• Journal of The Korean Society of Grassland and Forage Science
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• v.19 no.2
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• pp.115-120
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• 1999

This experiment was carried out to investigate the effects of additives on the quality of alfalfa(Medicago sativa L.) silage at the forage experimental field, National Livestock Research Institute, RDA, Suwon in 1996. The experiment was arranged in a randomized block design with three replications. The treatments consisted of different additives(control, formic acid, molasses, inoculant A and inoculant B). Crude protein(CP) and Nitrogen free extract(NFE) content of alfalfa silage with additives were higher compared with those obtained control, but Crude ash(CA) and Crude fiber(CF) content of control(11.5 and 39.6%) were higher than those of additive treated plots. ADF and NDF contents of control silage were the highest as 36.2 and 48.6%, respectively, and increased by 4% compared with those obtained before ensiling. The acidity(pH) of control was the highest(5.45), but the lowest in inoculant A(4.32). Inoculant teratment significantly reduced acidity of silage compared with control. DM content of control silage was the lowest but DM loss of control silage was higher than that of additive treated silage. Ammonia-N content was the highest at formic acid treatment and level of Lactobacillus was decreased at control and formic acid treated silage. Total organic acid and lactic acid content of inoculant A and inoculant B were higher than those of other treated plots. The results of this study indicate that the treatment of LAB(Lactic acid bacteria) could be recommended as producing high quality of alfalfa silage.

• Radiation Oncology Journal
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• v.17 no.1
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• pp.43-51
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• 1999

Purpose : To discuss the technical aspect of interstitial brachytherapy including method of implant, insertion time of radioactive source, total radiation dose, and complication, we reviewed patients who had diagnoses of soft tissue sarcoma and were treated by conservative surgery, interstitial implant and external beam radiation therapy Materials and Methods : Between May 1995 and Dec. 1997, ten patients with primary or recurrent soft tissue sarcoma underwent surgical resection (wide margin excision) and received radiotherapy including interstitial brachytherapy. Catheters were placed with regular intervals of 1 ~l.5 cm immediately after tumor removal and covering the critical structures, such as neurovascular bundle or bone, with gelform, muscle, or tissue expander in the cases where the tumors were close to those structures. Brachytherapy consisted of high dose rate, iridium-192 implant which delivered 12~15 Gy to 1 cm distance from the center of source axis with 2~2.5 Gy/fraction, twice a day, starting on 6th day after the surgery, Within one month after the surgery, total dose of 50~55 Gy was delivered to the tumor bed with wide margin by the external beam radiotherapy. Results : All patients completed planned interstitial brachytherapy without acute side effects directly related with catheter implantation such as infection or bleeding. With median follow up duration of 25 months (range 12~41 months), no local recurrences were observed. And there was no severe form of chronic complication (RTOGIEORTC grade 3 or 4). Conclusion : The high dose rate interstitial brachytherapy is easy and safe way to minimize the radiation dose delivered to the adjacent normal tissue and to decrease radiation induced chronic morbidity such as fibrosis by reducing the total dose of external radiotherapy in the management of soft tissue sarcoma with conservative surgery.

• Journal of Chest Surgery
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• v.31 no.7
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• pp.679-683
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• 1998

From June 1995 to May 1997, we have implanted 52 Sorin Bicarbon mechanical valves in 41 patients. They were 16 men and 25 women, and their mean age was 47.4${\pm}$14.8(range; 18∼74 y.o.). 35(27 mm∼31 mm) were in mitral position, 15(19 mm∼25 mm) in aortic position, and 2(31 mm) in tricuspid position. 3 CABGs and a tumor excision were taken concomittantly. 35 patients were primary operation, and 6 were re-do operations. By intraoperative transesophageal doppler echocardiography, transvalvular peak/mean pressure gradient was 6.1${\pm}$2.7/2.4${\pm}$1.4 mmHg in mitral position and 27.6/10.7 mmHg in aortic position. The effective valve opening area in mitral position was 3.2${\pm}$0.6 cm2. Follow-up was total 508.6 patient-months, and mean follw-up was 12.7${\pm}$9.2 months. NYHA class was improved from 2.6${\pm}$0.6 to 1.2${\pm}$0.3 in average postoperatively. During that period, there was no operative death. 2 late non-valve related deaths were occurred. One was died of COPD, and the other was possible acute myocardial infarction. Among 7 postoperative complications, one valve related complication(minimal paravalvular leakage) was noticed. In conclusion, Sorin Bicarbon mechanical valve is believed one of the safe choice in clinical settings. It showed excellent hemodynamic and mechanical functions, and very low postoperative valve related complications in short term clinical experience.

• Journal of the korean academy of Pediatric Dentistry
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• v.34 no.1
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• pp.91-98
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• 2007

The aim of this study was to examine the difference of the depth of sedation using the Bispectral index assessment with and without the added submucosal Midazolam to oral Chloral hydrate and Hydroxyzine for pediatric patients. Twenty seven sedation cases were performed in this study Selection criteria included good health(ASA I), 2 to 6 years of age, the need for sedation to receive dental treatment including anesthesia, and restorative procedure over at least two teeth. Patients were randomly classified into one group taking oral Chloral hydrate(60 mg/kg) and Hydroxyzine(1 mg/kg) and the other group recieving Chloral hydrate(60 mg/kg), Hydroxyzine(1 mg/kg) and submucosal Midazolam(0.1 mg/kg). Nitrous Oxide(50%) was used for both group during sedation. Patients were monitored using a pulse oximeter and a Bispectral monitor. A behavior scale was rated as quiet(Q), crying(C), movement(M), or struggling(S) every 2 minutes watching a recorded videotape. Analysis showed a significant difference in mean Bispectral index and SD during sedation across two groups(P<0.001). The group of patients injected with submucosal Midazolam in addition to oral Chloral hydrate and Hydroxyzine showed a lower mean Bispectral index and a narrower SD. PR and SpO2 for both groups remained within the normal values. Submucosal Midazolam improved the sedation quality by deepening sedation depth without compromising safety and enabled the sedation pattern to be kept more stable.

