• Korean Journal of Radiology
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• v.25 no.1
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• pp.24-32
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• 2024

Despite improvements in operative techniques and perioperative care, post-hepatectomy liver failure (PHLF) remains the most serious cause of morbidity and mortality after surgery, and several risk factors have been identified to predict PHLF. Although volumetric assessment using imaging contributes to surgical simulation by estimating the function of future liver remnants in predicting PHLF, liver function is assumed to be homogeneous throughout the liver. The combination of volumetric and functional analyses may be more useful for an accurate evaluation of liver function and prediction of PHLF than only volumetric analysis. Gadoxetic acid is a hepatocyte-specific magnetic resonance (MR) contrast agent that is taken up by hepatocytes via the OATP1 transporter after intravenous administration. Gadoxetic acid-enhanced MR imaging (MRI) offers information regarding both global and regional functions, leading to a more precise evaluation even in cases with heterogeneous liver function. Various indices, including signal intensity-based methods and MR relaxometry, have been proposed for the estimation of liver function and prediction of PHLF using gadoxetic acid-enhanced MRI. Recent developments in MR techniques, including high-resolution hepatobiliary phase images using deep learning image reconstruction and whole-liver T1 map acquisition, have enabled a more detailed and accurate estimation of liver function in gadoxetic acid-enhanced MRI.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.6
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• pp.890-896
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• 2012

This study was conducted to evaluate soil erosion risk with a standard unit watershed in the upper Upper Nakdong River Basin according to soil characteristics and landuse using the spatial soil erosion map. The study area is $3,605.6km^2$, which consists of 2 subbasins, 35 standard unit watersheds (Andong basin 18, Imha basin 17). As a evaluation of soil erosion potential using the spatial soil erosion map, total annual soil loss and soil loss per area estimated $2,013{\times}10^3Mg\;yr^{-1}$ (Andong basin 979, Imha basin 1,034) and $6.1Mg\;ha^{-1}yr^{-1}$ (Andong basin 6.0, Imha basin 5.2), respectively. 54.2% of soil loss was originated from Arable land (Andong basin 49.0%, Imha basin 59.0%), and the area of regions, graded as higher "Moderate" for annual soil loss, was $201.7km^2$ (Andong basin 84.9, Imha basin 116.8). Average soil loss per area of unit watersheds by classification according to soil dominant parent material types ranked "Sedimentary rock group" > "Mixed group" > "Metamorphic rock group" > "Igneous rock group". In conclusion, the results of this study inform that the classification of soil parent material type would be effective for soil erosion analysis and interpretation in the Upper Nakdong River Basin.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.208-220
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• 2016

Automatic Mountain Meteorology Observation System (AMOS) is an important ingredient for several climatological and forest disaster prediction studies. In this study, we select the optimal sites for AMOS in the mountain areas of Honam and Jeju in order to prevent forest disasters such as forest fires and landslides. So, this study used spatial dataset such as national forest map, forest roads, hiking trails and 30m DEM(Digital Elevation Model) as well as forest risk map(forest fire and landslide), national AWS information to extract optimal site selection of AMOS. Technical methods for optimal site selection of the AMOS was the firstly used multifractal model, IDW interpolation, spatial redundancy for 2.5km AWS buffering analysis, and 200m buffering analysis by using ArcGIS. Secondly, optimal sites selected by spatial analysis were estimated site accessibility, observatory environment of solar power and wireless communication through field survey. The threshold score for the final selection of the sites have to be higher than 70 points in the field assessment. In the result, a total of 159 polygons in national forest map were extracted by the spatial analysis and a total of 64 secondary candidate sites were selected for the ridge and the top of the area using Google Earth. Finally, a total of 26 optimal sites were selected by quantitative assessment based on field survey. Our selection criteria will serve for the establishment of the AMOS network for the best observations of weather conditions in the national forests. The effective observation network may enhance the mountain weather observations, which leads to accurate prediction of forest disasters.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.1-9
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• 2006

