• Korean Journal of Heritage: History & Science
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• v.55 no.1
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• pp.151-174
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• 2022

According to the "Special Act on the Restoration and Maintenance of the Core Relics of the Shilla Kingdom" enacted in 2019, the Shilla Kingdom refers to the capital of Shilla and Unified Shilla period, and refers to Gyeongju, where the king lived, and the nearby area. Shilla Wanggyeong is a heritage registered on the UNESCO World Heritage List in 2000 under the name of Gyeongju Historic Site and belongs to Wolseong District, Hwangnyongsa District, and Daeneungwon District among the five districts registered as Gyeongju Historic Site. Unlike the Namsan and Sanseong districts, the Shilla Kingdom is a heritage consisting mostly of archaeological sites without physical substance. Gyeongju City sought to promote local tourism while providing more direct experiences to visitors by restoring the heritage that constitutes the Shilla Kingdom. Starting with the restoration of Woljeonggyo Bridge in 2005, the Shilla Wanggyeong restoration project began in earnest. Gyeongju City tried to restore the building site on the west side of Donggung Palace and Wolji after Woljeonggyo Bridge, but it was canceled due to opposition from the UNESCO World Heritage Committee. The World Heritage Committee opposed the restoration and recommended a heritage impact assessment for similar projects in the future. During the miscarriage impact assessment procedure, there is an OUV attribute analysis process of the heritage to be evaluated. This study intends to preemptively derive OUV attributes for the Silla Kingdom through literature and overseas case analysis. In the case of literature research, domestic and foreign research data related to the UNESCO World Heritage Convention and World Heritage Management were examined, and in overseas cases, the architectural works of Krakow Historical District, Stonehenge and Abbury Geoseok Ruins in England, and Le Corbusier were analyzed. Through this, the outstanding universal value attributes of the Silla Kingdom were derived. This study is expected to be used as a reference in the process of restoration projects of other heritage constituting the Shilla Kingdom or construction plans in nearby areas in the future and serve as an indicator to improve the management system of the Shilla Kingdom more efficiently from the perspective of world heritage.

• Fisheries and Aquatic Sciences
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• v.26 no.12
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• pp.738-751
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• 2023

The Sembilan Archipelago is famous for its great biodiversity, in which the humphead wrasse (Cheilinus undulatus) (locally named Napoleon fish) is the primary commodity (economically important), and currently, the environmental degradation occurs due to anthropogenic activities. This study aimed to examine the eco-environmental parameters and assess their influence on the abundance of humphead wrasse and other coral reef fish compositions in the Sembilan Archipelago. Direct field monitoring was performed using a visual census throughout an approximately one km transect. Coral cover data collection and assessment were also carried out. A coastal water quality index (CWQI) was used to assess the water quality status. Furthermore, statistical-based analyses [hierarchical clustering, Pearson's correlation, principal component analysis (PCA), and canonical correspondence analysis (CCA)] were performed to examine the correlation between eco-environmental parameters. The Napoleon fish was only found at stations 1 and 2, with a density of about 3.8 Ind/ha, aligning with the dominant composition of the family Serranidae (covering more than 15% of the total community) and coinciding with the higher coral mortality and lower reef fish abundance. The coral reef conditions were generally ideal for supporting marine life, with a living coral percentage of about > 50% in all stations. Based on CWQI, the study area is categorized as good and excellent water quality. Of the 60 parameter values examined, the phytoplankton abundance, Napoleon fish, and temperature are highly correlated, with a correlation coefficient value greater than 0.7, and statistically significant (F < 0.05). Although the adaptation of reef fish to water quality parameters varies greatly, the most influential parameters in shaping their composition in the study area are living corals, nitrites, ammonia, larval abundance, and temperature.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• Progress in Medical Physics
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• v.25 no.3
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• pp.143-150
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• 2014

In general radiotherapy, mega-voltage (MV) x-ray images are widely used as the unique method to verify radio-therapeutic fields. But, the image quality of MV images is much lower than that of kilo-voltage x-ray images due to scatter interactions. Since 1990s, studies for the scatter correction have performed with digital-based MV imaging systems. In this study, a novel method for the scatter correction is suggested using scatter to primary ratio (SPR), instead of conventional methods such as digital image processing or scatter kernel calculations. We measured two MV images with and without a solid water phantom describing a patient body with given imaging conditions, and calculated un-attenuated ratios. Then, we obtained SPR distributions for the scatter correction. For experimental validation, a line-pair (LP) phantom using several Al bars and a clinical pelvis MV image was used. As the result, scatter signals of the LP phantom image were successfully reduced so that original density distribution of the phantom was restored. Moreover, image contrast values increased after SPR correction at all ROIs of the clinical image. The mean value of increases was 48%. The SPR correction method suggested in this study has high reliability because it is based on actually measured data. Also, this method can be easily adopted in clinics without additional cost. We expected that the SPR correction can be an effective method to improve the quality of MV image guided radiotherapy.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.81-94
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• 2006

