• 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.

• Geophysics and Geophysical Exploration
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• v.11 no.3
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• pp.250-262
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• 2008

In order to assess the feasibility of the dipole-dipole electric method to the investigation of metallic ore deposit, both field data simulation and inversion are carried out for several simplified ore deposit models. Our interest is in a vein-type model, because most of the ore deposits (more than 70%) exist in a vein type in Korea. Based on the fact that the width of the vein-type ore deposits ranges from tens of centimeters to 2m, we change the width and the material property of the vein, and we use 40m-electrode spacing for our test. For the vein-type model with too small width, the low resistivity zone is not detected, even though the resistivity of the vein amounts to 1/300 of that of the surrounding rock. Considering a wide electrode interval and cell size used in the inversion, it is natural that the size of the low resistivity zone is overestimated. We also perform field data simulation and inversion for a vein-type model with surrounding hydrothermal alteration zones, which is a typical structure in an epithermal ore deposits. In the model, the material properties are assumed on the basis of resistivity values directly observed in a mine originated from an epithermal ore deposits. From this simulation, we can also note that the high resistivity value of the vein does not affect the results when the width of the vein is narrow. This indicates that our main target should be surrounding hydrothermal alteration zones rather than veins in field survey. From these results, we can summarize that when the vein is placed at the deep part and the difference of resistivity values between the vein and the surrounding rock is not large enough, we cannot detect low resistivity zone and interpret the subsurface structures incorrectly using the electric method performed at the surface. Although this work is a little simple, it can be used as references for field survey design and field data Interpretation. If we perform field data simulation and inversion for a number of models and provide some references, they will be helpful in real field survey and interpretation.

• Journal of the Korea Concrete Institute
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• v.26 no.4
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• pp.429-440
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• 2014

Since the World Trade Center and Pentagon attacks in 2001, terror, military attack, or man-made disaster caused impact, explosion, and fire accident have frequently occured on civil infrastructures. However, structural behavior researches on major Prestressed Concrete (PSC) infrastructures such as bridges, tunnels, Prestressed Concrete Containment Vessel (PCCVs), and LNG tanks under extreme loading are significantly lacking. Especially, researches on possible secondary fire scenarios after terror, bombing, collision of vehicles and vessels on concrete structures have not been performed domestically where most of the past researches related to extreme loadings on structures focused on an independent isolated extreme loading scenario. Due to the outcry of public concerns and anxiety of potential terrorist attacks on major infrastructures and structures, a study is urgently needed at this time. Therefore, in this study, the bi-directional prestressed concrete $1400{\times}1000{\times}300mm$ panels applied with 430 kN prestressing force using unbonded prestressing thread bars were experimentally evaluated under impact, fire, and impact-fire combined loadings. Due to test site restrictions, impact tests were performed with 14 kN impactor with drop heights of 10m and 3.5 m to evaluate impact resistance capacity. Also, fire and impact-fire combined loading were tested using RABT fire loading curve. The measured residual strength capacities of PSC and RC specimens applied with impact, fire, impact-fire combined loadings were compared with the residual strength capacity of undamaged PSC and RC specimens for evaluation. The study results can be used as basic research data for related research areas such as protective design and numerical simulation under extreme loading scenarios.

• Korean Journal of Cognitive Science
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• v.3 no.1
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• pp.61-78
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• 1991

This paper descibes the study of application of a modified Neocognitron model with backward path for the recognition of Hangul(Korean) syllabic characters. In this original report, Fukushima demonstrated that Neocognitron can recognize hand written numerical characters of $19{\times}19$ size. This version accepts $61{\times}61$ images of handwritten Hangul syllabic characters or a part thereof with a mouse or with a scanner. It consists of an input layer and 3 pairs of Uc layers. The last Uc layer of this version, recognition layer, consists of 24 planes of $5{\times}5$ cells which tell us the identity of a grapheme receiving attention at one time and its relative position in the input layer respectively. It has been trained 10 simple vowel graphemes and 14 simple consonant graphemes and their spatial features. Some patterns which are not easily trained have been trained more extrensively. The trained nerwork which can classify indivisual graphemes with possible deformation, noise, size variance, transformation or retation wre then used to recongnize Korean syllabic characters using its selective attention mechanism for image segmentation task within a syllabic characters. On initial sample tests on input characters our model could recognize correctly up to 79%of the various test patterns of handwritten Korean syllabic charactes. The results of this study indeed show Neocognitron as a powerful model to reconginze deformed handwritten charavters with big size characters set via segmenting its input images as recognizable parts. The same approach may be applied to the recogition of chinese characters, which are much complex both in its structures and its graphemes. But processing time appears to be the bottleneck before it can be implemented. Special hardware such as neural chip appear to be an essestial prerquisite for the practical use of the model. Further work is required before enabling the model to recognize Korean syllabic characters consisting of complex vowels and complex consonants. Correct recognition of the neighboring area between two simple graphemes would become more critical for this task.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.763-774
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• 2020