Regardless of the recent observed warmer winters in Korea, more freeze injuries and associated economic losses are reported in fruit industry than ever before. Existing freeze-frost forecasting systems employ only daily minimum temperature for judging the potential damage on dormant flowering buds but cannot accommodate potential biological responses such as short-term acclimation of plants to severe weather episodes as well as annual variation in climate. We introduce 'dormancy depth', in addition to daily minimum temperature, as a complementary criterion for judging the potential damage of freezing temperatures on dormant flowering buds of grape vines. Dormancy depth can be estimated by a phonology model driven by daily maximum and minimum temperature and is expected to make a reasonable proxy for physiological tolerance of buds to low temperature. Dormancy depth at a selected site was estimated for a climatological normal year by this model, and we found a close similarity in time course change pattern between the estimated dormancy depth and the known cold tolerance of fruit trees. Inter-annual and spatial variation in dormancy depth were identified by this method, showing the feasibility of using dormancy depth as a proxy indicator for tolerance to low temperature during the winter season. The model was applied to 10 vineyards which were recently damaged by a cold spell, and a temperature-dormancy depth-freeze injury relationship was formulated into an exponential-saturation model which can be used for judging freeze risk under a given set of temperature and dormancy depth. Based on this model and the expected lowest temperature with a 10-year recurrence interval, a freeze risk probability map was produced for Hwaseong County, Korea. The results seemed to explain why the vineyards in the warmer part of Hwaseong County have been hit by more freeBe damage than those in the cooler part of the county. A dormancy depth-minimum temperature dual engine freeze warning system was designed for vineyards in major production counties in Korea by combining the site-specific dormancy depth and minimum temperature forecasts with the freeze risk model. In this system, daily accumulation of thermal time since last fall leads to the dormancy state (depth) for today. The regional minimum temperature forecast for tomorrow by the Korea Meteorological Administration is converted to the site specific forecast at a 30m resolution. These data are input to the freeze risk model and the percent damage probability is calculated for each grid cell and mapped for the entire county. Similar approaches may be used to develop freeze warning systems for other deciduous fruit trees.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.63-77
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• 2022

Our aim was to reduce estimation errors of a wind velocity model used as an early warning system for weather risk management in the agricultural sector. The Rural Development Administration (RDA) agricultural weather observation network's wind velocity data and its corresponding estimated data from January to December 2020 were used to calculate linear regression equations (Y = aX + b). In each linear regression, the wind estimation error at 87 points and eight time slots per day (00:00, 03:00, 06:00, 09.00, 12.00, 15.00, 18.00, and 21:00) is the dependent variable (Y), while the estimated wind velocity is the independent variable (X). When the correlation coefficient exceeded 0.5, the regression equation was used as the wind velocity correction equation. In contrast, when the correlation coefficient was less than 0.5, the mean error (ME) at the corresponding points and time slots was substituted as the correction value instead of the regression equation. To enable the use of wind velocity model at a national scale, a distribution map with a grid resolution of 250 m was created. This objective was achieved b y performing a spatial interpolation with an inverse distance weighted (IDW) technique using the regression coefficients (a and b), the correlation coefficient (R), and the ME values for the 87 points and eight time slots. Interpolated grid values for 13 weather observation points in rural areas were then extracted. The wind velocity estimation errors for 13 points from January to December 2019 were corrected and compared with the system's values. After correction, the mean ME of the wind velocities reduced from 0.68 m/s to 0.45 m/s, while the mean RMSE reduced from 1.30 m/s to 1.05 m/s. In conclusion, the system's wind velocities were overestimated across all time slots; however, after the correction model was applied, the overestimation reduced in all time slots, except for 15:00. The ME and RMSE improved b y 33% and 19.2%, respectively. In our system, the warning for wind damage risk to crops is driven by the daily maximum wind speed derived from the daily mean wind speed obtained eight times per day. This approach is expected to reduce false alarms within the context of strong wind risk, by reducing the overestimation of wind velocities.

• Progress in Medical Physics
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• v.25 no.2
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• pp.79-88
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• 2014

The dose distributions within the real volumes of tumor targets and critical organs during internal target volume-based intensity-modulated radiation therapy (ITV-IMRT) for liver cancer were recalculated by applying the effects of actual respiratory organ motion, and the dosimetric features were analyzed through comparison with gating IMRT (Gate-IMRT) plan results. The ITV was created using MIM software, and a moving phantom was used to simulate respiratory motion. The doses were recalculated with a 3 dose-volume histogram (3DVH) program based on the per-field data measured with a MapCHECK2 2-dimensional diode detector array. Although a sufficient prescription dose covered the PTV during ITV-IMRT delivery, the dose homogeneity in the PTV was inferior to that with the Gate-IMRT plan. We confirmed that there were higher doses to the organs-at-risk (OARs) with ITV-IMRT, as expected when using an enlarged field, but the increased dose to the spinal cord was not significant and the increased doses to the liver and kidney could be considered as minor when the reinforced constraints were applied during IMRT plan optimization. Because the Gate-IMRT method also has disadvantages such as unsuspected dosimetric variations when applying the gating system and an increased treatment time, it is better to perform a prior analysis of the patient's respiratory condition and the importance and fulfillment of the IMRT plan dose constraints in order to select an optimal IMRT method with which to correct the respiratory organ motional effect.

