• Journal of Yeungnam Medical Science
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• v.10 no.1
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• pp.179-189
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• 1993

It has recently become possible to record electrical activity originating from abnormally conducting myocardium from the body surface with high - gain amplification and averaging technique. These signals, which result from delayed ventricular activation(late potentials), have been recorded in patients with documented ventricular tachyarrythmia. Several electrode lead system for detecting ventricular late potential were introduced. Pyramidal electrode lead system(PLS) is useful. Also interpretation of SAECG in the young could be of value in detecting those at risk for episodic ventricular tachycardia, but suffer from a lack of data in normal young people. Selection of subjects : For this study, normal healthy young adult volunteers (age: mean 24 years) were recruited from the medical students at Yeungnam University Hospital, Internal Medicine. Twenty fourths male and seventeenths female subjects were selected. All subjects had normal resting ECGs as judged from both the standard 12 channel lead and echocardiography, and none had a history of cardiovascular disease. All subjects were considered to be in good general physical condition. Signal-averaged electrocardiography : In order to obtain low noise recordings with a small number of averaging cycles, all subject ware asked to relax completely in the supine position. Silver/silver chloride electrodes were attached after the skin was cleaned with alcohol, to constitute classic flank lead system(FLS) and pyramidal lead system(PLS). Signals were recorded and processed using a commercially available microprocessor-augmented ECG cart(Marquette Electronics, USA) suitable for portable bedside recording. There was no difference between normal values, determined by FLS and PLS at high pass filtering of 25 Hz and 80 Hz, but significant, difference was found in HFLAD and RMS-40 of 40 Hz(p<0.05). These results will provide a basis for interpretations of SAECG, determined by FLS and PLS in healthy young adults with normal QRS duration.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.157-176
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• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.6
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• pp.41-51
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• 2015

The purpose of the Follies that were constructed for the Gwangju-Biennale were for urban regeneration, to activate the empty old-town areas, and to strengthen the tradition and sense of place of the city. However, the ten Follies constructed around the wall of the old castle reveal many problems including that of leaving Follies alone instead of actively using them, damage to shop-keepers nearby, and pedestrian inconvenience, which is different from the original purposes. This study is meant to help understand the source of the negative phenomena, and to offer plans that will be conductive to the role of urban regeneration through activating the Follies and the spaces around them. As results of the investigation, there was no context giving uniformity among the various Follies. Also, the study showed that the insufficience of designers' understanding of the circumference near the Follies and lack of a consensus between the citizens and designers in the process of making the Follies. The crucial solution for solving these problems, and bringing to life the original purpose of creating the Follies was derived as applying "human activity" to the Follies. This study suggested 'street performance' as an effective device for application to human activity. While a Folly has no fixed function, the development of space program categories based on the applied characteristics of each Folly, and the simulation thereof showed effective potential for attracting people and activating those stagnated spaces. Recently, Gwangju city depicted the second Follies in applications such as reading roon, toilet, and movable food cart, which have clear purpose and different characteristics from the first ones. However, the first Follies will not be moved or demolished. As they are located around the National Asia Culture Center, some of them are supposed to be used to view the center. Consequently, a counterplan for the continuous and efficient use of those Follies is needed. Gwangju has a plan for the installation of 100 Follies throughout the city and it is expected that this study will be a meaningful guide line for improved Follies in the future.

• Journal of Korean Academy of Nursing
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• v.7 no.2
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• pp.11-21
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• 1977

