• Korean Journal of Radiology
• /
• v.22 no.3
• /
• pp.344-353
• /
• 2021

Objective: The mitotic count of gastrointestinal stromal tumors (GIST) is closely associated with the risk of planting and metastasis. The purpose of this study was to develop a predictive model for the mitotic index of local primary GIST, based on deep learning algorithm. Materials and Methods: Abdominal contrast-enhanced CT images of 148 pathologically confirmed GIST cases were retrospectively collected for the development of a deep learning classification algorithm. The areas of GIST masses on the CT images were retrospectively labelled by an experienced radiologist. The postoperative pathological mitotic count was considered as the gold standard (high mitotic count, > 5/50 high-power fields [HPFs]; low mitotic count, ≤ 5/50 HPFs). A binary classification model was trained on the basis of the VGG16 convolutional neural network, using the CT images with the training set (n = 108), validation set (n = 20), and the test set (n = 20). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated at both, the image level and the patient level. The receiver operating characteristic curves were generated on the basis of the model prediction results and the area under curves (AUCs) were calculated. The risk categories of the tumors were predicted according to the Armed Forces Institute of Pathology criteria. Results: At the image level, the classification prediction results of the mitotic counts in the test cohort were as follows: sensitivity 85.7% (95% confidence interval [CI]: 0.834-0.877), specificity 67.5% (95% CI: 0.636-0.712), PPV 82.1% (95% CI: 0.797-0.843), NPV 73.0% (95% CI: 0.691-0.766), and AUC 0.771 (95% CI: 0.750-0.791). At the patient level, the classification prediction results in the test cohort were as follows: sensitivity 90.0% (95% CI: 0.541-0.995), specificity 70.0% (95% CI: 0.354-0.919), PPV 75.0% (95% CI: 0.428-0.933), NPV 87.5% (95% CI: 0.467-0.993), and AUC 0.800 (95% CI: 0.563-0.943). Conclusion: We developed and preliminarily verified the GIST mitotic count binary prediction model, based on the VGG convolutional neural network. The model displayed a good predictive performance.

• Journal of Korean Academy of Rural Health Nursing
• /
• v.19 no.1
• /
• pp.25-34
• /
• 2024

Purpose: This study investigates the relationship between job stress and burnout among primary healthcare practitioners during COVID-19 pandemic through mixed methods study. Methods: Data were collected from October to November 2022 using Qualtrix, a web-based survey platform. 1,082 primary health care practitioners participated in the survey. Quantitative data were analyzed using correlation analysis using IBM SPSS/WIN 27.0. Qualitative data were analyzed using content analysis through open-ended questions. Results: Job stress and burnout among primary healthcare practitioners during COVID-19 were positively correlated. Four categories and seven subcategories were identified. Conclusion: Based on these findings, it is necessary to develop a support system for primary healthcare practitioners according to the type of residential area and the number of peopleto reduce job stress and burnout.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.44 no.1
• /
• pp.30-39
• /
• 2024

The current survey form of grassland has not played its role in managing the grassland effectively because of the ambiguous questionnaire items and the absence of method and time of the investigation. Therefore, this study was conducted to clarify and add the items for effective of grassland management. The survey form of grassland was regulated in Article 16 of the Enforcement Rules of the Grassland Act (Survey on Grasslands Management Status, etc.). The five contents that needed improvement were the grassland owner, the survey timing and method of established grassland, grassland used livestock, grassland usage condition, and grassland grade. In the improved survey form of grassland, the grassland owner was changed to the grassland manager. In addition, 'Survey by each land' was added to the improved survey form in which the managers can survey each land. The dimension of each grassland establishment method was deleted in the grassland establishment time and method. In the livestock using grassland, the number of livestock and the area where livestock are used were added, and the number of other livestock was added, too. The grassland grade was decided as the combined score by three evaluation categories; grassland usage, the ratio of forage production in grassland and kinds of forage. The high, middle, and low grades were over 8, 6~7, and under 5 points in the combined score, respectively. The results show that the changed survey form of grassland can make grassland management more efficient by materializing the subject of grassland management and the survey terminology and methods.