Wind data forecasted from the numerical weather prediction (NWP) model is generally used as the first-guess of the target tracking process to obtain the atmospheric motion vectors(AMVs) because it increases tracking accuracy and reduce computational time. However, there is a contradiction that the NWP model used as the first-guess is used again as the reference in the AMVs verification process. To overcome this problem, model-independent first guesses are required. In this study, we propose the AMVs derivation from Lucas and Kanade optical flow method and then using it as the first guess. To retrieve AMVs, Himawari-8/AHI geostationary satellite level-1B data were used at 00, 06, 12, and 18 UTC from August 19 to September 5, 2015. To evaluate the impact of applying the optical flow method on the AMV derivation, cross-validation has been conducted in three ways as follows. (1) Without the first-guess, (2) NWP (KMA/UM) forecasted wind as the first-guess, and (3) Optical flow method based wind as the first-guess. As the results of verification using ECMWF ERA-Interim reanalysis data, the highest precision (RMSVD: 5.296-5.804 ms^-1) was obtained using optical flow based winds as the first-guess. In addition, the computation speed for AMVs derivation was the slowest without the first-guess test, but the other two had similar performance. Thus, applying the optical flow method in the target tracking process of AMVs algorithm, this study showed that the optical flow method is very effective as a first guess for model-independent AMVs derivation.

• Journal of dental hygiene science
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• v.14 no.2
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• pp.158-166
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• 2014

This study is trying to grasp the stress of the male high school students and the correlation between the stress according to the oral health important cognitive and self-rated oral health status and number of brushing, emphasizing the need for the education of oral health important, providing the basic data in order to accomplish correctly until the enhance of oral health-related quality of the oral health correct behavior. From May to July 2013, a self administered survey was conducted by the selected by convenience sampling from subjects of two high school located in Chungcheongnam-do 1, 2 grade. The SPSS PASW Statistics 18.0 and Amos 5.0 program had been used for the statistical data analysis. The study results were as follow: 1) Among five areas of stress, the stress of school life was the highest as 2.11 points and the stress of home problem was the lowest as 1.51 points; 2) The significance analysis results between the five areas of stress according to the stress of latent variable and the oral health-related quality of life all showed the significant difference (p<0.001). 3) Oral health-related quality of life was higher as oral health important and self-rated oral health status positive. Furthermore oral health-related quality of life was higher as number of brushing increased; 4) Fit Measures test result of stress, academic level, and family economic level model all showed more than 0.9 in goodness of fit index (GFI), adjusted GFI, normed fit index and root mean square residual and root mean square error of approximation values is all estimated less than 0.1, so it showed good model. From this study, it can be concluded that there is the correlation between stress and oral health-related quality of life.

• The Journal of Engineering Geology
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• v.26 no.3
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• pp.383-392
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• 2016

This study is to evaluate the physical and mechanical properties on the Ipseok-dae columnar joints of Mt. Mudeung National Park. For these purposes, physical and mechanical properties as well as discontinuity property on the Mudeungsan tuff, measurement of vibration and local meteorology around columnar joints, and ground deformation by self-weight of columnar joints were examined. For the physical and mechanical properties, average values were respectively 0.65% for porosity, 2.69 for specific gravity, 2.68 g/cm³ for density, and 2411 m/s for primary velocity, 323 MPa for uniaxial compressive strength, 81 GPa Young's modulus, and 0.25 for Poisson's ratio. For the joint shear test, average values were respectively 3.15 GPa/m for normal stiffness, 0.38 GPa/m for shear stiffness, 0.50 MPa for cohesion, and 35° for internal friction angle. The JRC standard and JRC chart was in the range of 4~6, and 1~1.5, respectively. The rebound value Q of silver schmidt hammer was 57 (≒ 90 MPa). It corresponds 20% of the uniaxial compressive strength of intact rock. The maximum vibration value around the Ipseok=dae columnar joints was in the range of 0.57 PPV (mm/s)~2.35 PPV (mm/s). The local meteorology of surface temperature, air temperature, humidity, and wind on and around columnar joints appeared to have been greatly influenced the weather on the day of measurement. For the numerical analysis of ground deformation due to its self-weight of the Ipseok-dae columnar joints, the maximum displacement of the right ground shows when the ground distance is approximately 2 m, while drastically decreased by 2~4 m, thereafter was insignificant. The maximum displacement of the middle ground shows when the ground distance is approximately 0~2 m, while drastically decreased by 3~10 m, thereafter was insignificant. The maximum displacement of the left ground shows when the ground distance is approximately 5~6 m, while drastically decreased by 6~10 m, thereafter was insignificant.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.35-39
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• 2010