• Tuberculosis and Respiratory Diseases
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• v.73 no.5
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• pp.258-265
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• 2012

Background: Vitamin D can translocate a vitamin D receptor (VDR) from the nucleus to the cell membranes. The meaning of this translocation is not elucidated in terms of a role in pathogenesis of chronic obstructive pulmonary disease (COPD) till now. VDR deficient mice are prone to develop emphysema, suggesting that abnormal function of VDR might influence a generation of COPD. The blood levels of vitamin D have known to be well correlated with that of lung function in patients with COPD, and smoking is the most important risk factor in development of COPD. This study was performed to investigate whether cigarette smoke extracts (CSE) can inhibit the translocation of VDR and whether mitogen activated protein kinases (MAPKs) are involved in this inhibition. Methods: Human alveolar basal epithelial cell line (A549) was used in this study. 1,25-$(OH_2)D_3$ and/or MAPKs inhibitors and antioxidants were pre-incubated before stimulation with 10% CSE, and then nucleus and microsomal proteins were extracted for a Western blot of VDR. Results: Five minutes treatment of 1,25-(OH2)D3 induced translocation of VDR from nucleus to microsomes by a dose-dependent manner. CSE inhibited 1,25-$(OH_2)D_3$-induced translocation of VDR in both concentrations of 10% and 20%. All MAPKs inhibitors did not suppress the inhibitory effects of CSE on the 1,25-$(OH_2)D_3$-induced translocation of VDR. Quercetin suppressed the inhibitory effects of CSE on the 1,25-$(OH_2)D_3$-induced translocation of VDR, but not in n-acetylcysteine. Conclusion: CSE has an ability to inhibit vitamin D-induced VDR translocation, but MAPKs are not involved in this inhibition.

• Journal of Environmental Health Sciences
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• v.41 no.6
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• pp.449-457
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• 2015

Objectives: In Korea, the system of management of medical waste largely relies on the incineration method. Our study aimed to identify any regional imbalances between the generation and treatment of medical waste, and provide reference data for future policy in Korea. Methods: We analyzed data on the amount of medical waste from 2,000 hospitals in 2012, 2013, and 2014 obtained from the Korea Environment Corporation. In the Arc GIS program (version 10.2.3), the addresses of hospitals and incinerators were transformed into map coordinates. The amount of waste generated by each hospital and the amount incinerated were represented by density and size of a triangle symbol, respectively. Results: As of 2014, the total amount of medical waste from the top 2,000 hospitals was 136,073 tons, out of which about half (49%) was generated in the capital area. Eleven incineration companies (three in the capital area, two in the Chungcheong Provinces area, one in the Jeolla Provinces area, and five in the Gyeongsang Provinces area) treated this waste. For the years 2012, 2013, and 2014, about 60% of the medical waste generated from the hospitals in the capital area was treated within the capital area and about 40% was transported to other areas, especially the Gyeongsang Provinces area, for treatment. On the other hand, about 90% of the medical waste incinerated in the capital area originated from the capital area. Conclusion: Our results suggest a spatial imbalance between the generation and treatment of medical waste in Korea and warrants multilateral policies, including the expansion of on-site treatment, strengthening regulation of the containment of medical wastes, promoting reductions in medical waste and more.

• Journal of Dental Anesthesia and Pain Medicine
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• v.19 no.6
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• pp.353-360
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• 2019

Background: Controlled hypotension (CH) provides a better surgical environment and reduces operative time. However, there are some risks related to organ hypoperfusion. The EV1000/FloTrac system can provide continuous cardiac output monitoring without the insertion of pulmonary arterial catheter. The present study investigated the efficacy of this device in double jaw surgery under CH. Methods: We retrospectively reviewed the medical records of patients who underwent double jaw surgery between 2010 and 2015. Patients were administered conventional general anesthesia with desflurane; CH was performed with remifentanil infusion and monitored with an invasive radial arterial pressure monitor or the EV1000/FloTrac system. We allocated the patients into two groups, namely an A-line group and an EV1000 group, according to the monitoring methods used, and the study variables were compared. Results: Eighty-five patients were reviewed. The A-line group reported a higher number of failed CH (P = 0.005). A significant correlation was found between preoperative hemoglobin and intraoperative packed red blood cell transfusion (r = 0.525; P < 0.001). In the EV1000 group, the mean arterial pressure (MAP) was significantly lower 2 h after CH (P = 0.014), and the cardiac index significantly decreased 1 h after CH (P = 0.001) and 2 h after CH (P = 0.007). Moreover, venous oxygen saturation (ScVO₂) decreased significantly at both 1 h (P = 0.002) and 2 h after CH (P = 0.029); however, these values were within normal limits. Conclusion: The EV1000 group reported a lower failure rate of CH than the A-line group. However, EV1000/FloTrac monitoring did not present with any specific advantage over the conventional arterial line monitoring when CH was performed with the same protocol and same mean blood pressure. Preoperative anemia treatment will be helpful to decrease intraoperative transfusion. Furthermore, ScVO₂ monitoring did not present with sufficient benefits over the risk and cost.