• Radiation Oncology Journal
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• v.15 no.2
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• pp.129-136
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• 1997

Purpose : We analyzed the survival and failure patterns of cervix cancer patients treated with irradiation alone to evaluate our treatment method and to compare with the others Methods and Materials : Two hundred and twenty cervical cancer patients, Stage IB, II A, and II B who completed the planned treatment between Mar 1987 and December 1991 were analyzed retrospectively. The Stage IB patients were restaged to the Stage IB1 and IB2 by the recently revised FIGO classification, Patients were treated with a combination of external irradiation and the intracavitary brachytherapy Determination of the tumor control was done at the time of 6 months Postirradiation. The follow-up time was ranged from 3 to 115 months and the mean was 62 months and the follow-up rate was $93.6\%$(206/220) Results : The overall 5-year survival rate of Stage IB1 (N=50), IB2(N: 15). II A(N=58), and II B(N=97) was $94\%,\;87\%,\;69\%,\;and\;56\%$. respectively. In the univariate analysis of prognostic factors, stage(0.00), initial Hg level (P=0.00), initial TA-4(tumor-associated) antigen level(p= 0.02), initial CEA level(p=0.02), barrel-shaped tumor(p=0.02), whole cervical involvement (0.00), pelvic tyrnphadenopathy(LAP) in CT(p=0.04), and Post-irradiation adiuvant chemotherapy(P=0.00) were statistically significant in survival analysis. In a while multivariate analysis showed that the stage was the most powerful Prognostic indicator and the Post-irradiation chemotherapy factor also showed the statistical significance. The overall local control rate was $81\%$ and by the stage, $100\%$ in Stage IBI, $86.7\%$ in Stage IBS, $84.5\%$ in Stage IIA, and $68.1\%$ in Stage IIB, respectively The overall tumor recurrence rate was $15.5\%$(27/174) and by the stage, $8\%$(4/50) in Stage IB1, $0\%$(0/l3) in Stage IB2, $22.4\%$(l1/49) in Stage II A, and $19.4\%$(12/62) in Stage II B, respectively. Conclusions : We obtained the similar treatment results to the other's ones in early stage cervical cancer patients. But in Stage II B, the local control rate was lower than that of the other institutes and also the survival was poorer. So it seems to be necessary to reevaluate the treatment method in advanced cervical cancer patients.

• The Korean Journal of Food And Nutrition
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• v.29 no.5
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• pp.610-617
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• 2016

Current study was performed to investigate the effect of morphological properties of black ginseng such as size and shape on the quality of black ginseng. The raw ginsengs were separated based on size (medium, large, and extra-large) and shape (straight ginseng, fibrous root ginseng). Subsequently, the raw ginsengs were steamed at $95^{\circ}C$ for 3 h and dried in the presence of heated air at $50^{\circ}C$ for 30 h. This process was repeated nine times for black ginseng production. The physiochemical properties such as the content of acidic polysaccharides, ginsenosides, and antioxidative activity were evaluated. Although minor difference in physiochemical properties such as acidic polysaccharide content in raw ginseng was observed, no statistical difference in the content of acidic polysaccharides, total phenols, and ginsenosides was observed during final black ginseng production based on size classification. The minor ginsenosides in fibrous root black ginseng, such as Rk3, Rh4, Rg3, Rk1, and Rg5 were higher in content than straight black ginseng. However, no correlation between the shape of ginseng and total phenol content and antioxidative activity was observed. Therefore, present results demonstrate that the difference in ginseng size in same-age and -production area does not affect the quality of black ginseng. Furthermore, difference in ginseng shape does not influence the overall quality of black ginseng. It is hypothesized that this study would be considered as supportive data for the production of high-quality black ginseng.

