• Journal of Environmental Science International
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• v.25 no.7
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• pp.1007-1016
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• 2016

Environmental policy implementation has been strengthened to protect the source waters in Korea and to improve their water quality. Increasing of non-point source caused water quality problem continuously. Research on runoff from forests, which occupy over 65% of the land in korea, is insufficient, and studies on the characteristics and influences of storm runoff are necessary. In this study, we chose to compare the effects of land use in the form of two types of forest distribution and then gathered data on storm characteristics and runoff properties during rainfall events in these areas. Furthermore, the significance and influences of the discharges were analyzed through correlation analysis, and multilateral runoff characteristics were examined by deducing a formula through $COD_{Mn}$ and TOC regression analysis. At two forest points, for which the basin areas differed from each other, flow changed according to storm quantity and intensity. The peak discharge at point A, where the basin area was big, was high, whereas water-quality fundamental items (BOD, $COD_{Mn}$, and SS) and TOC density were high at point B where the slope and storm intensity were high. Effects of dissolved organic matter were determined through correlation analysis, and the regression formulas for $COD_{Mn}$ and TOC were deduced by regression analysis. It is expected that the data from this study could be useful as basic information in establishing forest management measures.

• Journal of Korean Society of Forest Science
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• v.95 no.3
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• pp.240-249
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• 2006

Recently, dispersion of damaged forest by pine wilt disease has been regarded as a serious social issue. Damages by pine wilt disease have been spreaded by natural area expansion of the vectors in the damaged area, while the national wide damage spread has induced by human-involved carrying infected trees out of damaged area. In this study, damaged trees were detected and located on the digital map by aerial photograph and terrestrial surveys. The spatial distribution pattern of damaged trees, and the relationship of spatial distribution of damaged trees and some geomorphological factors were geostatistically analysed. Finally, we maked natural spread pattern map of pine wilt disease using geostatistical CART(Classification and Regression Trees) model. This study verified that geostatistical analysis and CART model are useful tools for understanding spatial distribution and natural spread pattern of pine wilt diseases.

• Journal of Climate Change Research
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• v.6 no.3
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• pp.185-191
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• 2015

This study presents an estimate of on-site surface fuel loadings composed of coarse woody debris (CWD) using $5^{th}$ National Forest Inventory (NFI) data in South Korea. We classified CWD data into forest type, region and decay class, and used conversion factors by decay class and tonne of oil equivalent developed in the country. In 2010, the total wildfire fuel load of CWD was estimated as 8.9 million TOE; those of coniferous, deciduous and mixed forests were 3.5 million TOE, 2.8 million TOE and 2.6 million TOE, respectively. Gangwon Province had the highest wildfire fuel load of CWD (2.3 million TOE), whereas Seoul exhibited the lowest wildfire fuel load of CWD (0.02 million TOE). Wildfire fuel loads of CWD were estimated as 2.9 million TOE, 1.9 million TOE, 2.4 million TOE and 1.7 million TOE for decay classes I, II, III and IV, respectively. The total wildfire fuel load of CWD corresponded to the calorific value of 8.2 million tons crude oil, 2.46% of that of living trees. Proportionate to the growing stock, total wildfire fuel load of CWD was in a broad distinction by region, while its TOE $ha^{-1}$ was not. This implies that there is no need to establish different guidelines by region for management of CWD. The results of this work provide a baseline study for scientific policy guidelines on preventing wildfires by proposing CWD as wildfire fuel load.

• Journal of Forest and Environmental Science
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• v.26 no.3
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• pp.149-159
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• 2010