The water quality impacts of forest fragmentation at the Doam-dam watershed were evaluated in this study. For this ends, the watershed scale model, Soil and Water Assessment Tool (SWAT) model was utilized. To exclude the effects of different magnitude and patterns in weather, the same weather data of 1985 was used because of significant differences in precipitation in year 1985 and 2000. The water quality impacts of forest fragmentation were analyzed temporarily and spatially because of its nature. The flow rates for Winter and Spring has increased with forest fragmentations by $8,366m^3/month$ and $72,763m^3/month$ in the S1 subwatershed, experiencing the most forest fragmentation within the Doam-dam watershed. For Summer and Fall, the flow rate has increased by $149,901m^3/month$ and $107,109m^3/month$, respectively. It is believed that increased flow rates contributed significant amounts of soil erosion and diffused nonpoint source pollutants into the receiving water bodies. With the forest fragmentation in the S1 watershed, the average sediment concentration values for Winter and Spring increased by 5.448mg/L and 13.354mg/L, respectively. It is believed that the agricultural area, which were forest before the forest fragmentation, are responsible for increased soil erosion and sediment yield during the spring thaw and snow melts. For Spring and Fall, the sediment concentration values increased by 20.680mg/L and 24.680mg/L, respectively. Compared with Winter and Spring, the increased precipitation during Summer and Fall contributed more soil erosion and increased sediment concentration value in the stream. Based on the results obtained from the analysis performed in this study, the stream flow and sediment concentration values has increased with forest fragmentation within the S1 subwatershed. These increased flow and soil erosion could contribute the eutrophication in the receiving water bodies. This results show that natural functionalities of the forest, such as flood control, soil erosion protection, and water quality improvement, can be easily lost with on-going forest fragmentation within the watershed. Thus, the minimize the negative impacts of forest fragmentation, comprehensive land use planning at watershed scale needs to be developed and implemented based on the results obtained in this research.

• Journal of Nutrition and Health
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• v.53 no.3
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• pp.271-287
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• 2020

Purpose: Variations in the iodine contents of foods is critical for estimating the iodine intake. This study aimed to update the iodine database of common Korean foods and evaluated the iodine intake in Korean adults. Methods: A list of 855 Korean foods was selected for the updated iodine database. The updated database was established with Version 1 and 2 by applying an average or minimum value for the imputed values. The iodine intake was estimated in 5,927 Korean adults using the data from the 2013-2015 Korea National Health and Nutrition Examination Survey. Results: The analytical values in the updated database were 166 (19.4%), followed in order by 318 (37.2%), 247 (28.9%), and 124 (14.5%) for the adapted, imputed, and missing values, respectively. The median of dietary iodine intake was 352.1 ㎍/day (± 2,166.1) and 343.4 ㎍/day (± 2,161.9) in Version 1 and 2 among the total population. The contribution rates of each food group to the iodine intake were 55.7% for seaweeds, which showed a similar trend in Version 2. When subjects were divided by consumption of seaweeds, the median iodine intake was 495.7 ㎍ in the consumer group, which was almost double (241.2 ㎍) that of the non-consumer group. The proportion of subjects who consumed below the Estimated Average Requirement of iodine was 11.0% in the non-consumer group. In contrast, 11.6% in the consumer group of seaweed consumed above the Upper Level of iodine. When the dietary iodine and urinary iodine were examined, the regression coefficient was 0.11718 in Version 1 and 0.11512 in Version 2 after adjusting for age and sex. Conclusion: This study presented the variation of iodine intake in Korean adults by applying different versions of the iodine database. As the iodine intake can vary due to the highly variable concentrations in the major food sources, an iodine database is necessary to be monitored, and caution should be taken when the database is used in research.

• Journal of Life Science
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• v.28 no.7
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• pp.795-801
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• 2018

This study was conducted to investigate the association of single nucleotide polymorphism (SNP) markers on equine chromosomes (ECA) 3 and 9 with body weight in Jeju horses. We used DNA samples and body weight data of 320 horses provided by the Livestock Promotion Agency, Jeju Special Self-Governing Province, and the Korean Racing Association, respectively. We genotyped all the experimental animals using nine SNP markers located on ECA 3 (BIEC2-808466, BIEC2-808543, BIEC2-808967, and BIEC2-809370) and ECA 9 (BIEC2-1105370, BIEC2-1105372, BIEC2-1105377, BIEC21105505, and BIEC2-1105840). These markers were selected due to their effects on body conformation traits in horses. The joint effect of the genotypes of the two SNP markers (BIEC2-808467 and BIEC2-1105377) regarding body weight were also evaluated. The estimated breeding value (EBV) of body weight was obtained as the dependent variable for association analyses using a linear mixed model. Significant associations were detected between SNP markers (BIEC2-808543, BIEC2-808967, BIEC2-809370, BIEC2-1105370, BIEC2-1105372, and BIEC2-1105377) and the body weight EBV. In addition, the joint genotype effect of the BIEC2-808467 and BIEC2-1105377 on the body weight EBV was significant. These results indicate that the SNP markers, which showed their significant effects on body conformation, can be used as genetic markers to improve the efficiency of the selective breeding program for the body weight traits in Jeju horses.

