• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.103-116
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• 2008

In this study, in-situ testing method, Dynamic Cone Penetration Test(DCPT) was presented to establish a new compaction control criteria with using mechanical property like elastic modulus instead of unit weight for field compaction control. Soil chamber tests and in-situ tests were carried out to confirm DCPT tests can predict the designed elastic modulus after field compaction, and correlation analysis among the DCPT, CBR and resilient modulus of sub grade were performed. Also, DCPT test spacing criteria in the construction site was proposed from the literature review. In the result of laboratory tests, Livneh's equation was the best in correlation between PR of DCPT and CBR, George and Pradesh's equation was the best in the predicted resilient modulus. In the resilient modulus using FWD, Gudishala's equation estimates little larger than predicted resilient modulus and Chen's equation estimates little smaller. And KICT's equation estimates the modulus smaller than predicted resilient modulus. But using the results of laboratory resilient modulus tests considering the deviatoric and confining stress from the moving vehicle, the KICT's equation was the best. In the results of In-situ DCPT tests, the variation of PR can occur according to size distribution of penetrate points. So DCPT test spacing was proposed to reduce the difference of PR. Also it was shows that average PR was different according to subgrade materials although the subgrade was satisfied the degree of compaction. Especially large sized materials show smaller PR, and it is also found that field water contents have influence a lot of degree of compaction but a little on the average PR of the DCPT tests.

• Progress in Medical Physics
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• v.26 no.2
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• pp.87-92
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• 2015

The gated RapidArc may produce a dosimetric error due to the stop-and-go motion of heavy gantry which can misalign the gantry restart position and reduce the accuracy of important factors in RapidArc delivery such as MLC movement and gantry speed. In this study, the effect of stop-and-go motion in gated RapidArc was analyzed with varying gating window time, which determines the total number of stop-and-go motions. Total 10 RapidArc plans for treatment of liver cancer were prepared. The RPM gating system and the moving phantom were used to set up the accurate gating window time. Two different delivery quality assurance (DQA) plans were created for each RapidArc plan. One is the portal dosimetry plan and the other is MapCHECK2 plan. The respiratory cycle was set to 4 sec and DQA plans were delivered with three different gating conditions: no gating, 1-sec gating window, and 2-sec gating window. The error between calculated dose and measured dose was evaluated based on the pass rate calculated using the gamma evaluation method with 3%/3 mm criteria. The average pass rates in the portal dosimetry plans were $98.72{\pm}0.82%$, $94.91{\pm}1.64%$, and $98.23{\pm}0.97%$ for no gating, 1-sec gating, and 2-sec gating, respectively. The average pass rates in MapCHECK2 plans were $97.80{\pm}0.91%$, $95.38{\pm}1.31%$, and $97.50{\pm}0.96%$ for no gating, 1-sec gating, and 2-sec gating, respectively. We verified that the dosimetric accuracy of gated RapidArc increases as gating window time increases and efforts should be made to increase gating window time during the RapidArc treatment process.

• Journal of Nutrition and Health
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• v.56 no.5
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• pp.554-572
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• 2023

Purpose: The purpose of the study was to analyze the priorities for educational content regarding precautions to be taken to prevent safety accidents for employees in school foodservice using the Borich priority formula and the Locus for Focus model. Methods: A survey was conducted in February 2019 on 194 employees in elementary school and 122 employees in middle- and high school foodservice in the Jeonbuk area. Demographic characteristics, status of safety accidents, safety education, and their importance and performance levels were assessed using a self-administered questionnaire. The priorities for the educational content on precautions to prevent safety accidents were based on a 3-step analysis method, including the paired sample t-test, Borich priority formula, and the Locus for Focus Model. Results: The average perceived importance of the precautions to be taken against safety accidents of employees in elementary-, middle-, and high schools was higher compared to the average performance of the employees (p < 0.001). The top priority for elementary school employees was caution against falls during the cleaning of the gas hood and the trench in the kitchen. In addition, 'awareness of chemical signs' was added as one of the top priorities of middle- and high school employees. The second highest priority items were 'do stretching', 'safely adjusting workbench height', 'keeping the right attitude', 'using assistive devices when moving heavy things', and 'checking the material safety data sheet', which were the same for all elementary, middle- and high school employees. Conclusion: Thus, to improve the educational preparedness of employees in the area of safety precautions, eight safety/accident prevention items should be included in the safety education program.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• The Journal of Bigdata
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• v.4 no.2
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• pp.1-12
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• 2019