This paper analyzes data on the composition, status, diversity, and distribution pattern of invasive forest undergrowth in a protected area (Khadimnagar National Park) of Northeastern Bangladesh. Assessment was done by means of stratified random sampling to diversify the invasive forest undergrowth species. For vegetation survey, 45 plots were taken randomly in ($2m{\times}2m$) circular plot from three topographical regions namely top of the hill, middle slope and plain land (15 plots from each region) and a total of 715 individuals, 22 invasive species belonging to 17 families were recorded from the study site. Among invasive species, shrubs constitute 10 species, herbs 9 species, and vines 3 species respectively. Mass number of invasive undergrowth species was grows in plain land (45.45%) followed by middle slope (31.82%). Based on the survey, invasive undergrowth plants of study areas were also categorized into three degrees of invasiveness e.g., highly invasive, moderately invasive and potentially invasive. Herbs, shrubs, and vines constitute the highest density at Chromolaema odorata (Linn.) King. (1.09), relative density at Chromolaema odorata (Linn.) King. 6.85%; highest and lowest frequency was calculated at Cassia alata L. (64.44%) and Diplazium esculentum (24.44%); for relative frequency the highest was Cassia alata L., which occupies 6.64%. Determination of the abundance of the different species revealed that Cassia alata L., constitutes (3.36) followed by Pteris cretica Wilsonii (3.14) of the area. The presence of invasive undergrowth species always reduced the number of associated species. Therefore, an extensive in-depth long-term investigation, proper policy formulation and management interventions and further study and continuous monitoring on their impacts need to be triggered targeting the control of the invasive undergrowth species of this protected area. In this aspect, national and international organization could help to conserve its biodiversity.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.263-268
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• 2021

The purpose of this study was to propose a model which is suitable for the actual delivery system by designing a fetal delivery hospital operation management and fetal health classification model. The number of deaths during childbirth is similar to the number of maternal mortality rate of 295,000 as of 2017. Among those numbers, 94% of deaths are preventable in most cases. Therefore, in this paper, we proposed a model that predicts the health condition of the fetus using data like heart rate of fetuses, fetal movements, uterine contractions, etc. that are extracted from the Cardiotocograms(CTG) test using a random forest. If the redundancy of the data is unbalanced, This proposed model guarantees a stable management of the fetal delivery health management system. To secure the accuracy of the fetal delivery health management system, we remove the outlier which embedded in the system, by setting thresholds for the upper and lower standard deviations. In addition, as the proportion of the sequence class uses the health status of fetus, a small number of classes were replicated by data-resampling to balance the classes. We had the 4~5% improvement and as the result we reached the accuracy of 97.75%. It is expected that the developed model will contribute to prevent death and effective fetal health management, also disease prevention by predicting and managing the fetus'deaths and diseases accurately in advance.

• Journal of Korean Society of Forest Science
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• v.105 no.2
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• pp.238-246
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• 2016

The study aims to examine Japan's National REDD+ Strategies prepared for Post-2020 and the status of its implementation by organizations in Japan, and then to suggest the potential REDD+ countermeasures against Joint Credit Mechanism (JCM) for Republic of Korea and their implications. As for the technical limitations of the guidelines of REDD+ under the JCM, it is pointed out that forests located at the place with less potential safeguard intervention tend to be selected as the target area for a project and that, as reference emission trend changes depending on the basic year of the baseline, differences could occur among the amounts of greenhouse gas emission. In addition, it is pointed out that the result of the calculation of the displacement of emissions, or leakeage, in REDD+, can have an uncertainty, since the calculation is done by just multiplying leakage area by certain coefficients, without considering the size of the leakage area. Furthermore, the lack of implementation guideline or methodologies for a project level is also pointed out as a limitation, considering that there are only some national and sub-national monitoring guidelines at present. Finally, internationally accepted guidelines for safeguard and its sub-items needed to be prepared, as current safeguard policy only includes lists without detailed items. Such things mentioned above are all related to, and can lead to the problem of double counting of items in Nested Approach etc., as well as of the distribution of credits. Therefore, Republic of Korea should take these into consideration when implementing its REDD+ projects.

• Journal of Family Resource Management and Policy Review
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• v.26 no.3
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• pp.19-34
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• 2022

There are growing concerns about debt insolvency among youth and low-income households. The deterioration in household debt quality among young people is due to a combination of sluggish employment, an increase in student loan burden and an increase in high-interest loans from the secondary financial sector. The purpose of this study was to explore the possibility of household debt default among young borrowers in Korea and to predict the factors affecting this possibility. This study utilized the 2021 Household Finance and Welfare Survey and used random forest algorithm to comprehensively analyze factors related to the possibility of default risk among young adults. This study presented the importance index and partial dependence charts of major determinants. This study found that the ratio of debt to assets(DTA), medical costs, household default risk index (HDRI), communication costs, and housing costs the focal independent variables.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.188-194
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• 2023

