• Journal of Gastric Cancer
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• v.8 no.4
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• pp.256-261
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• 2008

Purpose: Intra-abdominal fluid collection is one of the risk factors associated with postoperative morbidity or mortality for patients who undergo gastric cancer surgery. The aim of this study was to analyze the clinicopathological characteristics of the patients with postoperative intra-abdominal fluid collection and to identify the indications for inserting a percutaneous drain (PCD) in patients with intra-abdominal fluid collection. Materials and Methods: Among the 1,277 patients who underwent operations for gastric cancer at Seoul National University Hospital between April 2005 and July 2006, the data of 117 patients with an intra-abdominal fluid collection were reviewed. Results: The number of patients' with pathologic stage I, II, III and IV disease was 42 (36.8%), 23 (20.2%), 16 (14%) and 33 (28.9%), respectively. Forty-three patients (36.3%) underwent PCD insertion and the other 43 patients received conservative management. A univariate analysis of multiple clinical variables revealed that age, gender, diabetes, liver disease, lymph node dissection, the pathologic stage and the body mass index (BMI, $kg/m^2$) were not significantly associated with PCD insertion (P>0.05). However, the univariate analysis showed that two characteristics were associated with a significantly high incidence of PCD insertion: a diameter of an intra-abdominal fluid collection greater than 4 cm and infectious signs such as leukocytosis, fever and bacteremia. Conclusion: About two thirds of the intra-abdominal fluid collections after surgery for gastric cancer were managed with only conservative method without other morbidities of mortality. Surgeons should consider performing PCD insertion if the largest diameter of an intra-abdominal fluid collection is over 4 cm or if infectious signs are seen.

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

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

• 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 Life Science
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• v.23 no.2
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• pp.228-236
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• 2013

This study was aimed at investigating whether dietary therapy using medicinal enzyme powder is effective in reducing constipation caused by loperamide in rats. Nine-week-old male Sprague Dawley were subdivided into 4 groups: normal diet group (C), loperamide treatment and normal diet (CL), medicinal enzyme powder diet (E), and loperamide treatment and medicinal enzyme powder diet (EL). Constipation was induced by subcutaneous injection of loperamide (1.5 mg/kg) 3 days prior to sacrifice. The treatment with loperamide led to an increase in weight gain, a decrease in the number and wet weight of fecal pellets, and a decrease in intestinal motility. The administration of the medicinal enzyme powder significantly reduced weight gain but increased intestinal mobility compared with the loperamide-treated group. The treatment with loperamide in the normal diet group reduced the activities of both suggesting that constipation may be involved in the low level of glutamic oxaloacetic transaminase (GOT) and glutamic pyruvic transaminase (GPT). Additionally, the loperamide treatment in the medicinal enzyme powder diet group increased the level of GOT, but reduced the level of GPT. Loperamide treatment also reduced cholesterol and increased the atherogenic index (AI) and cardiac risk factors (CRFs). Interestingly, the treatment with the medicinal enzyme powder effectively attenuated both the increase in AI and the reduction in high density lipopretein (HDL)-cholesterol, caused by the treatment with loperamide. Although there were no significant differences in the blood protein level, including hemoglobin and hematocrit, between the normal diet group and the loperamide-treated group, the administration of the medicinal enzyme powder to the loperamide-treated group effectively increased the levels of both hemoglobin and hematocrit. Collectively, the results demonstrate that the medicinal enzyme powder can help to combat the negative events caused by constipation.

• Journal of Nutrition and Health
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• v.47 no.2
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• pp.124-133
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• 2014

Purpose: The current study was designed for development of a simplified malnutrition screening tool (SMST) for hospitalized patients using readily available laboratory and patient information and for evaluation of its reliability compared to well-established tools, such as PGSGA and NRS-2002. Methods: Anthropometric and biochemical measurements, as well as a few subjective assessments, of 903 patients who were preclassified by their nutritional status according to PGSGA were analyzed. Among them, a combination of factors, including age, BMI, albumin, cholesterol, total protein, hematocrit, and changes in body weight and food intake, were statistically selected as variables for SMST. Results: According to SMST, 620 patients (68.7%) were classified as the normal group and 283 patients (31.3%) were classified as the malnutrition group. Significant differences in age, albumin, TLC, BMI, hemoglobin, hematocrit, total protein, cholesterol, and length of stay were observed between the two groups. For inter-methods reliability, the screening results by SMST were compared with those by PGSGA and NRS-2002. The comparison with PGSGA and NRS-2002 showed 'Substantial agreement' (sensitivity 94.4%, specificity 88.4%, ${\kappa}$ = 0.747) and 'Moderate agreement' (sensitivity 96.1%, specificity 79.5%, ${\kappa}$ = 0.505), respectively, indicating that SMST held high inter-methods reliability. Conclusion: In conclusion, SMST, based on readily available laboratory and patient information and simple subjective assessments on changes in food intake and body weight, may be a useful alternative tool with a simple but reliable risk index, especially in resource-limited domestic hospitals.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.177-183
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• 2018

