• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.18 no.3
• /
• pp.1-11
• /
• 2015

This research was conducted to compare the effect of soil amendment and loess on physial and chemical properties of dredged soil and primary height growth of Ulmus davidiana var. japonica. Three types of research plots: control plot (Dredged soil only), DC treatment plot (Dredged soil + soil amendment) and DCL treatment plot (Dredged soil + soil amendment + Loess) were set at Okgu research site in Saemanguem. 32 trees of U. davidiana var. japonica were planted in each plots after 14 months from the construction. Soil texture, pH, electrical conductivity (EC), organic matter (OM), total nitrogen (TN), available P, exchangeable cation ($K^+$, $Na^+$, $Mg^{2+}$, $Ca^{2+}$) and sodium chloride were measured after 3 years from the construction. Also, survival rate and height of U. davidiana var. japonica were measured 22 months after planting, and the correlation between height of trees and the physico-chemical properties of soil were analyzed. Even though pH in both DC and DCL treatment plots are lower than control plot, they are still alkaline (> pH 8). OM, TN and available P in both DC and DCL treatment were higher than the control. Particularly, the content of available P in both DC and DCL treatment plots are 1.4~5.1 times and 2.0~3.1 times higher than the control respectively. The concentration of exchangeable Mg in DCL treatment plot was 1.1~5.5 times higher than the control (p < .05). The survival rate of the species was the highest in DCL treatment plot (98%) followed by DC treatment plot and the control. The average height of the trees in both DC and DCL treatment plots is 1.1m while the control is 0.8m. OM, TN, available P, K+ were significantly related to the height of U. davidiana var. japonica(p < .01). The results indicate that soil amendment affects on soil physial and chemical properties of dredged soil and height growth of U. davidiana var. japonica.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
• /
• v.46 no.3
• /
• pp.191-196
• /
• 2020

Objectives: Beyond the original application approved by the U.S. Food and Drug Administration, recombinant human bone morphogenetic protein-2 (rhBMP-2) is used for medication-related osteonecrosis of the jaw (MRONJ) treatment because of its bone remodeling enhancement properties. The purpose of the study was to investigate the bone formation effect of rhBMP-2/absorbable collagen sponge (ACS) in patients with MRONJ. Materials and Methods: In this retrospective cohort study, 26 female patients diagnosed with MRONJ and who underwent mandibular sequestrectomy at Ajou University Dental Hospital from 2010 to 2018 were included. The experimental group was composed of 18 patients who received rhBMP-2/ACS after sequestrectomy, while the control group was composed of 8 patients who did not receive rhBMP-2/ACS after sequestrectomy. A total dose of 0.5 mg of rhBMP-2 was used in the experimental group at a concentration of 0.5 mg/mL. Follow-up panoramic X-rays were taken immediately after the surgery and more than 6 months after the surgery. Using those X-rays, a radiographic index of bone defect area was calculated using the modified Ihan Hren method, which measures radiographic density of the normal bone and the defect site. Results: This study suggests that rhBMP-2 contributes to new bone formation. The mean radiographic index immediately after surgery and more than 6 months after the surgery for the experimental group was 68.4% and 79.8%, respectively. The mean radiographic index immediately after surgery and more than 6 months after the surgery for the control group was 73.4% and 76.7%, respectively (Wilcoxon signed rank test, P>0.05). The mean radiographic index increased 11.4% in the experimental group and 3.27% in the control group (Mann-Whitney U-test, P<0.05). Conclusion: Based on the results, use of rhBMP-2/ACS on bone defect sites after sequestrectomy could be a successful strategy for treatment of MRONJ patients.

• Journal of the Korean Chemical Society
• /
• v.54 no.2
• /
• pp.208-214
• /
• 2010

In the presence of alcohol, phospholipase D (PLD) is known to perform transphosphatidylation activity, during which the overall reaction rate of PLD increased. To elucidate the reaction mechanism of transphosphatidylation further, we investigated rate constants of transphosphatidylation reaction of the purified ${\alpha}$-type PLD from cabbage in the presence of various alcohols. The second-oder rate constants of PLD transphosphatidylation showed a large increase with the primary alcohols examined as expected. In the case of butanol we observed the second-oder rate constant of $33.33{\pm}1.33M^{-1}sec^{-1}$. This second-order rate constant of transphosphatidylation was as 400 times greater as the second-order hydrolysis rate constant of $0.078M^{-1}sec^{-1}$ which was adjusted for the water concentration. A linear free energy relationship between the $pK_a$ of alcohol and transphosphatidylation rate gives a Br${\o}$nsted slope of ${\beta}_{nu}$ = 0.12 ${\pm}$ 0.03. This small ${\beta}_{nu}$ value implicates that the transition state of break down of phosphatidyl-enzyme intermediate (E-P) is likely dissociative. Finally, a reaction mechanism of cabbage PLD is suggested on the basis of our results presented here and the histidine residue known to be located in the active site of cabbage PLD.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.23-45
• /
• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Journal of Korea Water Resources Association
• /
• v.49 no.6
• /
• pp.551-563
• /
• 2016