• Journal of Chest Surgery
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• v.36 no.11
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• pp.828-833
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• 2003

Background: It has been reported that the recently developed intermittent antegrade warm blood cardioplegia (IAWBC) has better myocardial protective effects during coronary artery bypass surgery than cold blood cardioplegia or continuos retrograde cold blood cardioplegia. The aim of this study is to evaluate the safety and usefulness of IAWBC by comparing it retrospectively with intermittent retrograde cold blood cardioplegia (lRCBC). Material and Method: From April 2001 to Feb. 2003, fifty seven patients who underwent isolated coronary surgery were divided into two groups (IAWBC vs. IRCBC). The two group had similar demographic and angiographic characteristics. There were no statistical differences in age, sex, Canadian Cardiovascular Society Functional Classification for angina, ejection fraction, and number of grafts. Result: Aortic cross clamping time and total pump time in IAWBC (99$\pm$23 and vs. 126$\pm$32 min) were shorter than those of IRCBC (118$\pm$32 min. and 185$\pm$48 min.)(p<0.05). The reperfusion time (13$\pm$7 min) in IAWBC was shorter than that of IRCBC (62$\pm$109 min.)(p<0.05). CKMB at 12 hours and 24 hours (16$\pm$15 and 9$\pm$13) in IAWBC was lower than that of IRCBC (33$\pm$47 and 17$\pm$26)(p<0.05). The awakening time in IAWBC (2$\pm$1 hour) was shorter than that of IRCBC (4$\pm$3)(p<0.05). The number of spontaneous heart beat recovery in IAWBC (85%) was more than that of IRCBC (35%)(p<0.05). The cardiac index after discontinuing cardio-pulmonary bypass was significantly elevated in the IAWBC group. The prevalence of perioperative myocardial infarction in IAWBC (4%) was lower than that of IRCBC group (20%)(p<0.05). Conclusion: Intermittent antegrade warm blood cardioplegia is a safe, reliable, and effective technique for myocardial protection. It can also provide simpler and economic way than the retrograde cold cardioplegia by shortening of cardiopulmonary bypass time and avoiding retrograde cannulation for coronary sinus.

• Radiation Oncology Journal
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• v.12 no.2
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• pp.175-184
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• 1994

From March 1983 through January 1990, two hundred sixty six patients with non-small cell lung cancer were treated with external radiation therapy at the Department of Therapeutic Radiology, Kangnam St. Mary's Hospital, Catholic University Medical College. A retrospective analysis was performed on eligible 116 patients who had been treated with radiation dose over 40 Gy and had been able to be followed up. There were 104 men and 12 women. The age ranged from 33 years to 80 years (median ; 53 years). Median follow up period was 18.8 months ranging from 2 months to 78 months. According to AJC staging system, there were 18($15.5\%$) patients in stage II, 79($68.1\%$) patients in stage III and 19($16.4\%$) patients in stage IV. The Pathologic classification showed 72($62.8\%$) squamous cell carcinomas, 16($13.8\%$) adenocarcinomas, 7($6\%$) large cell carcinomas, 5($4\%$) undifferentiated carcinomas, and 16($13.8\%$) un-known histology. In Karnofsky performance status, six ($5.2\%$) patients were in range below 50, 12($10.4\%$) patients between 50 and 60, 46($39.6\%$) patients between 60 and 70, 50($44.0\%$) patients between 70 and 80 and only one ($0.8\%$) patient was in the range over 80. Sixty ($51.7\%$) patients were treated with radiation therapy (RT) alone. Thirty three ($28.4\%$) patients were treated in combination RT and chemotherapy, twenty three ($19.8\%$) patients were treated with surgery followed by postoperative adjuvant RT and of 23 Patients above, five ($4.3\%$) patients, were treated with postoperative RT and chemotherapy. Overall response according to follow-up chest X-ray and chest CT scans was noted in $92.5\%$ at post RT 3 months. We observed that overall survival rates at 1 year were $38.9\%$ in stage II, $27.8\%$ in stage III, and $11.5\%$ in stage IV, and 2 year overall survival rates were $11.1\%$ in stage II, $20.8\%$ in stage III and $10.5\%$ in stage IV, respectively. We evaluated the performance status, radiation dose, age, type of histology, and the combination of chemotherapy and/or surgery to see the influence on the results fellowing radiation therapy as prognostic factors. Of these factors, only performance status and response after radiation therapy showed statistical significance (P<0.05)

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Sleep Medicine and Psychophysiology
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• v.6 no.2
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• pp.126-132
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• 1999

