• Clinical and Experimental Pediatrics
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• v.50 no.7
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• pp.643-648
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• 2007

Purpose : Sepsis is a common complication in Neonatal Intensive Care Units (NICU), seen especially in low birth weight (LBW) infants. A recent study showed that fungal or gram-negative sepsis is associated with a greater degree of thrombocytopenia than is seen with gram-positive sepsis. So, this study was undertaken to examine the platelet counts and platelet indices in LBW infants during episodes of sepsis. Methods : We analyzed 36 cases with culture-proven sepsis on chart review in LBW infants admitted to the NICU at Wonkwang University Hospital from January 2001 to June 2006. Results : Patients were grouped by organism type: gram-positive bacteria ($1,521{\pm}309g$, $31.3{\pm}2.9wk$, 15/36), gram-negative bacteria ($1,467{\pm}290g,\;30.6{\pm}3.6wk$, 17/36), and fungi ($1,287{\pm}205g,\;30.0{\pm}3.9wk$, 4/36). The most common organism was Staphylococcus epidermis and the incidence of thrombocytopenia was 88.9%. When compared with infants with gram-positive sepsis, those with gram-negative sepsis had significantly higher incidences of thrombocytopenia, lower initial platelet count, lower platelet nadir, and greater mean percentage decrease in platelet count from before the onset of sepsis. Those with fungal infections were similar to gram-negative sepsis, but they were not significant because of the small number of patients. And mean platelet volume (MPV) in sepsis was increased more significantly in time of platelet nadir than before the onset of sepsis. Conclusion : We conclude that decrease in platelet count was significantly greater in gram-negative sepsis than gram-positive sepsis, and also greater than fungal sepsis-which was insignificant because of the small number of patients-in LBW infants. And elevation in MPV will be helpful in the diagnosis and treatment of sepsis in LBW infants.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.2
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• pp.95-107
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• 2020

The purpose of this study is to provide the basic data by analyzing and analysing the Growth Conditions of old Trees in Yangdong village. This study investigated about the conducted on tree information, soil information, and tree health. The result are as follows. The trees information in Yangdong Village consists of Juniperus chinensis, Salix chaenomeloides, Salix pseudolasiogyne, Celtis sinensis, Zelkova serrata, Gleditsia japonica, and Gleditsia sinensis trees, The range of height was 4.0~17.0m, and the diameter was 0.51~1.34m, Juniperus chinensis trees of No.17 was most large. In the results of soil analysis, there showed that acidity was pH4.1~6.3, hardness of 5~48mm, organic matter content of 21.2~29.1g/kg, electrical conductivity(EC) of 0.34~1.76dS/m, available P₂O₅ of 79.8~451.6mg/kg, exchangeable K of 0.22~1.71cmol+/kg, exchangeable Ca of 4.98~7.44cmol+/kg, exchangeable Mg of 0.67~2.19cmol+/kg, exchangeable Na of 0.19~1.04cmol+/kg and cation exchange capacity(C.E.C) of 7.23~13.02cmol+/kg. As a result, the highest number of tree health levels is 8 of 11trees of Celtis sinensis, 2 of 7trees of Zelkova serrata, and 3 of Gleditsia sinensis, and 13 of 30 trees of health levels, The Older trees with high infection, spoil and hollowed part were the remaining trees except for the healthy part. Relatively, more than half of the number of targets is infected, decay, and the hollowed site, and it is necessary to perform surgery on the damaged area. In addition, preservation and protection measures should be implemented by supplying root nutrients for trees, controlling nutrients in the body to prevent secondary and tertiary damages that cause the infection site to metastasize to the health site, In order to continually monitor the trees, measures to improve the location environment and management of the trees should be sought.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.133-148
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• 2014