According to the 4th and 5th assessment of the Intergovernmental Panel on Climate Change (IPCC), global climate has been rapidly changing because of the human activities since Industrial Revolution. The perceived changes were appeared strongly in temperature and concentration of carbon dioxide ($CO_2$). Global average temperature has increased about $0.74^{\circ}C$ over last 100 years (IPCC, 2007) and concentration of $CO_2$ is unprecedented in at least the last 800,000 years (IPCC, 2014). These phenomena influence precipitation, evapotranspiration and soil moisture which have an important role in hydrology, and that is the reason why there is a necessity to study climate change. In this study, Asia region was selected to simulate primary energy index from 1951 to 2100. To predict future climate change effect, Common Land Model (CLM) which is used for various fields across the world was employed. The forcing data was Representative Concentration Pathway (RCP) data which is the newest greenhouse gas emission scenario published in IPCC 5th assessment. Validation of net radiation ($R_n$), sensible heat flux (H), latent heat flux (LE) for historical period was performed with 5 flux tower site-data in the region of AsiaFlux and the monthly trends of simulation results were almost equaled to observation data. The simulation results for 2006-2100 showed almost stable net radiation, slightly decreasing sensible heat flux and quite increasing latent heat flux. Especially the uptrend for RCP 8.5 has been about doubled compared to RCP 4.5 and since late 2060s, variations of net radiation and sensible heat flux would be significantly risen becoming an extreme climate condition. In a follow-up study, a simulation for energy index and hydrological index under the detailed condition will be conducted with various scenario established from this study.

• Journal of Radiation Protection and Research
• /
• v.36 no.2
• /
• pp.71-78
• /
• 2011

Yeong-Gwang N.P.P Private Environment Supervisory Organization analyzed over 3,000 samples including 10 marine and 24 land samples from the year 2,000 to 2009. According to the results of the analysis, artificial nuclides that resulted from the effect of Yeong-Gwang Nuclear Power Plant operations were not detected in most samples. However, from the rain and seawater samples, which were taken from inside the plants such as the intake, the discharge and the observatory, $^3H$ was detected although it was below the regulation level. The $^3H$ concentration detected in the rain taken from the observatory, by the yearly average criterion, was 30.5~40.0 $Bq{\cdot}L^{-1}$, which is around 20 times the $^3H$ concentration detected in the surroundings of the power plants, but it is 0.1% of the regulation level of 40,000 $Bq{\cdot}L^{-1}$. Also, $^3H$ concentration detected in the seawater taken from the intake and the discharge, by the yearly average criterion, was 2.75~17.8$Bq{\cdot}L^{-1}$, which means the concentration detected in the discharge is about 140~280% higher than that detected in the intake except the year 2006. Based on these results, it was determined that, although lower than the regulation level, the $^3H$ in gas and liquid form detected in the rain and seawater sampled from the observatory and the discharge was released into the environment from the power plants. Therefore, regular monitoring and analysis is required on the level of $^3H$ in the observatory and the discharge.

• Journal of Korean Society of Environmental Engineers
• /
• v.37 no.5
• /
• pp.253-261
• /
• 2015

In this study, Chlorophyll-a (chl-a) prediction model and multiple parameters affecting algae occurrence in Mulgeum site were evaluated by statistical analysis using water quality, hydraulic and climate data at Mulgeum site (1998~2008). Before the analysis, control chart method and effect period of typhoon were adopted for improving reliability of the data. After data preprocessing step two methods were used in this study. In method 1, chl-a prediction model was developed using preprocessed data. Another model was developed by Method 2 using significant parameters affecting chl-a after data preprocessing step. As a result of correlation analysis, water temperature, pH, DO, BOD, COD, T-N, $NO_3-N$, $PO_4-P$, flow rate, flow velocity and water depth were revealed as significant multiple parameters affecting chl-a concentration. Chl-a prediction model from Method 1 and 2 showed high $R^2$ value with 0.799 and 0.790 respectively. Validation for each prediction model was conducted with the data from 2009 to 2010. Training period and validation period of Method 1 showed 20.912 and 24.423 respectively. And Method 2 showed 21.422 and 26.277 in each period. Especially BOD, DO and $PO_4-P$ played important role in both model. So it is considered that analysis of algae occurrence at Mulgeum site need to focus on BOD, DO and $PO_4-P$.