This study aimed to derive the basic wood density, one of several carbon emission factors, for carbon accounting of bamboo forests in Korea. Bamboo is mainly distributed in Jeollanam-do and Gyeongsangnam-do provinces, and 101 sample trees were selected for each of the three species (Phyllostachys nigra var. henonis, P. bambusoides, and P. pubescens). The basic wood density derivation used the KS F 2098 method. The measurements showed that the basic wood density was 0.83 g/cm³ for P. nigra var. henonis, 0.81 g/cm³ for P. bambusoides, and 0.72 g/cm³ for P. pubescens. However, the bamboo distribution area in Korea is not very large, and P. pubescens grows in one area only. Therefore, the basic wood density that can be applied to bamboo was 0.79 g/cm³. Evaluation of the uncertainty of the extracted basic wood density showed a very low value of 1.61%, which confirmed the reliability of the basic wood density derived from this analysis. The basic wood density, biomass expansion factor, and root-to-shoot ratio were used to calculate the carbon storage capacity of one bamboo plant and expanded to calculate the capacity for a hectare of bamboo. Carbon storage and absorption of bamboo were calculated by applying a carbon-emission factor, such as the basic wood density. These study results are expected to contribute to the carbon-neutral policy and forest management direction in Korea.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.2
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• pp.87-96
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• 2023

Recently, research on predicting the treatment results of diseases using deep learning technology is also active in the medical community. However, small patient data and specific deep learning algorithms were selected and utilized, and research was conducted to show meaningful results under specific conditions. In this study, in order to generalize the research results, patients were further expanded and subdivided to derive the results of a study predicting mortality after lung cancer diagnosis for men and women in their 80s, 90s, and 100s. Using AutoML, which provides large-scale medical information and various deep learning algorithms from the Health Insurance Review and Assessment Service, five algorithms such as Decision Tree, Random Forest, Gradient Boosting, XGBoost, and Logistic Registration were created to predict mortality rates for 84 months after lung cancer diagnosis. As a result of the study, men in their 80s and 90s had a higher mortality prediction rate than women, and women in their 100s had a higher mortality prediction rate than men. And the factor that has the greatest influence on the mortality rate was analyzed as the treatment period.

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.6
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• pp.57-65
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• 2003

This study researches attributes , behaviors , satisfaction factors and degrees of curiosity of visitors to recreational forests in the suburbs of a large city. It aims to present suggestions for urban forest development and management policy by offering basic data which help to plan, design and manage recreational forests to increase the quality of these environments. The results are as follows First, in attribute, the visiting rate of males is higher than that of females, and the main users are in their thirties and forties. Sixty percent of visitors graduated from university and their rate of employment is evenly distributed. 95 percent of visitors are residents of the metropolitan area. In terms of behavior, major visitors are family units visiting during summer seasons and for overnight stays. 75% are re-visitors. 85% of visitors came to escape the city with families and friends, keep in good health and experience nature. Second, to extract the factors affecting visitor satisfaction in recreational forests, the natural environment, facilities, and management/use systems were identified as independent variables, while subordinate satisfactions were dependent variables. so regression analysis was used. Thus, the variables affecting the natural environment are quality of water, stream use, biodiversity, fresh air and landscape factors. The variables affecting facilities are puking, convenience, play facilities, sanitary arrangement and camping. Most important among the variables affecting management/use systems are educational facilities and access condition. On the basis of generalizing the study in the existing individual site, we must verify the visiting characteristics in recreational forests in the suburbs of a large city. Since development of recreational forests is understood as a sequence considering a site and a given condition, and since management and improvement must unfold according to these characteristics, a strategy is needed to reveal visitors' opinions about the site. Depending on the facilities and service, satisfaction of recreational forests is generally influenced by social and economic qualities. Also, this study can look into the effect according to use pattern motive and season. As suburban recreational forests have many overnight-users and younger men, programs suitable for these groups are needed. On the basis of variables affecting satisfaction according to natural environment, facilities, and use system, policies which can manage the natural environment and introduce educational programs are needed.