As Artificial Intelligence (AI) technology develops, it is applied to various fields such as image, voice, and text. AI has shown fine results in certain areas. Researchers have tried to predict the stock market by utilizing artificial intelligence as well. Predicting the stock market is known as one of the difficult problems since the stock market is affected by various factors such as economy and politics. In the field of AI, there are attempts to predict the ups and downs of stock price by studying stock price patterns using various machine learning techniques. This study suggest a way of predicting stock price patterns based on the Convolutional Neural Network(CNN) among machine learning techniques. CNN uses neural networks to classify images by extracting features from images through convolutional layers. Therefore, this study tries to classify candlestick images made by stock data in order to predict patterns. This study has two objectives. The first one referred as Case 1 is to predict the patterns with the images made by the same-day stock price data. The second one referred as Case 2 is to predict the next day stock price patterns with the images produced by the daily stock price data. In Case 1, data augmentation methods - random modification and Gaussian noise - are applied to generate more training data, and the generated images are put into the model to fit. Given that deep learning requires a large amount of data, this study suggests a method of data augmentation for candlestick images. Also, this study compares the accuracies of the images with Gaussian noise and different classification problems. All data in this study is collected through OpenAPI provided by DaiShin Securities. Case 1 has five different labels depending on patterns. The patterns are up with up closing, up with down closing, down with up closing, down with down closing, and staying. The images in Case 1 are created by removing the last candle(-1candle), the last two candles(-2candles), and the last three candles(-3candles) from 60 minutes, 30 minutes, 10 minutes, and 5 minutes candle charts. 60 minutes candle chart means one candle in the image has 60 minutes of information containing an open price, high price, low price, close price. Case 2 has two labels that are up and down. This study for Case 2 has generated for 60 minutes, 30 minutes, 10 minutes, and 5minutes candle charts without removing any candle. Considering the stock data, moving the candles in the images is suggested, instead of existing data augmentation techniques. How much the candles are moved is defined as the modified value. The average difference of closing prices between candles was 0.0029. Therefore, in this study, 0.003, 0.002, 0.001, 0.00025 are used for the modified value. The number of images was doubled after data augmentation. When it comes to Gaussian Noise, the mean value was 0, and the value of variance was 0.01. For both Case 1 and Case 2, the model is based on VGG-Net16 that has 16 layers. As a result, 10 minutes -1candle showed the best accuracy among 60 minutes, 30 minutes, 10 minutes, 5minutes candle charts. Thus, 10 minutes images were utilized for the rest of the experiment in Case 1. The three candles removed from the images were selected for data augmentation and application of Gaussian noise. 10 minutes -3candle resulted in 79.72% accuracy. The accuracy of the images with 0.00025 modified value and 100% changed candles was 79.92%. Applying Gaussian noise helped the accuracy to be 80.98%. According to the outcomes of Case 2, 60minutes candle charts could predict patterns of tomorrow by 82.60%. To sum up, this study is expected to contribute to further studies on the prediction of stock price patterns using images. This research provides a possible method for data augmentation of stock data.

• Progress in Medical Physics
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• v.22 no.3
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• pp.107-116
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• 2011

Respiratory gated radiation therapy and stereotactic body radiation therapy require identical tumor motions during each treatment with the motion detected in treatment planning CT. Therefore, this study developed a tumor motion monitoring and analysis system during the treatments employing RPM data, gated setup OBI images and a data analysis software. A respiratory training and guiding program which improves the regularity of breathing was used to patients. The breathing signal was obtained by RPM and the recorded data in the 4D console was read after treatment. The setup OBI images obtained gated at 0% and 50% of breathing phases were used to detect the tumor motion range in crenio-caudal direction. By matching the RPM data recorded at the OBI imaging time, a factor which converts the RPM motion to the tumor motion was computed. RPM data was entered to the institute developed data analysis software and the maximum, minimum, average of the breathing motion as well as the standard deviation of motion amplitude and period was computed. The computed result is exported in an excel file. The conversion factor was applied to the analyzed data to estimate the tumor motion. The accuracy of the developed method was tested by using a moving phantom, and the efficacy was evaluated for 10 stereotactic body radiation therapy patients. For the sine wave motion of the phantom with 4 sec of period and 2 cm of peak-to-peak amplitude, the measurement was slightly larger (4.052 sec) and the amplitude was smaller (1.952 cm). For patient treatment, one patient was evaluated not to qualified to SBRT due to the usability of the breathing, and in one patient case, the treatment was changed to respiratory gated treatment due the larger motion range of the tumor than treatment planed motion. The developed method and data analysis program was useful to estimate the tumor motion during treatment.