Recently, with the advent of various information channels, the number of has continued to grow. The main cause of this phenomenon can be found in the significant increase of unstructured data, as the use of smart devices enables users to create data in the form of text, audio, images, and video. In various types of unstructured data, the user's opinion and a variety of information is clearly expressed in text data such as news, reports, papers, and various articles. Thus, active attempts have been made to create new value by analyzing these texts. The representative techniques used in text analysis are text mining and opinion mining. These share certain important characteristics; for example, they not only use text documents as input data, but also use many natural language processing techniques such as filtering and parsing. Therefore, opinion mining is usually recognized as a sub-concept of text mining, or, in many cases, the two terms are used interchangeably in the literature. Suppose that the purpose of a certain classification analysis is to predict a positive or negative opinion contained in some documents. If we focus on the classification process, the analysis can be regarded as a traditional text mining case. However, if we observe that the target of the analysis is a positive or negative opinion, the analysis can be regarded as a typical example of opinion mining. In other words, two methods (i.e., text mining and opinion mining) are available for opinion classification. Thus, in order to distinguish between the two, a precise definition of each method is needed. In this paper, we found that it is very difficult to distinguish between the two methods clearly with respect to the purpose of analysis and the type of results. We conclude that the most definitive criterion to distinguish text mining from opinion mining is whether an analysis utilizes any kind of sentiment lexicon. We first established two prediction models, one based on opinion mining and the other on text mining. Next, we compared the main processes used by the two prediction models. Finally, we compared their prediction accuracy. We then analyzed 2,000 movie reviews. The results revealed that the prediction model based on opinion mining showed higher average prediction accuracy compared to the text mining model. Moreover, in the lift chart generated by the opinion mining based model, the prediction accuracy for the documents with strong certainty was higher than that for the documents with weak certainty. Most of all, opinion mining has a meaningful advantage in that it can reduce learning time dramatically, because a sentiment lexicon generated once can be reused in a similar application domain. Additionally, the classification results can be clearly explained by using a sentiment lexicon. This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of movie reviews. Additionally, various parameters in the parsing and filtering steps of the text mining may have affected the accuracy of the prediction models. However, this research contributes a performance and comparison of text mining analysis and opinion mining analysis for opinion classification. In future research, a more precise evaluation of the two methods should be made through intensive experiments.

• Journal of Food Hygiene and Safety
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• v.29 no.2
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• pp.79-84
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• 2014

This study has been performed for about 270 days at analyzing biologically hazardous factors in order to develop HACCP system for the non heat-frozen carrot juice. A process chart was prepared by manufacturing process of raw agricultural products of non heat-frozen carrot juice, which was contained water and packing material, storage, washing, cutting, extraction of the juice, internal packing, metal detection, external packing, storage and consignment (delivery). As a result of measuring Coliform group, Staphylococcus aureus, Salmonella spp., Bacillus cereus, Listeria Monocytogenes, Enterohemorrhagic E. coli before and after washing raw carrot, Standard plate count was $4.7{\times}10^4CFU/g$ before washing but it was $1.2{\times}10^2CFU/g$ detected after washing. As a result of testing airborne bacteria (Standard plate count, Coliform group, Yeast and Fungal) depending on each workplace, number of microorganism of in packaging room, shower room and juice extraction room was detected to be 10 CFU/Plate, 60 CFU/Plate, 20 CFU/Plate, respectively. As a result of testing palm condition of workers, as number of Standard plate count, Coliform group and Staphylococcus aureus was represented to be high as $6{\times}10^4CFU/cm^2$, $0CFU/cm^2$ and $0CFU/cm^2$, respectively, an education and training for individual sanitation control was considered to be required. As a result of inspecting surface pollution level of manufacturing facility and devices, Coliform group was not detected in all the specimen but Standard plate count was most dominantly detected in scouring kier, scouring kier tray, cooling tank, grinding extractor, storage tank and packaging machine-nozzle as $8.00{\times}10CFU/cm^2$, $3.0{\times}10CFU/cm^2$, $4.3{\times}10^2CFU/cm^2$, $7.5{\times}10^2CFU/cm^2$, $6.0{\times}10CFU/cm^2$, $8.5{\times}10^2CFU/cm^2$ respectively. As a result of analyzing above hazardous factors, processing process of ultraviolet ray sterilizing where pathogenic bacteria may be prevented, reduced or removed is required to be controlled by CCP-B (Biological) and critical level (critical control point) was set at flow speed is 4L/min. Therefore, it is considered that thorough HACCP control plan including control criteria (point) of seasoning fluid processing process, countermeasures in case of its deviation, its verification method, education/training and record control would be required.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.48-62
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• 2023

