated CWP) and 10 healthy controls. The serum concentrations of PDGF-BB and IGF-1 were measured using ELISA (R&D system, Minneapolis, MN). Results : The serum PDGF-BB concentration in patients with complicated CWP($10083.76{\pm}639.07pg/mL$) was significantly higher than in the patients with simple CWP ($8493.88{\pm}848.51pg/mL$) and the healthy controls ($3726.17{\pm}292.20pg/mL$) (p<0.05). Compared to the healthy controls ($413.40{\pm}1.94ng/mL$), there was no significant difference in the serum IGF-1 concentration in patients with simple ($366.77{\pm}183.67ng/mL$) and complicated CWP ($403.18{\pm}15.39ng/mL$) (p>0.05). Conclusion : These results show the important role of the PDGF-BB mediated pathways in the pathogenesis of CWP. These data suggests that the PDGF-BB serum concentration is a useful biomarkers of the fibrotic extent in CWP patients.