• Korean Journal of Food Science and Technology
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• v.33 no.4
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• pp.437-443
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• 2001

Gastrodia elata blume (GEB) is considered to be a useful herbal medicine in oriental countries for the treatment of headache, migraine, dizziness, childhood convulsion, epilepsy, rheumatism, hypertension, neuralgia and neurological disorders. This study was carried out to investigate the quality of bread added with the powder of GEB. The possibility of GEB wheat flour mixture as bread was studied by adding 0%, 0.5%, 1.0%, 1.5%, 2.0% of GEB powder to wheat flour. In Farinograph data, the dough stability decreased with the increase of GEB powder. Granular size of starches ranged from $36\;{\mu}m\;to\;60{\mu}m$, and the shape of them showed a long oval figure. Amylograph showed that the increase in the ratio of GEB on the doughs slightly elevated in the maximum viscosity. The loaf volume of 0.5% powder increased by 10.2% but that of 2.0% decreased by 16.8%. The moisture content was 43.57% in the control but it increased as the powder addition. The colors of crust and crumb were not significantly different among L, b and ${\Delta}E$, but 'a' value in crumb was increased as the powder addition. The addition of the powder had no significant effect on bread texture. In sensory evaluation, the moistness increased as the increase of the powder addition. The control bread was most excellent, and the bread made by mixing additives were better than just 0.5% GEB-wheat flour in terms of quality.

• The Journal of Korean Academy of Prosthodontics
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• v.48 no.4
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• pp.280-286
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• 2010

Purpose: This study evaluated the detorque values of screws in a multiple implant-supported superstructure using stone casts made with 2 different impression techniques. Material and methods: A fully edentulous mandibular master model and a metal framework directly connected to four implants (Br${\aa}$nemark $System^{(R)}$; Nobel Biocare AB) with a passive fit to each other were fabricated. Six experimental stone casts (Group 1) were made with 6 non-splinted impressions on a master cast and another 6 experimental casts (Group 2) were made with 6 acrylic resin splinted impressions. The detorque values of screws ($TorqTite^{(R)}$ GoldAdapt Abutment Screw; Nobel Biocare AB) were measured twice after the metal framework was fastened onto each experimental stone cast with 20 Ncm torque. Detorque values were analyzed using the mixed model with the fixed effect of screw and reading and the random effect of model for the repeated measured data at a .05 level of ignificance. Results: The mean detorque values were 7.9 Ncm (Group 1) and 8.1 Ncm (Group 2), and the mean of minimum detorque values were 6.1 Ncm (Group 1) and 6.5 Ncm (Group 2). No statistically significant differences between 2 groups were found and no statistically significant differences among 4 screws were found for detorque values. No statistically significant differences between 2 groups were also found for minimum detorque values. Conclusion: In a multiple external hexagon implant-supported prosthesis, no significant differences between 2 groups were found for detorque values and for minimum detorque values. There seems to be no significant differences in screw joint stability between 2 stone cast groups made with 2 different impression techniques.

• Journal of Preventive Medicine and Public Health
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• v.32 no.2
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• pp.177-182
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• 1999

Objectives: To reexamine the association between air pollution and daily mortality in Seoul, Korea using a method of meta-analysis with the data filed for 1991 through 1995. Methods: A separate Poisson regression analysis on each district within the metropolitan area of Seoul was conducted to regress daily death counts on levels of each ambient air pollutant, such as total suspended particulates (TSP), sulfur dioxide $(SO_2)$, and ozone $(O_3)$, controlling for variability in the weather condition. We calculated a weighted mean as a meta-analysis summary of the estimates and its standard error. Results: We found that the p value from each pollutant model to test the homogeneity assumption was small (p<0.01) because of the large disparity among district-specific estimates. Therefore, all results reported here were estimated from the random effect model. Using the weighted mean that we calculated, the mortality at a $100{\mu}g/m^3$ increment in a 3-day moving average of TSP levels was 1.034 (95% Cl 1.009-1.059). The mortality was estimated to increase 6% (95% Cl 3-10%) and 3% (95% Cl 0-6%) with each 50 ppb increase for 9-day moving average of SO2 and 1-hr maximum O3, respectively. Conclusions: Like most of air pollution epidemiologic studies, this meta-analysis cannot avoid fleeing from measurement misclassification since no personal measurement was taken. However, we can expect that a measurement bias be reduced in a district-specific estimate since a monitoring station is hefter representative cf air quality of the matched district. The similar results to those from the previous studios indicated existence of health effect of air pollution at current levels in many industrialized countries, including Korea.