Objectives: The purposes of this study were to investigate 1) the incidence of insomnia, 2) the clinical characteristics of the insomniacs, 3) the correlation of severity of insomnia with somatic complaints and psychological distresses, and 4) the beliefs and attitudes about sleep in patients with chronic renal failure on hemodialysis. Methods: The author evaluated 153 patients, receiving hemodialysis therapy at the four outpatients hemodialysis units in Pusan, Korea. The patients had completed a self-administered questionnaire package, which consisted of basic demographic findings, questions characterizing insomnia, Beck Depression Inventory(BDI), Spielburger's State-Trait Anxiety Inventory(STAI), and visual analogue scales measuring quantitatively the severity of the self-perceived psychological and somatic symptoms. And several laboratory data were collected. Diagnosis of insomnia was made in the base of insomnia criteria of DSM-IV and international classification of sleep disorders. Subjects were dichotomized into those who reported any characteristics of insomnia or those who had no insomnia during the preceding two weeks. Results: Insomnia was found in 100(65.4%) of 153 patients. No statistical differences were found between the patients with and without insomnia in terms of age, gender, education, marital status, mean duration of hemodialysis and all considered laboratory findings except serum albumin. The patients with insomnia had significantly higher BDI score and predialysis systolic blood pressure, and lower serum albumin as compared to non-insomnia group. Significant differences were found between two groups in terms of self-perceived distress such as sadness, anxiety, worry, pruritus, and dysfunction of daily life. The data showed statistically significant correlation between insomnia severity and some variables such as physical dysfunction, pruritus, bone pain, sadness, anxiety, worry, dysfunction of daily life and excessive daytime sleepiness. The patients with insomnia had significantly several dysfunctional beliefs and attitudes about sleep than those without insomnia. Conclusion: These results indicate that insomnia is very common in hemodialysis patients and likely contribute to the impaired quality of life experienced by many these patients. The author suggests that physical and psychological distresses would be reduced and the quality of life could be improved if their sleep disturbances are properly ameliorated in patients on hemodialysis.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1981.05a
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• pp.9.1-10
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• 1981

The clinical study of 183 cases of laryngeal mass was observed and 88 cases of vocal nodule and polyp which is confirmed histopathologically, were clinically classified into 30 cases of vocal nodule, 48 cases of localized vocal polyp, 10 cases of diffuse vocal polyp, and the following results of microscopic examination were obtained. I. The clinical study of laryngeal mass 1. Among total cases of 183, vocal nodule is 82(45%) vocal polyp 53(29%) postintubation granuloma 3(1%) laryngeal papilloma 18(10%) tuberculosis 2(1%) cancer 25(14%). 2. The sex ratio of male to female is 3:4 in vocal nodule, 1:1 in vocal polyp, 1:2 in postintubation granuloma, 3:2 in laryngeal papilloma, 11:1 in cancer. 3. The age distribution is third-fourth decade in vocal nodule, fourth-fifth decade in vocal polyp, third decade in postintubation granuloma, second and fifth decade in laryngeal tuberculosis, sixth decade in laryngeal cancer. 4. The distribution of symptoms is 5 month. -1 year in vocal nodule and polyp, less than 1 year in laryngeal papilloma and postintubation granuloma, 1 year-3 year in laryngeal tuberculosis and cancer. 5. The location of the lesion is between the anterior 1/3 and middle 1/3 in vocal nodule and polyp and papilloma, middle 1/3 and posterior 1/3 in postintubation granuloma, and is diffusely spread on the entire vocal cord in laryngeal tuberculosis and cancer. 6. The side of the lesion is bilateral in vocal nodule and papilloma and the ratio of right to left is 5:3 in vocal polyp, 2:1 in postintubation granuloma. 7. The size is 1~2mm(67%) in vocal nodule, 3~5mm(42%) in vocal polyp, 6~10mm (67%) in postintubation granuloma, 1~2mm (39%) in papilloma, more than 10mm in tuberculosis and cancer. 8. Among the symptoms, the hoarseness is in more than 90% of disease entity, the sore-throat in tuberculosis and cancer, the dyspnea in postintubation granuloma and papilloma and tuberculosis and cancer. 9. In the past history, certain relationship with smoking is noted in cancer (40%) and tuberculosis(50%) and the history of frequent attack of URI is in papilloma(33%). 10. In occupation, certain statistical significance was not noted. II. The histopathological study of vocal nodule and polyp. 1. Most polyps and nodules were covered with stratified squamous epithelium, but focal hyperkeratosis, parakeratosis, acanthosis and atrophy were rather frequently observed. Hyperkeratosis and acanthosis was most frequently seen.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1475-1490
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• 2021