• Food Science and Preservation
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• v.19 no.3
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• pp.376-384
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• 2012

This study was conducted to investigate the food purchasing management of school food services. The subjects consisted of 271 school dietitians in the Daegu and Gyeongbuk area. The percentages of ready-to-use vegetables actually being used were as follows: root of balloon flowers, 88.4%; garlic, 87.8%; blanched bracken, 80.1%; raw lotus root, 65.7%; burdock, 63.5%; small green onion, 63.5%; stem of taro, 57.6%; ginger, 35.1%; radish root, 30.6%; blanched asterscaber, 29.2%; large type welsh onion, 25.8%; carrot, 25.5%; onion, 21.4%; and potato, 8.9%. The percentages of HACCP-certified products being used were as follows: meat, 75.9%; eggs, 66.7%; soybean curds, 65.5%; ready-to-use seafood, 55.1%; starch jellies, 49.9%; spice, 44.9%; kimchi, 30.9%; ready-to-use vegetables, 22.7%; and fruits, 6.9%. The percentages of environment-friendly food items being used were as follows: eggs, 31.0%; meat, 28.7%; soybean curds, 22.1%; and fruits, 17.7%. Of these food items, meat and ready-to-use seafood were being used the most in the elementary schools. The percentages of imported food items being used were as follows: starch jelly, 29.2%; ready-to-use seafood, 24.7%; soybean curds, 20.5%; spice, 15.9%; and fruits, 10.1%. The food items requiring HACCP certification were as follows: beef and pork, 81.5%; chicken, 80.1%; ready-to-use seafood, 78.6%; frozen dumplings, 73.8%; soybean curds, 71.6%; peeled eggs, 70.8%; fish paste, 69.4%; starch jelly, 65.7%; milk, 63.1%; kimchi, 54.6%; spice, 50.6%; frozen noodle, 45.4%; ready-to-use vegetables, 44.3%; and bean sprouts, 29.5%. It was confirmed that 8.1% of the sanitation monitoring results were intentionally misreported. Therefore, to supply good and safe foods to schools, active management is needed in schools and food manufacturing and delivery companies.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.1-11
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• 2023

This study intended to develop a technique for quantitatively and 3-dimensionally predicting the potential failure zone and impulse that may occur when trees are fall down. The main outcomes of this study are as follows. First, this study established the potential failure zone and impulse calculation formula in order to quantitatively calculate the risks generated when trees are fallen down. When estimating the potential failure zone, the calculation was performed by magnifying the height of trees by 1.5 times, reflecting the likelihood of trees falling down and slipping. With regard to the slope of a tree, the range of 360° centered on the root collar was set in the case of trees that grow upright and the range of 180° from the inclined direction was set in the case of trees that grow inclined. The angular momentum was calculated by reflecting the rotational motion from the root collar when the trees fell down, and the impulse was calculated by converting it into the linear momentum. Second, the program to calculate a potential failure zone and impulse was developed using Rhino3D and Grasshopper. This study created the 3-dimensional models of the shapes for topography, buildings, and trees using the Rhino3D, thereby connecting them to Grasshopper to construct the spatial information. The algorithm was programmed using the calculation formula in the stage of risk calculation. This calculation considered the information on the trees' growth such as the height, inclination, and weight of trees and the surrounding environment including adjacent trees, damage targets, and analysis ranges. In the stage of risk inquiry, the calculation results were visualized into a three-dimensional model by summarizing them. For instance, the risk degrees were classified into various colors to efficiently determine the dangerous trees and dangerous areas.

• Journal of the Korean Orthopaedic Association
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• v.54 no.2
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• pp.127-132
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• 2019

Purpose: The aim of this study was to determine if preoperative temporary discontinuation of antiplatelet medication (aspirin, clopidogrel, or cilostazol) is a safe procedure that does not increase early postoperative bleeding and allogenic blood transfusion after a total knee arthroplasty. Materials and Methods: A retrospective analysis was conducted among consecutive patients who underwent navigation assisted primary total knee arthroplasty performed by a single surgeon, from January 2013 to December 2016. A total of 369 patients enrolled in this study were divided into two groups, 271 patients with no history of antiplatelet therapy and 98 patients who underwent 7 days of temporary withdrawal of antiplatelet therapy. Comparative analysis between the two groups, on the variation of hemoglobin and hematocrit during the first and second postoperative days, was conducted to determine the amount of early postoperative bleeding and the frequency of allogenic blood transfusion during hospitalization. Results: The variation of hemoglobin, hematocrit during the first and second postoperative days and the frequency of allogenic blood transfusion between no history of antiplatelet medication and discontinuation antiplatelet medication before 7 days from surgery were similar in both groups. Of the 369 patients, 149 patients received a blood transfusion during their hospitalization. Compared to patients who did not receive a blood transfusion, those who did received blood transfusion were significantly older in age, smaller in height, lighter in weight, and showed significantly lower preoperative hemoglobin and hematocrit values. No statistically significant differences in sex, preoperative American Society of Anesthesiologists scores, and the history of antiplatelet medication until 7 days prior to surgery were observed between the two groups according to blood transfusion. Conclusion: Compared to patients with no history of antiplatelet medication, the temporary discontinuation of antiplatelet medication 7 days prior to surgery in patients undergoing antiplatelet medication did not increase the amount of postoperative bleeding or the need for allogenic blood transfusion.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.