• Journal of Distribution Science
• /
• v.9 no.2
• /
• pp.111-122
• /
• 2011

The purpose of this study is to survey the successful cases of small and medium Business Systematization Cognition by examining their entrepreneurial characteristics and analysing the factors affecting their success. To that end, previous studies on the association types of small businesses were studied. A research model was developed, and research hypotheses for an empirical analysis were established upon it. Suh et al. (2010) insist on the importance of Small Business Systematization in Korea but also show that small business performance is suffering: they are too small to stand alone. That is why association is so crucial for them: they must stand together. Unfortunately, association is difficult, as they have few specific links and little motivation. Even in franchising networks, association tends to be initiated by big franchisers, not small ones. In that sense, association among small businesses is crucial for their long-term survival. With this in mind, this study examines how they think and feel about the issue of 'Industrial Classification', how important Industrial Classification is to their business success, and what kinds of problems it raises in the markets. This study seeks the different cognitions among the association types of small businesses from the perspectives of participation motivation, systematization expectation, policy demand level, and management performance. We assume that different industrial classification types of small businesses will have different cognitions concerning these factors. There are four basic industrial classification types of small businesses: retail sales, restaurant, service, and manufacturing. To date, most of the studies in this area have focused on collecting data on the external environments of small businesses or performing statistical analyses on their status. In this study, we surveyed 4 market areas in Busan, Masan, and Changwon in Korea, where business associations consist of merchants, shop owners, and traders. We surveyed 330 shops and merchants by sending a questionnaire or visiting. Finally, 268 questionnaires were collected and used for the analysis. An ANOVA, T-test, and regression analyses were conducted to test the research hypotheses. The results demonstrate that there are differences in cognition depending upon the industrial classification type. Restaurants generally have a higher cognition concerning job offer problems and a lower cognition concerning their competitiveness. Restaurants also depend more on systematization expectation than do the other industrial classification types. On the policy demand level, restaurants have a higher cognition. This study identifies several factors that are contributing to management performance through differences in cognition that depend upon association type: systematization expectation and policy demand level have positive effects on management performance; participation motivation has a negative effect on management performance. We confirm also that the image factors of different cognitions are linked to an awareness of the value of systematization and that these factors show sequential and continual patterns in the course of generating performances. In conclusion, this study carries significant implications in its classifying of small businesses into the four different associational types (retail sales, restaurant, services, and manufacturing). We believe our study to be the first one to conduct an empirical survey in this subject area. More studies in this area will likely use our research frameworks. The data show that regionally based industrial classification associations such as those in rural cities or less developed areas tend to suffer more problems than those in urban areas. Moreover, restaurants suffer more problems than the norm. Most of the problems raised in this study concern the act of 'associating itself'. Most associations have serious difficulties in associating. On the other hand, the area where they have the least policy demand is that of service types. This study contributes to the argument that associating, rather than financial assistance or management consulting, promotes the start-up and managerial performance of small businesses. This study also has some limitations. The main limitation is the number of questionnaires. We could not survey all the industrial classification types across the country because of budget and time limitations. If we had, we could have produced many more useful results and enhanced the precision of our analysis. The history of systemization is very short and the number of industrial classification associations is relatively low in Korea. We should keep in mind, though, that this is very crucial to systemization entrepreneurs starting their businesses, as it can heavily affect their chances of success. Being strongly associated with each other might be critical to the business success of industrial classification members. Thus, the government needs to put more effort and resources into supporting the drive of industrial classification members to become more strongly associated.

