• The Journal of Korean Society for Radiation Therapy
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• v.29 no.1
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• pp.37-48
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• 2017

Purpose: The most basic conditions of radiation therapy is to prevent unnecessary exposure of normal tissue. The risk factors that are important o evaluate the dose emitted to the lung and heart from radiation therapy for breast cancer. Therefore, comparing the dose factors of a normal tissue according to the radion treatment position and Seeking an effective radiation treatment for breast cancer through the analysis of the correlation relationship. Materials and Methods: Computed tomography was conducted among 30 patients with left breast cancer in supine and prone position. Eclipse Treatment Planning System (Ver.11) was established by computerized treatment planning. Using the DVH compared the incident dose to normal tissue by position. Based on the result, Using the SPSS (ver.18) analyzed the dose in each normal tissue factors and Through the correlation analysis between variables, independent sample test examined the association. Finally The HI, CI value were compared Using the MIRADA RTx (ver. ad 1.6) in the supine, prone position Results: The results of computerized treatment planning of breast cancer in the supine position were V20, $16.5{\pm}2.6%$ and V30, $13.8{\pm}2.2%$ and Mean dose, $779.1{\pm}135.9cGy$ (absolute value). In the prone position it showed in the order $3.1{\pm}2.2%$, $1.8{\pm}1.7%$, $241.4{\pm}138.3cGy$. The prone position showed overall a lower dose. The average radiation dose 537.7 cGy less was exposured. In the case of heart, it showed that V30, $8.1{\pm}2.6%$ and $5.1{\pm}2.5%$, Mean dose, $594.9{\pm}225.3$ and $408{\pm}183.6cGy$ in the order supine, prone position. Results of statistical analysis, Cronbach's Alpha value of reliability analysis index is 0.563. The results of the correlation analysis between variables, position and dose factors of lung is about 0.89 or more, Which means a high correlation. For the heart, on the other hand it is less correlated to V30 (0.488), mean dose (0.418). Finally The results of independent samples t-test, position and dose factors of lung and heart were significantly higher in both the confidence level of 99 %. Conclusion: Radiation therapy is currently being developed state-of-the-art linear accelerator and a variety of treatment plan technology. The basic premise of the development think normal tissue protection around PTV. Of course, if you treat a breast cancer patient is in the prone position it take a lot of time and reproducibility of set-up problems. Nevertheless, As shown in the experiment results it is possible to reduce the dose to enter the lungs and the heart from the prone position. In conclusion, if a sufficient treatment time in the prone position and place correct confirmation will be more effective when the radiation treatment to patient.

• The Journal of the Korea Contents Association
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• v.14 no.6
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• pp.367-384
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• 2014

This study addresses an empirical issue which has been received little attention in the contemporary finance literature: To identify any financial determinants of the profitability indices for the firms belonging to the Korean chaebol. Three hypotheses of concern were postulated and tested for the sample firms covering the periods of the pre-and post-financial global crises. Regarding the results on the 1st hypothesis test of characterizing any financial profiles for the firms (belonging to the chaebols) by estimating a legitimate panel data model: the present study found the statistically significant relationships of the explanatory variables (BVLEVl, MVLEVl, MV/BV, RISK, FCFF and FOS) with the book-value based profitability ratio: while the market-valued profitability index was explained only by BVLEV2. Regarding the 2nd hypothesis test for the profitability of the sample firms at the industry level: the chaebol firms in the chemical and the food industries overall positioned themselves into the top ranks in order, which was tested by the ANCOVA and the Tukey multiple comparison procedure. Finally: on the 3rd hypothesis test for the 'adjusted' Dupont system, only two such as the 'operating margin' and the 'asset turnover' showed their significant effects between the chaebol firms and their counterparts in both the (parametric) independent samples t-test and the (nonparametric) Wilcoxon-Mann-Whitney statistics.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.574-583
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• 2021

Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

• Journal of Environmental Impact Assessment
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• v.15 no.1
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• pp.1-12
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• 2006