As seen in the recent K-pop craze, the size and influence of the Korean music industry is growing even bigger. At least 6,000 songs are released a year in the Korean music market, but not many can be said to have been successful. Many studies and attempts are being made to identify the factors that make the hit music. Commercial factors such as media exposure and promotion as well as the quality of music play an important role in the commercial success of music. Recently, there have been many marketing campaigns using Internet memes in the pop music industry, and Internet memes are activities or trends that spread in various forms, such as images and videos, as cultural units that spread among people. Depending on the Internet environment and the characteristics of digital communication, contents are expanded and reproduced in the form of various memes, which causes a greater response to consumers. Previously, the phenomenon of Internet memes has occurred naturally, but artists who are aware of the marketing effects have recently used it as an element of marketing. In this paper, the mediated effect of Internet memes in relation to the success factors of popular music was analyzed, and a prediction model reflecting them was proposed. As a result of the analysis, the factors with the mediated effect of 'cover effect' and 'challenge effect' were the same. Among the internal success factors, there were mediated effects in "Singer Recognition," the genres of "POP, Dance, Ballad, Trot and Electronica," and among the external success factors, mediated effects in "Planning Company Capacity," "The Number of Music Broadcasting Programs," and "The Number of News Articles." Predictive models reflecting cover effects and challenge effects showed F1-score at 0.6889 and 0.7692, respectively. This study is meaningful in that it has collected and analyzed actual chart data and presented commercial directions that can be used in practice, and found that there are many success factors of popular music and the mediating effects of Internet memes.

• Journal of Korean Public Health Nursing
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• v.3 no.2
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• pp.5-46
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• 1989

The current medical payment Insurance Rates in Korea stipulate charges for medical treatment by the doctor, pharmaceutist, medical technician and maternity nurse. But unfortunately didn't specify those charges for nursing done by the professional nurse. Only basic nursing fee is accounted insufficiently in current medical insurance fee schedule. therefore, Being face with covering entire people by medical insurance by 1991, It seems that the problems pertaining to operating the hospital and medical insurance system would be incessantly expanded in that no mention is made of medical charges rendered by major medical producer service in the current system, For that reason, this study made an attempt to clarify the importance the professional nursing puts of the current medical payment. The purpose of this study was to accounting nursing fee which diveded into the current medical fee schedule. (Method) 1. Data collection; Importance and difficulties in nursing activities was conducted in 'S' National University Hospital. Total nursing activities were selected 72 items which included direct care and indirect care. This study was conducted to evaluating the degree of importance and difficulties according to nursing activities through questionnaire to 204 RN. and so relative difficulties (acuity) were computered because the nursing cost level of each nursing service was differently established by the equivalent coefficient according to degree of relative difficulty and time required. 2. Calculation of cost according to nursing activities; After 47 nursing activities were selected in General surgery nursing units, calculation of nursing cost was as follows Cost of Nursing activity = (relative difficulty X Average hourly wage and benefits of nurse) + material cost of nursing -t- Average nursing administration cost So, Calculated cost by nursing activities was compared to current non-insured and insurance rate. 3. Calculation of nursing cost by K - DRG ; Total of 578 patients who were hospitalized in General Surgery units from January to March 1988 ware classified by K - DRG After estimation of total nursing cost based on the K-DRG, verified the appropriateness of basic nursing fee in medical insurance rate (Results) 1. Analysis of degree of importance and difficulties were 4.16 and 3.67 based on 5 point scale. This score were judged that it is worthy specifying the nursing fee 2. The nursing cost of 47 nursing service items in general surgery patients showed that the average cost of nursing activity was \1374.5 and The lowest cost was \217 of 'oral administration nursing' item, The highest cost was \11,025 of 'saline enematill clear' item 3. The result of comparison between the calculated cost by nursing activities against the current non-insured and insurance rate showed that 13 items(27.7%) involved to payment of insurance rate, 9 items(19.1%) involved to non-insured rate, remainder 25 items (53.2%) were not charged anywhere of total 47 nursing activities 4. When calculated cost by nursing activities was 100. current insurance rate was 62.3, non-insured rate was 176.6. Therefore this showed that most of non-insured rate were higher than calculated nursing cost. The insurance rate, however, were lower than it. Reim-bursement was imputed to non-insured patients. So the current rate system became estrainged from cost system. When Remainder 25 items of nursing activities compared' to \1390 of daily basic nursing fee per patient belonged to payment as a insurance fee schedule, basic nursing fee schedule was 1-2% of calculated cost of nursing activities. Therefore it showed that nursing fee was not counted adequately in it. 5. Nursing cost by K-DRG estimated in chart review based on counting number of nursing activities and length of stay The result showed that average amount of total nursing cost was \183828.1 Comparison of nursing cost calculated by K- DRG and basic nursing fee schedule showed that only 12.3% of nursing cost was charged (Conclusion) From the above research result, It is fact that nursing prime cost should be estimated more accurately and included adequately in current medical payment system. The payment system of nursing activities should be introduced not only nursing activities of drug administration and injection fee belonged to insurance fee schedule but also most nursing activities belonged not to mekical fee schedule. Even if introducing payment system of nursing activities, It should be estimated scientific method of Accounting nursing cost So nurses could offer nursing care of good quality, thereby they could make a great contribution not merely to the convalescence of the patient but to the promotion of the people's health.