• (The) Research of the performance art and culture
• /
• no.36
• /
• pp.441-471
• /
• 2018

East Coast Gut, Korean shamanism ritual on its east coastal area, is a Gut held in fishing villages alongside Korean east coastal area from Goseong area in Gangwon-Do to Busan area. East Coast Gut is performed in a series mainly by a successor shaman, Korean shaman, who hasn't received any spiritual power from a God, and the implications of this thesis lie in that we look over the learning aspects of Seokchool Kim shaman group among other East Coast Gut successor shaman groups after dividing it into 2 categories, successor shaman and learner shaman and based upon this, we reveal the meaning of the learning aspects of East Coast Gut. For successor shamans, home means the field of education. Since they are little, they chased Gut events performing dance in a series to accumulate onsite experiences. However, in the families of successor shamans that have passed their shaman work down from generation to generation, their descendents didn't inherit shaman work any longer, which changed the way of succession and learning of shaman work. Since 1980's, Gut has been officially acknowledged as a kind of general art embracing songs, dance and music and designated as a cultural asset of the state and each city and province, and at art universities, it was adopted as a required course for its related major, which caused new learner shamans who majored in shamanism to emerge. These learner shamans are taking systematical succession lessons on the performance skills of East Coast Byeolshin Gut at universities, East Coast Byeolshin Gut preservation community, any places where Guts are held and etc.. As changes along time, the successor shamans accepted the learner shamans to pass shaman work down and changes appeared in the notion of towners who accept the performer groups of Gut and Gut itself. Unlike the past, as Gut has been acknowledged as the origin of Korean traditional arts and as the product of compresensive learning on songs, dance and music and it was designated as a national intangible cultural asset, shaman's social status and personal pride and dignity has become very high. As shaman has become positioned as the traditional artist getting both national and international recognition unlike its past image of getting despised, at the site of Gut event or even in the relation with towners, their status and the treatment they get became far different. Even towners, along with shift in shaman groups' generation, take position to acknowledge and accept the addition of new learning elements unlike the past. Even in every town, rather than just insisting on the type or the event purpose of traditional Gut, they think over on the type of festival and the main direction of a variety of Guts with which all of towners can mingle with each other. They are trying to find new meanings in the trend of changing Gut and the adaptation of new generation to this. In our reality of Gut events getting minimalized along with rapid change of times, East Coast Gut is still very actively performed in a series until now compared to Guts in other regions. This is because following the successor shamans who have struggled to preserve the East Coast Gut, the learner shamans are actively inflowing and the series performance groups preserve the origin of Gut and try hard to use Gut as art contents. Besides, the learner shamans systematically organize what they learned on shamanism from the successor shamans and get prepared and try to hand it down to descendents in the closest possible way to preserve its origin. In the future, East Coast Gut will be succeeded by the learner shamans from the last successor shamans to inherit its tradition and develop it to adapt to the times.

• Journal of Korean Society of Forest Science
• /
• v.66 no.1
• /
• pp.37-44
• /
• 1984

The study was carried out to investigate the relationship of certain socio-economic factors to the private owner's knowledge of forestry practices. The dependent variable was knowledge level in forestry, and the six independent variables were owner's age, educational level, forestland area, socio-economic status, communication and socio-psychological factors. For the study the data were collected by interviewing 258 private forest owners, and analized primarily by multiple correlation statistical technique. The sampled private owners were grouped into two categories: the common owners and model owners. 1) The average score of forestry knowledge of common owners was lower than that of model owners, and the difference was about 15 scores. The scores of other independent variables such as age, educational level, forestland area, socio-economic status, communication and socio-psychological factors of common owners were also significantly lower than those of model owners. 2) The common owner's knowledge of forestry practice were positively correlated with educational level, socio-psychological and communication variables. On the other hand, the model owner's were negatively correlated with the educational level, but positively with the socio-economic status and the socio-psychological variables. 3) The multiple correlation coefficient between the common owner's knowledge scores and six independent variables was 0.5667. About 31.46 percent of the variance of this knowledge could be explained by the communication variable, and other 1.42 percent by the socio-psychological factor. In the case of model owners, the multiple correlation was 0.5332, and about 16.62 percent of the variance of the knowledge could be explained by the communication variable, and ls.y percent by the socio-psychological factor. 4) The opportunity of communication contact through the mass media, personal communication and owner's social participation should be augmented for the effective forestry extension works, because it is one of the results of the study that the private forest owner's knowledge in forestry was greatly affected by communication variable.