Changes in the soil physical property and the topographic condition derived from agricultural activities like as farming activities, land clearance and cutting down resulted in environmental and economic problems including the outflow of nutrient from farms and the water pollution. Several theories on the soil conservation have been developed and reviewed to protect soil erosion in the regions having a high risk of erosion. This study was done using the USLE model developed by Wischmeier and Smith (1978), and model for the slope length and steepness made by Desmet and Govers (1996), and Nearing (1997) to evaluate the potential of the soil erodibility. Therefore, several results were obtained as follows. First, factors affecting the soil erosion based on the USLE could be extracted to examine the erosion potential in farms. Soil erodibility (K), slope length (L), and slope steepness (S) were used as main factors in the USLE in consideration of the soil, not by the land use or land cover. Second, the soil erodibility increased in paddy soils where it is low in soil content, and the very fine sandy loam exists. Analysis of the slope length showed that the value of a flat ground was 1, and the maximum value was 9.17 appearing on the steep mountain. Soil erodibility showed positive relationship to a slope. Third, the potential soil erodibility index (PSEI) showed that it is high in the PSEI of the areas of steep upland and orchard on the slope of mountainous region around Dokjigol mountain, Dunji mountain, and Deummit mountain. And the PSEI in the same land cover was different depending on the slope rather than on the physical properties in soil. Forth, the analysis of land suitability in soil erosion explained that study area had 3,672.35ha showing the suitable land, 390.88ha for the proper land, and 216.54ha for the unsuitable land. For unsuitable land, 8.71ha and 6.29ha were shown in fallow uplands and single cropping uplands, respectively.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.10 no.2
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• pp.179-184
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• 2007

Purpose: Obesity has recently emerged as a significant health problem in the pediatric population, and the prevalence of non-alcoholic fatty liver disease is increasing in tandem with a significant rise in childhood obesity. Therefore, this study was conducted to clarify the risk factors of non-alcoholic steatohepatitis in obese children. Methods: We enrolled 84 obese children who visited the pediatric obesity clinic at Yeung-Nam university hospital. The patients were divided into two groups based on their alanine aminotransferase (ALT) level (separated at 40 IU/L), and the mean of ages, total cholesterol levels, HDL-cholesterol levels, LDL-cholesterol levels, triglyceride (TG) levels, as well as the mean obesity index, and body fat percentage of the two groups were then compared. Results: When the mean of ages ($10.5{\pm}1.6$ vs. $10.7{\pm}2.0$ years), total cholesterol levels ($183.0{\pm}29.1$ vs. $183.7{\pm}31.3$ mg/dL), HDL-cholesterol levels ($53.0{\pm}10.2$ vs. $55.7{\pm}13.0$ mg/dL), LDL-cholesterol levels ($113.4{\pm}30.2$ vs. $113.0{\pm}30.0$ mg/dL), triglyceride levels ($99.4{\pm}62.9$ vs. $114.2{\pm}47.3$ mg/dL), obesity indexes ($44.7{\pm}12.2$ vs. $47.9{\pm}15.1%$), and body fat percentages ($32.7{\pm}5.0$ vs. $34.0{\pm}4.8%$) of group 1 (ALT${\leq}$40 IU/L) were compared with those of group 2 (ALT${\geq}$41 IU/L), no significant differences were observed (p>0.05). However, hypertriglyceridemia (TG${\geq}$110 mg/dL) was more frequent in group 2 than in group 1 (p=0.023). Conclusion: TG may be an important risk factor in non-alcoholic steatohepatitis and further study regarding the risk factors in non-alcoholic steatohepatitis is required.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.5
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• pp.94-101
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• 2021

According to the Facility Management System (FMS) operated by the Korea Authority of Land & Infrastructure Safety, it is expected that the number of aging facilities that have been in use for more than 30 years will increase rapidly to 13.9% in 2019 and 34.5% in 2929, and end up with a social problem. In addition, with the revision of "Common Application of Seismic Design Criteria" by the Ministry of Public Administration and Security in 2017, it is mandatory to re-evaluate all existing road facilities and if necessary seismic reinforcement should be done to minimize the magnitude of earthquake damage and perform normal road functions. The seismic performance management-decision support technology currently used in seismic performance management practice in Korea only determines the earthquake-resistance reinforcement priority based on the qualitative index value for the seismic performance of individual facilities. However with this practice, normal traffic functions cannot be guaranteed. A new seismic performance management decision support technology that can provide various judgment data required for decision making is needed to overcome these shortcomings and better perform seismic performance management from a road network perspective.