Purpose : Volumetric Modulated Arc Therapy(VMAT) has the advantage of uniformly and precisely irradiating the tumor to the shape of the tumor while reducing the risk of radiation damage to normal tissues. such as brain cancer, head and neck cancer and prostate cancer, It is being used for treatment. The purpose of this study is to evaluate the usefulness of the Jaw-Tracking technique(JTT) in VMAT for brain and head and neck cancer. Materials and Methods : We selected eight patients with brain and head and neck cancer(4 Brain, 4 head and neck) who were treated with the VMAT treatment technique. Contouring information of the patient's tumor and normal organ was fused to the Rando phantom using the deformable registration of Velocity(Varian, USA). A treatment plan was developed using the Varian Eclipse(ver 15.5, Varian, USA) with the same patient actual beam parameters except for the use of jaw-tracking. As the evaluation index, the maximum dose and mean dose of target and OAR were compared and a portal dosimetry was performed for the treatment plan verification. Results : When using JTT, the relative dose of OAR decreased by 5.24 % and the maximum dose by 7.05 %, respectively, compared with the Static-Jaw technique(SJT). In the various OARs, the mean dose and maximum dose reduction ranges ranged from 0.01 to 3.16 Gy and from 0.12 to 6.27 Gy, respectively. In the case of the target, the maximum dose of GTV, CTV, PTV decreased by 0.17 %, 0.43 %, and 0.37 % in JTT, and the mean dose decreased by 0.24 %, 0.47 % and 0.47 %, respectively. Gamma analysis The JTT and SJT passing rates were $98{\pm}1.73%$ and $97{\pm}1.83%$ on the basis of 3 % / 3 mm, respectively. Comparing the doses of all OARs applied to the experiment, it was found that the use of JTT resulted in a significant decrease in dose due to additional jaw shielding besides MLC than SJT. Conclusion : In radiation therapy using VMAT treatment plan, we can apply JTT in the case of adjacent tumor and normal organs such as brain cancer and head and neck cancer, and in radiotherapy required large field and high energy caused increase leakage dose through MLC. It is considered that the target dose of PTV can be increased by lowering the dose of normal tissue surrounding the tumor.

• Food Science and Preservation
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• v.17 no.5
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• pp.688-697
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• 2010

We investigated the cholesterol-lowering and body-weight loss effects of Cheonggukjang fermented using Bacillus subtilis DJI in rats fed a high-fat/high-cholesterol diet for 4 weeks. Weight-matched male Sprague-Dawley rats were assigned to one of four groups: a normal diet group (N), a high-fat/high-cholesterol diet group (HFC), a high-fat/high-cholesterol diet with DJI Cheonggukjang group (HFC-SCK), and a high-fat/high-cholesterol with commercial Cheonggukjang group (HFC-CCK). All of body weight and liver and adipose tissue weights increased in animals fed a high-fat/high-cholesterol diet, but decreased significantly in rats fed Cheonggukjang powder, compared with the HFC group. Food intake was lower in the HFC group than in the N group, and that of the HFC-CCK group was the lowest among the four groups. Serum total cholesterol levels were significantly lower in the Cheonggukjang-powder fed groups than the other groups. Serum phospholipid and HDL-cholesterol concentrations were significantly decreased in HFC animals and were markedly increased upon feeding of a Cheonggukjang-containing-diet. Levels of serum LDL-cholesterol, the atherogenic index, and cardiac risk factor assessment indications tended to be decreased in Cheonggukjang powder-fed groups, compared with the HFC group. The total cholesterol level in liver tissue was increased by feeding of a high-fat/high-cholesterol diet, and was significantly reduced when Cheonggukjang powder was present in the diet. The levels of total lipids and triglycerides in adipose tissues were lower in the HFC-SCK group than in the HFC group, whereas no significant differences were evidence when the HFC and the HFC-CCK groups were compared. Fecal weight, moisture level, and total lipid content increased in animals fed Cheonggukjang powder. The activities of HR-LPL and TE-LPL in adipose tissues were increased in the HFC group compared with the Cheonggukjang powder-fed groups. These results indicate that dietary Cheonggukjang may improve lipid metabolism and prevent obesity and hyperlipidemia.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.167-175
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• 2019

To effectively deal with the fire in tunnel which is mostly the vehicle fire, it's more important to suppress the fire at early stage. In urban tunnel, however, accessibility to the scene of fire by the fire fighter is very limited due to severe traffic congestion which causes the difficulty with firefighting activity in timely manner and such a problem would be further worsened in underground road (double-deck tunnel) which has been increasingly extended and deepened. In preparation for the disaster in Korea, the range of life safety facilities for installation is defined based on category of the extension and fire protection referring to risk hazard index which is determined depending on tunnel length and conditions, and particularly to directly deal with the tunnel fire, fire extinguisher, indoor hydrant and sprinkler are designated as the mandatory facilities depending on category. But such fire extinguishing installations are found inappropriate functionally and technically and thus the measure to improve the system needs to be taken. Particularly in a double-deck tunnel which accommodates the traffic in both directions within a single tunnel of which section is divided by intermediate slab, the facility or the system which functions more rapidly and effectively is more than important. This study, thus, is intended to supplement the problems with existing tunnel life safety system (fire extinguishing) and develop the remote-controlled automatic fire extinguishing system which is optimized for a double-deck tunnel. Consequently, the system considering low floor height and extended length as well as indoor hydrant for a wide range of use have been developed together with the performance verification and the process for commercialization before applying to the tunnel is underway now.