Detecting oil spill area using statistical characteristics of SAR images has limitations in that classification algorithm is complicated and is greatly affected by outliers. To overcome these limitations, studies using neural networks to classify oil spills are recently investigated. However, the studies to evaluate whether the performance of model shows a consistent detection performance for various oil spill cases were insufficient. Therefore, in this study, two CNNs (Convolutional Neural Networks) with basic structures(Simple CNN and U-net) were used to discover whether there is a difference in detection performance according to the structure of CNN and distribution characteristics of oil spill. As a result, through the method proposed in this study, the Simple CNN with contracting path only detected oil spill with an F1 score of 86.24% and U-net, which has both contracting and expansive path showed an F1 score of 91.44%. Both models successfully detected oil spills, but detection performance of the U-net was higher than Simple CNN. Additionally, in order to compare the accuracy of models according to various oil spill cases, the cases were classified into four different categories according to the spatial distribution characteristics of the oil spill (presence of land near the oil spill area) and the clarity of border between oil and seawater. The Simple CNN had F1 score values of 85.71%, 87.43%, 86.50%, and 85.86% for each category, showing the maximum difference of 1.71%. In the case of U-net, the values for each category were 89.77%, 92.27%, 92.59%, and 92.66%, with the maximum difference of 2.90%. Such results indicate that neither model showed significant differences in detection performance by the characteristics of oil spill distribution. However, the difference in detection tendency was caused by the difference in the model structure and the oil spill distribution characteristics. In all four oil spill categories, the Simple CNN showed a tendency to overestimate the oil spill area and the U-net showed a tendency to underestimate it. These tendencies were emphasized when the border between oil and seawater was unclear.

• Journal of the Korean Orthopaedic Association
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• v.56 no.3
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• pp.234-244
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• 2021

Purpose: To date, studies of firearm and explosive injuries in the Korean military have been limited compared to its importance. To overcome this, this study examined the characteristics of musculoskeletal damages in soldiers who have suffered firearm and explosive injuries over the past four years. Materials and Methods: From January 2015 to July 2019, military forces who had suffered musculoskeletal injuries from firearms or explosive substances were included. The medical records and radiographs were reviewed retrospectively, and telephone surveys about Short Musculoskeletal Functional Assessment (SMFA) for this group were conducted. To compare the functional outcomes, statistical analysis was performed using a t-test for the types of weapons, and ANOVA for others. Results: Of the 61 patients treated for firearms and explosives injuries, 30 patients (49.2%) were included after undergoing orthopedic treatment due to musculoskeletal injury. The average age at injury was 26.4 years old (21-52 years old). The number of officers and soldiers was similar. Eleven were injured by gunshot and 19 by an explosive device. Sixteen were treated in the Armed Forces Capital Hospital and 10 at private hospitals. More than half of the 16 patients (53.3%) with a fracture had multiple fractures. The most common injury site was the hand (33.3%), followed by the lower leg (30.0%). There were 14 patients (46.7%) with Gustilo-Anderson classification 3B or higher who required a soft tissue reconstruction. Fifteen patients agreed to join the SMFA survey for the functional outcomes. Between officers and soldiers, officers had better scores in the Bother Index compared to soldiers (p=0.0045). Patients treated in the Armed Forces Capital Hospital had better scores in both the Dysfunction and Bother Index compared to private hospitals (p=0.0008, p=0.0149). Conclusion: This is the first study to analyze of weapons injuries in the Korean military. As a result of the study, the orthopedic burden was high in the treating patients with military weapon injuries. In addition, it is necessary to build a military trauma registry, including firearm and explosive injuries, for trauma treatment evaluation and development of military trauma system.