• Journal of Korean Society for Atmospheric Environment
• /
• v.28 no.3
• /
• pp.233-248
• /
• 2012

The national emission from energy sector accounted for 84.7% of all domestic emissions in 2007. Of the energy-use emissions, the emission from mobile source as one of key categories accounted for 19.4% and further the road transport emission occupied the most dominant portion in the category. The road transport emissions can be estimated on the basis of either the fuel consumed (Tier 1) or the distance travelled by the vehicle types and road types (higher Tiers). The latter approach must be suitable for simultaneously estimating $CO_2$, $CH_4$, and $N_2O$ emissions in local administrative districts. The objective of this study was to estimate 31 municipal GHG emissions from road transportation in Gyeonggi Province, Korea. In 2008, the municipalities were consisted of 2,014 towns expressed as Dong and Ri, the smallest administrative district unit. Since mobile sources are moving across other city and province borders, the emission estimated by fuel sold is in fact impossible to ensure consistency between neighbouring cities and provinces. On the other hand, the emission estimated by distance travelled is also impossible to acquire key activity data such as traffic volume, vehicle type and model, and road type in small towns. To solve the problem, we applied a hierarchical cluster analysis to separate town-by-town road patterns (clusters) based on a priori activity information including traffic volume, population, area, and branch road length obtained from small 151 towns. After identifying 10 road patterns, a rule building expert system was developed by visual basic application (VBA) to assort various unknown road patterns into one of 10 known patterns. The expert system was self-verified with original reference information and then objects in each homogeneous pattern were used to regress traffic volume based on the variables of population, area, and branch road length. The program was then applied to assign all the unknown towns into a known pattern and to automatically estimate traffic volumes by regression equations for each town. Further VKT (vehicle kilometer travelled) for each vehicle type in each town was calculated to be mapped by GIS (geological information system) and road transport emission on the corresponding road section was estimated by multiplying emission factors for each vehicle type. Finally all emissions from local branch roads in Gyeonggi Province could be estimated by summing up emissions from 1,902 towns where road information was registered. As a result of the study, the GHG average emission rate by the branch road transport was 6,101 kilotons of $CO_2$ equivalent per year (kt-$CO_2$ Eq/yr) and the total emissions from both main and branch roads was 24,152 kt-$CO_2$ Eq/yr in Gyeonggi Province. The ratio of branch roads emission to the total was 0.28 in 2008.

• Journal of Korean Academy of Nursing
• /
• v.7 no.2
• /
• pp.11-21
• /
• 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 Construction Engineering and Management
• /
• v.12 no.6
• /
• pp.65-78
• /
• 2011

Construction business, which is complex and long-term business, requires accurate estimation and verification in construction costs and payment procedure from project planning to the completion of construction phase. And more importantly, it is necessary to investigate and determine the risk factors related to construction costs during the entire process including design planning, construction drawings, and quantity calculating. But, currently, it is not seem to be adequate to cope with the risk and increased construction costs against the operational budget in terms of actual costs when screening and estimating the bidding cost of public apartment. Therefore, this study selected and analyzed 40 sites' report of construction completion account from 2004 to 2010 focused on the adequacy on the modification of contract and design planning and on the complication of the budget in the beginning of the project. This study deducted various risk causes and results by analyzing actual costs according to year, architectural area, region, construction cost and sale/lease classification. We could find out construction risk according to annual variation of government policy and economy, and also deducted risk items by construction characteristic according to region and architectural area. Study result, we first found out the problems of lowest price award system according to the construction costs. The weight of the cost increase risk was analyzed that subcontract and material costs are very high. Roof and tile work were analyzed highly in subcontract cost risk and reinforcing bar and cement were analyzed highly in material cost risk, among direct construction cost. Finally, this study results could be used in comparing the categories of the construction costs made by specific construction process, belonging to the construction costs, with the operational budget made in the beginning of the project that can enable to grasp unpredictable risks over the construction costs and making quantitative analysis for it through analyzing the range of fluctuation and variations led by the fluctuations in the actual construction costs.

• Asia pacific journal of information systems
• /
• v.19 no.2
• /
• pp.157-178
• /
• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.