• Cartoon and Animation Studies
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• s.38
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• pp.177-194
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• 2015

This study that had been conducted two months by a research team of Pusan National University at the request of Korea Manwha Contents Agency in Dec. 2013 is about the statistical analysis on 'Korean Webtoon DB and its Flow Report' which resulted from the complete survey of Korean webtoons which had been published with payment in official media from early 2000 to 2013. Webtoon which means the cartoons published on web has become a typical type of Korean cartoons and has developed into a main industry since 2000s when traditional published cartoons had declined and social environments had changed. Today, it represents cultural contents in Korea. This study collected the webtoons officially published in media with payment, among Korean webtoons having been published from the early 2000s to Jan. Based on the collected data, it analyzed the general characteristics of webtoons, including cartoonists, the number of cartoons, distribution chart of each media, genre, and publication cycle. According to the data analysis and statistics, a great deal of Korean webtoons are still published in main portal websites, but their platform is being diversified and a webtoon's publication cycle tends to be shortened. In terms of genre, traditional popular genres, such as drama, comic, fantasy, and action, are still popular, and the genres of history, sports, and food are on the rise along with a social trend. Regarding webtoon application, such events as relay webtoon and brand webtoon, and a new type of webtoon featuring PPL commercialism appear. Such phenomena can realize the common profits of cartoonists, media, and ordering bodies, and are various trials to test the possibility of webtoons. In addition, what needs to pay attention on in the expansion of webtoons is increasing webtoons for adults. The study subjects are the webtoons published with payment, excluding free webtoons. However, this study failed to collect the webtoons published on the online websites already closed, and the lost information on cartoonists and their lost webtoons, and it is necessary to conduct a complete survey on all webtoons including free ones. Despite the limitations, this study is meaningful in the points that it categorized and analyzed Korean webtoons accoridng to official media, webtoons, cartoonists, and genres and that it provided a fundamental material to understand the current conditions of webtoons. It is expected that this study will be able to contribute to activating more research on webtoons and producing more supplementary data which will be used for the Korean cartoon industry and academia.

• Clinical and Experimental Pediatrics
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• v.48 no.10
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• pp.1121-1125
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• 2005

Purpose : Rotavirus is the main cause of infantile diarrheal disease worldwide, especially in patients 3-24 months of age. Infants younger than 3 months of age are relatively protected by transplacental antibody. So the purpose of this study is to evaluate the clinical features and severity of neonatal rotaviral gastroenteritis less than 1 month of age. Methods : A retrospective chart review was established of 62 neonates less than 1 month of age and with a diagnosis of rotaviral gastroenteritis who had been admitted to Pochon CHA University between June 2002 through July 2004. The rotavirus was examined by stool latex agglutination. Results : During 2 years, the total number of admitted patients for rotaviral gastroenteritis was 688 and among these, less than 1 month of age accounted for 9%(62). The occurrence was generally even distribution from January to July($7.14{\pm}1.0$) but since then decreased($2.4{\pm}1.8$). The most common chief complaint was mild fever(46%) when admitted which subsided within 1 hospital day in most patients. 4 patients had seizure and cyanosis with no typical symptoms of rotaviral gastroenteritis. During admission, all the patients had diarrhea. 17% of the patients had leukocytosis and positive C-reactive protein. In one patient, stool occult blood test was positive but there was no necrotizing gastroenteritis evidence. The mean period of hospital day was $5.8{\pm}2.5$ and breast-milk feeding was 62.9%. Conclusion : Neonatal rotaviral gastroenteritis is not a rare disease. Most patients have fever and diarrhea and improve through conservative therapy but a few patients may have severe complications so we must be more cautious about the hygiene for prevention.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

• 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.