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.8
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• pp.1302-1310
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• 2004

The purpose of this study was to investigate whether a web-based nutrition counseling could lead to beneficial outcomes in food intake and serum lipids of patients with hyperlipidemia. Forty hyperlipidemic patients, twenty of them were hypercholesterolemia and the other twenty were hypertriglyceridemia, participated in a web-based nutrition counseling program. At the first nutrition counseling, the patients were counselled through interview and then follow up nutrition counseling was accomplished four times during eight weeks through a web-based internet program. Various markers of disease risk including anthropometric indices, food intakes and serum lipid levels were measured before and after the web-based nutrition counseling. After nutrition counseling, body mass index significantly decreased in both groups and waist to hip ratio significantly decreased in male hypercholesterolemic patients (p<0.05). Total-cholesterol decreased from 262.2 mg/dL to 234.9 mg/dL, LDL-cholesterol decreased from 186.8 mg/dL to 160.5 mg/dL in hypercholesterolemic patients, triglyceride decreased from 288.6 mg/dL to 211.9 mg/dL and total-cholesterol decreased from 217.2 mg/dL to 198.7 mg/dL in hypertriglyceridemic patients after nutrition counseling. Anthropometric value and nutrient intakes were improved after nutrition counseling. Energy, fat and saturated fatty acid intakes decreased significantly in both groups (p<0.05). Therefore, this study shows that the web-based nutrition counseling is effective in improving food habit and influences positively in serum lipid levels of the patients. In addition, these results indicate that internet presents us with potential as a new medium for nutrition counseling in informationized society.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.157-177
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• 2022

Investors are trading stocks by keeping a close watch on the order information submitted by domestic and foreign investors in real time through Limit Order Book information, so-called price current provided by securities firms. Will order information released in the Limit Order Book be useful in stock price prediction? This study analyzes whether it is significant as a predictor of future stock price up or down when order imbalances appear as investors' buying and selling orders are concentrated to one side during intra-day trading time. Using classification algorithms, this study improved the prediction accuracy of the order imbalance information on the short-term price up and down trend, that is the closing price up and down of the day. Day trading strategies are proposed using the predicted price trends of the classification algorithms and the trading performances are analyzed through empirical analysis. The 5-minute KOSPI200 Index Futures data were analyzed for 4,564 days from January 19, 2004 to June 30, 2022. The results of the empirical analysis are as follows. First, order imbalance information has a significant impact on the current stock prices. Second, the order imbalance information observed in the early morning has a significant forecasting power on the price trends from the early morning to the market closing time. Third, the Support Vector Machines algorithm showed the highest prediction accuracy on the day's closing price trends using the order imbalance information at 54.1%. Fourth, the order imbalance information measured at an early time of day had higher prediction accuracy than the order imbalance information measured at a later time of day. Fifth, the trading performances of the day trading strategies using the prediction results of the classification algorithms on the price up and down trends were higher than that of the benchmark trading strategy. Sixth, except for the K-Nearest Neighbor algorithm, all investment performances using the classification algorithms showed average higher total profits than that of the benchmark strategy. Seventh, the trading performances using the predictive results of the Logical Regression, Random Forest, Support Vector Machines, and XGBoost algorithms showed higher results than the benchmark strategy in the Sharpe Ratio, which evaluates both profitability and risk. This study has an academic difference from existing studies in that it documented the economic value of the total buy & sell order volume information among the Limit Order Book information. The empirical results of this study are also valuable to the market participants from a trading perspective. In future studies, it is necessary to improve the performance of the trading strategy using more accurate price prediction results by expanding to deep learning models which are actively being studied for predicting stock prices recently.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.10
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• pp.1545-1554
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• 2010

Korean government will set up the nationwide food safety system with strict control of hazardous nutrients like sugar, fatty acids and sodium as well as advanced nutrition education system. In addition, almost one hundred percent of school food service rate forced the government to consider more effective ways to upgrade the nutritional status of school meals. The object of our study was to provide the data on content and consumption of sugar in school meal for the nationwide project. For this purpose, we surveyed the sugar content of 842 school meal menus and their intake level for 154 days in 8 schools in Daejeon and Chungcheong Province. Sugar contents, the sum of the quantity of 5 sugars commonly detected in food, were analysed with HPLC-RID (Refractive Index Detector). Sugar intakes were calculated by multiplying the intake of each menu to the sugar content of that menu. The sugar content was highest in the desserts, which include fruit juices, dairy products and fruits. Sugar content of side dish was high in sauces and braised foods. Sugar intake from one dish is high in beverage and dairy product, and one dish meals contribute greatly to sugar intake because of their large amount of meal intake. The average lunch meal intakes of second grade and fifth grade elementary school students were 244 g/meal and 304 g/meal, respectively. The meal intake of middle school student was 401 g/meal. The average sugar intake from one day school lunch was 4.22 g (4.03 g on elementary and 5.31 g on middle school student), which is less than 10% of daily sugar reference value for Koreans. The result of this study provides exact data of sugar intake pattern based on the content of sugar which is matched directly to the meals consumed by the students.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.