Purpose: The aim of this study was to investigate distribution of particle size in phytate kit and compare filtered method with non-filtered method using 200 nm filter for sentinel lymphoscintigraphy (SLS). Materials and Methods: Five phytate kit of having the same available period was measured by particle size analyzer. For in-vivo experiment, $^{99m}Tc$-phytate was injected intradermally at both foot to perform lymphoscintigraphy. Imaging was acquired at 1hour after injection. Region of interest (ROI) was drawn in inguinal and background area for analysis. RAW 264.7 cells (Murine macrophage cell) were prepared for measurement of celluar uptake as a representative of macrophages. Paired t-test was performed using SPSS (SPSS Inc, USA) for statistical analysis. Results: The size of most particle in Techne phytate kit was distributed in 130~650 nm(90.5 %). In-vivo study, the ROI analysis showed similar result between filtered and non-filtered sample, and the numerical value of count/pixel were $58.3{\pm}5.97$ and $60.2{\pm}4.88$. In-vitro study, cellular uptake study also showed no difference between filtered and non-filtered sample by gamma counting. Conclusion: The present study demonstrates that there was no meaning of 200 nm filtered method for SLS using $^{99m}Tc$-phytate.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.83-93
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• 2002

To improve the performance of estimation, the research that uses additional information addition to traffic count and target OD with additional survey cost have been studied. The purpose of this paper is to improve the performance of OD estimation by reducing the feasible solutions with cost-efficiently additional information addition to traffic counts and target OD. For this purpose, we Propose the OD estimation method with sample link use proportion as additional information. That is, we obtain the relationship between OD trip and link flow from sample link use proportion that is high reliable information with roadside survey, not from the traffic assignment of target OD. Therefore, this paper proposes OD estimation algorithm in which the conservation of link flow rule under the path-based non-equilibrium traffic assignment concept. Numerical result with test network shows that it is possible to improve the performance of OD estimation where the precision of additional data is low, since sample link use Proportion represented the information showing the relationship between OD trip and link flow. And this method shows the robust performance of estimation where traffic count or OD trip be changed, since this method did not largely affected by the error of target OD and the one of traffic count. In addition to, we also propose that we must set the level of data precision by considering the level of other information precision, because "precision problem between information" is generated when we use additional information like sample link use proportion etc. And we Propose that the method using traffic count as basic information must obtain the link flow to certain level in order to high the applicability of additional information. Finally, we propose that additional information on link have a optimal counting location problem. Expecially by Precision of information side it is possible that optimal survey location problem of sample link use proportion have a much impact on the performance of OD estimation rather than optimal counting location problem of link flow.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.461-470
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• 2019

This study was carried out to quantify the drought stress in grafted watermelon seedlings non-destructively by using chlorophyll fluorescence (CF) imaging technique rather than the visual judgment. Six-day old watermelon seedlings were grown under uniform irrigation for 3 days, and then given drought stress. Afterward, the sensor for the measurement of water content in plug tray cell unit was used to classify the drought-stress level into nine groups from D1 (53.0%, sufficient moisture state) to D9 (15.7%, extremely dry stress), and the 16 CF parameters were measured. In addition, re-irrigation was performed on the drought stressed seedlings(D5 - D9) to determine the growth and photosynthesis recovery level, which was not confirmed by visual judgment. The kinetic curve patterns of CF in three different drought stressed seedling groups were found to be different for the early detection of drought stress. All the 16 CF parameters decreased continuously with exposure to drought stress and drastically decreased from D5 (32.1%) where the visual judgment was possible. The fluorescence decline ratio (Rfd_Lss) started to decrease from the initial drought stress level (D5 - D6), and the Maximum PSII quantum yield (Fv/Fm) was significantly decreased in the later extreme drought stress range (D7 - D9) by re-irrigation recovery test. Thus, Rfd_Lss and Fv/Fm parameters were finally selected as potent indicators of growth and photosynthesis recovery in the initial and later stages of drought stress. Also, to the differences in the numerical values of the individual chlorophyll fluorescence parameters, the drought stress level was intuitively confirmed through the image. These results indicate that Rfd and Fv/Fm can be considered as potential CF parameters for the detection of low and extremely high drought stress, respectively. Furthermore, Fv/Fm can be considered as the best CF parameters for recovery at re-irrigation.