Many in nursing look back on Nursing Research history and proudly point to the fact that emphasis in nursing research has changed from studying the nurse to studying nursing practice. In recent years, much emphasis has been placed on seeking a method of evaluating the quality of nursing care. In spite of these attempts, however, an instrument for evaluating the quality of nursing care that is actually applicable in the clinical area has not been found. The Purposes of this study are as follows: 1) To develop the instrument to be used in evaluating the quality of nursing care provided in the Neuro - Surgery Constant Care Unit of Severance Hospital 2) To evaluate the quality of nursing care in the clinical area. 3) To provide the necessary information for improvement of quality of nursing care. The instrument for evaluating the quality of nursing care, developed by the investigator, was composed of 7 nursing goals and divided into 65 standards of nursing performance. The 7 nursing goal are as follows : 1) Maintenance of airway 2) Maintenance of fluid at electrolyte balance 3) Maintenance of elimination 4) Personal hygiene 5) Optimum activity 6) Prevention of accidents 7) Emotional care The study population defined was composed of all the case (51) who were admitted in the Neuro- Surgery Constant Care Unit of Severance Hospital from May 7-13, 1976. The observation method was used and the data was subjected to the %, X²-test, T-test, F-test and Correlation. The results of tile study were as follows : 1. Levels of nursing performance regarding nursing goals. Seven different nursing care indices were constructed in terms of nursing goals. The index scores were grouped arbitrarily into ,j categories such as "excellent", "good", "moderate", "incomplete", and "poor"based upon the investigator′s personal judgement. a. The nursing index of maintaining airway showed that 78% of the patients fell within the "excellent" and 22% of the patients, fell within the "good" category. b. The nursing index of maintaining fluid & electrolyte balance showed that 95% of the patients fell within the "excellent" and 5 % of the patients fell within the "good" category. c. The nursing index of maintaining elimination showed that 100% of the patients fell within the "excellent" category. d. The nursing index of personal hygiene revealed that 49% of the patients fell within the "excellent" and 51% of the patients fell within the "good" category. e. The nursing index of optimum activity showed that 63% of the patients fell within the "excellent" and 32% of the patients fell within tile "good" and 5% of patients fell within the "moderate" category. f. The nursing index of prevention of accidents showed that 100% of the patients foil within the "excellent" category. g. The nursing index of emotional cart revealed that 27% of the patients fell within the "excellent", 24 % of the patients fell within tile "good", 29 % of the patients fell within the "incomplete" category. From these findings it is disclosed that the quality of nursing care provided in the Neuro- Surgery Constant Care Unit of Severance Hospital was excellent. h. There were statistically significant differences between the nursing index of physical care and emotional care. (t=8.73, D. F. =100. p<0.01) It is revealed that more physical care then emotional care was carried out by nurses. 2. Levels of nursing performance regarding general characteristics of the patients. No significant differences were observed statistically with the nursing indices of nursing goals according to the sex (t=0.084, D. F. =12, p>0.05). Age (F=0.1251, D. F. : 3.18. p 〉0.05), absence or presence of operating experiences (t=0.6032, D. F. =12, p〉0.05, levels of consciousness (F=0.31, D. F. :3. 18, p >0.05) 3. Relationship between the levels of consciousness and the nursing index of each nursing goal. There was negative correlation between the levels of consciousness and the nursing index of maintaining airway (r=-0. 5449, p<0.01) and personal hygiene (r= -0.4075, p<0.01) There was positive correlation between the levels of consciousness and the nursing index of optimum activity (r=0.3936, p <0.01) and emotional care (r=0.7819, p〈0.01). There was slight correlation between the levels of consciousness and the nursing index of maintaining fluid & electrolyte balance (r=-0.3418, 0.010.05) and preventing accidents (r=0.1441, p>0.05.

• Korean Journal of Agricultural Science
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• v.9 no.1
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• pp.260-268
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• 1982

The study has been carried out to investigate the relationship of certain factors to the private owners' attitudes toward forest management. The dependent variable is the attitude toward forest management, and the six independent variables are owner's age, educational level, forestland area, socioeconomic status, communicational and sociopsychological factors. The dependent variables were measured by Likert attitude scale. The data used in the study were obtained from 262 common-and model-forest owners, and analyzed primarily by multiple correlation statistical technique. Major findings of the study are summarized as follows; 1. The average score of common-owners' attitudes toward forest management is significantly lower than that of model-owners'. The scores of such independent variables as age, forestland area, socioeconomic status and communication of common-owners are also significantly lower than those of model-owners', while the significant difference of sociopsychological scores is not recognized between two owner groups. 2. The common-owners' attitudes toward forest management are negatively correlated with age variable, arid positively with other independent variables. On the other hand, the model-owners' are negatively correlated with education variable, arid positively with age, communicational and sociopsychological factors. 3. The multiple correlation coefficient between common-owner' management-attitude scores and six independent variables is 0.6971. About 41 percent of the variance of this attitude cart be explained by sociopsychological factor, and other 7 percent by communicational variable. In case of model-owners, the multiple correlation coefficient is 0.5207, and about 16.2 percent of the variance of the attitude can be explained by sociopsychological factor and 6 percent by age variable. 4. The multiple correlation coefficient between the attitude scores of all-owners arid such seven different personality factors as fatalistic, trustful, cooperative, ambitious, conservative, scientific and traditional familism personalities is 0.6566. In this case, 15 percent of the variance of the management-attitude can be explained by ambitious personality, and 11.2 percent by traditional familism. 5. The private forest owners' attitudes toward forest management are greatly affected by sociopsychological and communicational factors. The emphasis should be therefore put on the forestry extension works to induce private owners to management practices.

• Journal of the Korean Applied Science and Technology
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• v.36 no.1
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• pp.23-33
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• 2019

After making tea by steaming the Burdock(Arctium lappa) nine times and drying it nine times, the ingredients and functions of the Burdock tea were compared to those of M company. The tea's calories were 346.48kcal/100g, carbohydrates were 72.75g/100g, crude protein was 11.98g/100g, and crude ash was 5.01g/100g. The total of free sugars were 31.93mg/100, among them, fructose was 26.27, sucrose was 1.27 mg/100g. The inorganic material contents were 1,476.21mg/100g of potassium, 255.96 mg/100g of calcium and 311.41 mg/100g of magnesium. The saturated fatty acids were 40.73mg/100g and the unsaturated fatty acids were 59.27mg/100g, among which the linoleic acid was 41.28mg/100g, the palmitic acid was 33.11mg/100g, the oleic acid was 10.07mg/100g and linolenic acid was 7.92mg/100g. DPPH radical scavenging was 33.9% of teas that were developed, 2.3% of M's tea for comparison, and 37.2% of indiex material. ABTS radical scavenging were 90.7% of teas developed, 85.9% of M's tea and 37.2% of index materials, and SOD like activities were 11.3% of teas developed and 50.5% of M's teas. The flavonoid content was 2.6 fold of the tea developed, 2.9 fold of M's tea and 1.7 fold of index material. The polyphenol content was 33.8 fold of teas developed, 38.9 fold of the M's tea and 13.8 fold of the index material. The sensory evaluation compare to the one-time extract and the five-time extract. Based on the one-time extract, the color were 65.9 % of the five-time extract tea were developed, 12.8 % of the M's tea. Flavour were 78.0% of the tea developed and 33.3% of the M's tea, tastes were 71.4% of the tea developed, 20.7% of the M's tea. The cart for comparison showed that while the extract decreased as we developed it, the overall symbolism decreased to 21.4% after five time extracts, the developed tea decreased to 72.1%. We believe that the developed tea will have a greater effect on preventing and improving diseases as it has a stronger antioxidant function, more effective substances, and a higher level of symbolism than the comparative M squared tea and surface substance.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.59-77
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• 2012