• Korean Security Journal
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• no.24
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• pp.53-66
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• 2010

This study aims to analyze kinematic variables regarding lateral break-fall quantitatively that can protect the body, prevent the injury and minimize the impact. To this end, three Hapkido, judo athletes of H University with experience of over 5 years were selected. Test was conducted through three dimensional image analysis by checking the time and order the subjects reach a mat. In this study, lateral break-fall was repeated five times and among them, the best movement was selected. The picture shot with high-speed camera was analyzed by using KWON3D ver. 3.1 program through three dimensional coordinate calculation based on DLT method and smoothing process of data. Study results were as follows. 1. With respect to time variables shown in lateral break-fall of A, B, C athletes, there is small difference in temporal variables and in the order the body reaches a mat. With respect to average value, hand is ($0.94{\pm}0.20$), elbow ($0.97{\pm}0.17$), hip ($0.97{\pm}0.18$), back ($0.98{\pm}0.18$), and shoulder ($1.04{\pm}0.16$). Time variable the body reaches a mat in lateral break-fall is in hand, elbow, hip, back and shoulder. 2. With respect to moving distance variables shown in lateral break-fall of A, B, C athletes, hand is ($34.33{\pm}34.59$), elbow ($52.00{\pm}26.06$), hip ($70.00{\pm}15.72$), back ($153.67{\pm}17.93$), and should ($130.67{\pm}29.02$). The fact that this study contributed to improving security martial arts technique and protecting the body by understanding the principle of lateral break-fall movement is of significance. In addition, the fact that this study provided systematic basic data for improving security martial arts technique is significant.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.1
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• pp.16-25
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• 2012

To calculate the total mass flux that change in dry and flood season in the Yeomha Channel of Gyeonggi Bay, the 13 hour bottom tracking observation was performed from the southern extremity. The value of the total mass flux(Lagrange flux) was calculated as the sum of the Eulerian flux value and stroke drift value and the tidal residual flow was harmonically analyzed through the least-squares method. Moreover, the average during the tidal cycle is essential to calculate the mass flux and the tidal residual flow and there is the need to equate the grid of repeatedly observed data. Nevertheless, due to the great differences in the studied region, the number of vertical grid tends to change according to time and since the horizontal grid differs according to the transport speed of the ship as a characteristic of the bottom tracking observation, differences occur in the horizontal and vertical grid for each hour. Hence, the present study has vertically and horizontally normalized(sigma coordinate) to equate the grid per each hour. When compared to the z-level coordinate system, the Sigma coordinate system was evaluated to have no irrationalities in data analysis with 5% of error. As a result of the analysis, the tidal residual flow displayed the flow pattern of sagging in the both ends in the main waterway direction of dry season. During flood season, it was confirmed that the tidal residual flow was vertical 2-layer flow. As a result of the total mass flux, the ebb properties of 359 cm/s and 261 cm/s were observed during dry and flood season, respectively. The total mass flux was moving the intertidal region between Youngjong-do and Ganghwa-do.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.61-71
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• 2020

Purpose: To investigate the effect of collimator angle on plan quality of PAN-Pelvis Multi-isocenter VMAT plan, dose reproducibility at the junction and impact on set-up error at the junction. Material and method: 10 adult patients with whole pelvis cancer including PAN were selected for the study. Using Trubeam STx equipped with HD MLC, we changed the collimator angle to 20°, 30°, and 45° except 10° which was the default collimator angle in the Eclipse(version 13.7) and all other treatment conditions were set to be the same for each patient and four plans were established also. To evaluate these plans, PTV coverage, coverage index(CVI) and homogeneity index (HI) were compared and clinical indicators for each treatment sites in normal tissues were analyzed. To evaluate dose reproducibility at the junction, the absolute dose was measured using a Falmer type ionization chamber and dose changes at the junction were evaluated by moving the position of the isocenter in and out 1~3mm and setting up the virtual volume at the junction. Result: CVI mean value was PTV-45 0.985±0.004, PTV-55 0.998±0.003 at 45° and HI mean value was PTV-45 1.140±0.074, and PTV-55 1.031±0.074 at 45° which were closest to 1. V20Gy of the kidneys decreased by 9.66% and average dose of bladder and V30 decreased by 1.88% and 2.16% at 45° compared to 10° for the critical organs. The dose value at the junction of the plan and the actual measured were within 0.3% and within tolerance. At the junction, due to set-up error the maximum dose increased to 14.56%, 9.88%, 8.03%, and 7.05%, at 10°, 20°, 30°, 45°, and the minimum dose decreased to 13.18%, 10.91%, 8.42%, and 4.53%, at 10°, 20°, 30°, 45° Conclusion: In terms of CVI, HI of PTV and critical organ protection, overall improved values were shown as the collimator angle increased. The impact on set-up error at the junction by collimator angle decreased as the angle increased and it will help improve the anxiety about the set up error. In conclusion, the collimator angle should be recognized as a factor that can affect the quality of the multi-isocenter VMAT plan and the dose at the junction, and be careful in setting the collimator angle in the treatment plan.