• Journal of Korean Society of Forest Science
• /
• v.105 no.3
• /
• pp.294-302
• /
• 2016

This study was conducted to evaluate aboveground tree biomass and nutrient (C, N, P, K, Ca, and Mg) response of tree components by high (1,933 trees $ha^{-1}$) and low (1,200 tree $ha^{-1}$) stand densities in a 27-year-old Quercus glauca plantation. The study site was located in Goseong county, Gyeongsangnam-do, southern Korea. Total 12 trees (6 high and 6 low stand densities) were cut to develop allometric equations and to measure nutrient concentration of tree components. Stand density-specific allometric equations in the high and low stand densities were significant (P < 0.05) in tree components with diameter at breast height (DBH). Also, generalized allometric equations could be applied to estimate tree biomass regardless of the difference of stand density because of no significant effect on slope of stand density-specific allometric equations. Aboveground tree biomass estimated by the allometric equations was significantly higher in the high stand density (177 Mg $ha^{-1}$) than in the low stand density (114 Mg $ha^{-1}$). However, nutrient concentration of tree components was not significantly affected by the difference of stand density. Nutrient stocks in tree components were not significantly between the high stand density and the low stand density, except for the N and P stocks of stem wood. These results indicate that aboveground tree biomass could be significantly affected by stand density, but nutrient concentration among the tree components was not affected by the difference of stand density in a Quercus glauca plantation.

• Applied Chemistry for Engineering
• /
• v.27 no.1
• /
• pp.92-100
• /
• 2016

Low-temperature conversion of nitrogen oxides using plasma-assisted hydrocarbon selective catalytic reduction of (HC-SCR) was investigated. Plasma was created in the catalyst-packed bed so that it could directly interact with the catalyst. The effect of the reaction temperature, the shape of catalyst, the concentration of n-heptane as a reducing agent, the oxygen content, the water vapor content and the energy density on $NO_x$ removal was examined. $NO_x$ conversion efficiencies achieved with the plasma-catalytic hybrid process at a temperature of $250^{\circ}C$ and an specific energy input (SIE) of $42J\;L^{-1}$ were 83% and 69% for one-dimensional Ag catalyst ($Ag\;(nanowire)/{\gamma}-Al_2O_3$) and spherical Ag catalyst ($Ag\;(sphere)/{\gamma}-Al_2O_3$), respectively, whereas that obtained with the catalyst-alone was considerably lower (about 30%) even with $Ag\;(nanowire)/{\gamma}-Al_2O_3$ under the same condition. The enhanced catalytic activity towards $NO_x$ conversion in the presence of plasma can be explained by the formation of more reactive $NO_2$ species and partially oxidized hydrocarbon intermediates from the oxidation of NO and n-heptane under plasma discharge. Increasing the SIE tended to improve $NO_x$ conversion efficiency, and so did the increase in the n-heptane concentration; however, a further increase in the n-heptane concentration beyond $C_1/NO_x$ ratio of 5 did not improve the $NO_x$ conversion efficiency any more. The increase in the humidity affected negatively the $NO_x$ conversion efficiency, resulting in lowering the $NO_x$ conversion efficiency at the higher water vapor content, because water molecules competed with $NO_x$ species for the same active site. The $NO_x$ conversion efficiency increased with increasing the oxygen content from 3 to 15%, in particular at low SIE values, because the formation of $NO_2$ and partially oxidized hydrocarbon intermediates was facilitated.

• Economic and Environmental Geology
• /
• v.40 no.2 s.183
• /
• pp.209-221
• /
• 2007

Numerical analysis was performed to investigate the effect of heavy metal contamination on neighboring environment in case a dam is constructed by using rockfill materials contaminated by heavy metals. The numerical simulation carried out in this research includes both subsurface flow and contaminant transport in the inside of the CFRD(Concrete Faced Rockfill Dam), using two commercial programs, SEEP2D and FEMWATER. The three representative cases of scenarios were chosen to consider a variety of cases occurring in a dam site; (1) Scenario 1 : no crack in the concrete face slab, (2) Scenario 2 : a crack In the upper part of face slab, and (3) Scenario 3 : a crack between plinth and face slab in the lower part of face slab. As a result of seepage analysis, the amount of seepage in scenario 2 was calculated as $14.31\sim14.924m^3/day$ per unit width, corresponding to the 1,000 times higher value than that in other scenarios. Also, in the simulation of contaminant transport by using FEMWATER, specified contaminant concentration of 13 ppb in main rockfill zone was set to consider continuous leakage from the rock materials. Through the analysis of contaminant transport, we found that elapsed times to take for the contaminant concentration of about 2 ppb to arrive at the end of a dam are as follows. Scenario 1 has the elapsed time of 55,000 years. In Scenario 2. it is 50 years. Finally, scenario 3 has 27,000 years. The rapid transport of the contaminant in scenario 2 was attributed to greater seepage flow by 500 times than other scenarios. Although, in case of upper crack in the face slab, it was identified that the contaminant might transport to the end of a dam within 100 years with about 2 ppb concentration, however, it happened that the contaminant was hardly transported out of the dam in other scenarios, which correspond to either no crack or a crack between plinth and face slab. In conclusion, the numerical analysis showed that the alternative usage of the contaminated sand and gravel as the dam embankment material can be one of the feasible methods with the assumption that the cracks in a face slab could be controlled adequately.