This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.9
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• pp.1447-1456
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• 2014

The purpose of this study was to compare perception of school foodservice facilities and utilities in dietitians and school nutrition teachers in the Gyeongnam area between schools that improved foodservice facilities and utilities versus those who did not. From July 23 to Aug 31, 2012, 391 questionnaires were distributed, and 289 questionnaires were obtained. A total of 275 questionnaires were used for the final analysis, excluding improper ones. The results of this study were as follows. First, among 275 schools, 90 schools (32.7%) improved school foodservice facilities and utilities while 175 schools (67.3%) did not. Second, schools with improved facilities had a more well-equipped receiving room (P<0.01), preparation room (P<0.001), dishwashing room (P<0.001), storage room for supplies (P<0.001), rest-room for school foodservice employees (P<0.05), locker room (P<0.01), shower room (P<0.001), laundry room (P<0.001), boiler room (P<0.05), and room for serving cart (P<0.05) than schools with no improvement. Third, total perception score of school foodservice facilities area from schools with improved facilities (1.71) was significantly higher than that (1.60) of school without improvement (P<0.001). Fourth, total satisfaction (3.32) of school foodservice facilities and utilities in school with improved facilities was significantly higher than that (2.62) of schools without improvement (P<0.01). Fifth, schools with improved facilities had a better equipped of floor (P<0.05), entrance (P<0.001), drain (P<0.001), water supply (P<0.01), lighting (P<0.001), hand washing (P<0.001), foodservice management room (P<0.001), locker room (P<0.001), rest-room and shower room (P<0.001), and preparation room (P<0.001) than schools without improvement. However, there was no significant difference in terms of walls and ceilings, windows, ventilation, and storage. In conclusion, school foodservice facilities and utilities improvement should conducted as soon as possible.

• Progress in Medical Physics
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• v.23 no.2
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• pp.91-98
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• 2012

Verification of internal organ motion during treatment and its feedback is essential to accurate dose delivery to the moving target. We developed an offline based internal organ motion verification system (IMVS) using cine EPID images and evaluated its accuracy and availability through phantom study. For verification of organ motion using live cine EPID images, a pattern matching algorithm using an internal surrogate, which is very distinguishable and represents organ motion in the treatment field, like diaphragm, was employed in the self-developed analysis software. For the system performance test, we developed a linear motion phantom, which consists of a human body shaped phantom with a fake tumor in the lung, linear motion cart, and control software. The phantom was operated with a motion of 2 cm at 4 sec per cycle and cine EPID images were obtained at a rate of 3.3 and 6.6 frames per sec (2 MU/frame) with $1,024{\times}768$ pixel counts in a linear accelerator (10 MVX). Organ motion of the target was tracked using self-developed analysis software. Results were compared with planned data of the motion phantom and data from the video image based tracking system (RPM, Varian, USA) using an external surrogate in order to evaluate its accuracy. For quantitative analysis, we analyzed correlation between two data sets in terms of average cycle (peak to peak), amplitude, and pattern (RMS, root mean square) of motion. Averages for the cycle of motion from IMVS and RPM system were $3.98{\pm}0.11$ (IMVS 3.3 fps), $4.005{\pm}0.001$ (IMVS 6.6 fps), and $3.95{\pm}0.02$ (RPM), respectively, and showed good agreement on real value (4 sec/cycle). Average of the amplitude of motion tracked by our system showed $1.85{\pm}0.02$ cm (3.3 fps) and $1.94{\pm}0.02$ cm (6.6 fps) as showed a slightly different value, 0.15 (7.5% error) and 0.06 (3% error) cm, respectively, compared with the actual value (2 cm), due to time resolution for image acquisition. In analysis of pattern of motion, the value of the RMS from the cine EPID image in 3.3 fps (0.1044) grew slightly compared with data from 6.6 fps (0.0480). The organ motion verification system using sequential cine EPID images with an internal surrogate showed good representation of its motion within 3% error in a preliminary phantom study. The system can be implemented for clinical purposes, which include organ motion verification during treatment, compared with 4D treatment planning data, and its feedback for accurate dose delivery to the moving target.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.