• Korean Journal of Occupational Health Nursing
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• v.8 no.2
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• pp.193-211
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• 1999

This study was carried out to investigate the management and support system affecting to the occupational health nursing services(OHNS) provided in group occupational health agencies(GOHA). Questionnaire was developed and distributed to 82 nurses who were working in GOHA and who agreed to participate in the survey. The results were as follow: 1. OH nurses responded were mostly in the age of twenty to thirties(89%), married(73.7%), technical college graduates(88.9%), worked in hospital(85.4%) and participated more than 1 year in group occupational health services (96.3%). 2. Fifty eight point four percent of the OH nurses worked in number of workplace more than 30 to less than 60 in the OHNS form. The figure of workplaces undertaken by nurses was ranged greatly from 9 to more than 100. Number of employees who cared by nurses were mostly under 5,000 peoples in 93.3%. The types of industry was mostly manufacturing and located in the order of factory complex area, suburban, urban and others. 3. Most OH nurses(87.8%) were fully involved in the OHNS for the SSE. Their working days to visit SSE was 5 days per week(77.8%) and one day in the GOHA at 41.3%. 4. The OH documents using by nurses were found in more than 23 different types. However, they were largely summarized in the types of 'Workplace Health Management Card', 'Personal Health Counselling Card', 'Daily Health Management Report', 'Visiting List of Workplace' and 'Sick Employee List'. 5. The items of laboratory test provided by GOHA were mostly achieved in the purpose of basic health examination. They were used to be the blood pressure check(98.8%), blood sugar test (98.8%), urine sugar and protein(91.4%), SGOT and SGPT(85.3% each), cholesterol (82.9%), hepa vaccine immunization(82.9%), r-GPT(81.7%), hemoglobin(79.3%) and triglyceride(75.5%). 6. The OH nurses(92.7%) followed the work pattern to visit the GOHA before and after small-scale enterprises(SSE) visit by car driven by nurses in 74.3%. They were payed by GOHA for transportation fees in certain amounts. However, nurse is the main person(75.0%) who covers up in case of traffic accident. If the GOHA has no transportation regulation for the formal workplace visit, data showed that nurses had been responsible to take charge(31.7%). 7. The personnel manager who takes in charge for nursing services was 'nurse' in 61.7% and 41.2% worked as the final decision maker related to nursing work. The OH nurses' opinions about factors affecting to the management were classified in the four areas such as 'Nature(Quality) of health professional'. 'Content of OHNS', 'Delivery system of the GOHS', and 'Others'. The factors were indicated highly in 'Authority as health professional', 'Level of perception of director on the OH' and 'Physical work condition for OHNS'. The things that this study suggests in the recommendation would be summarized in such as the management and supporting system working for SSE in the OHNS is necessary to reform thoroughly. The reconsidered aspects might be in the matters of number of workplaces undertaken by nurses, development of effectively practical health documents, preparation for guideline of the laboratory test in the workpleces, establishment of convenient and encouraging support system and cooperation between other health professionals with respect and skill.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.39-58
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• 2014

As the importance of big data and related technologies continues to grow in the industry, it has become highlighted to visualize results of processing and analyzing big data. Visualization of data delivers people effectiveness and clarity for understanding the result of analyzing. By the way, visualization has a role as the GUI (Graphical User Interface) that supports communications between people and analysis systems. Usually to make development and maintenance easier, these GUI parts should be loosely coupled from the parts of processing and analyzing data. And also to implement a loosely coupled architecture, it is necessary to adopt design patterns such as MVC (Model-View-Controller) which is designed for minimizing coupling between UI part and data processing part. On the other hand, big data can be classified as structured data and unstructured data. The visualization of structured data is relatively easy to unstructured data. For all that, as it has been spread out that the people utilize and analyze unstructured data, they usually develop the visualization system only for each project to overcome the limitation traditional visualization system for structured data. Furthermore, for text data which covers a huge part of unstructured data, visualization of data is more difficult. It results from the complexity of technology for analyzing text data as like linguistic analysis, text mining, social network analysis, and so on. And also those technologies are not standardized. This situation makes it more difficult to reuse the visualization system of a project to other projects. We assume that the reason is lack of commonality design of visualization system considering to expanse it to other system. In our research, we suggest a common information model for visualizing text data and propose a comprehensive and reusable framework, TexVizu, for visualizing text data. At first, we survey representative researches in text visualization era. And also we identify common elements for text visualization and common patterns among various cases of its. And then we review and analyze elements and patterns with three different viewpoints as structural viewpoint, interactive viewpoint, and semantic viewpoint. And then we design an integrated model of text data which represent elements for visualization. The structural viewpoint is for identifying structural element from various text documents as like title, author, body, and so on. The interactive viewpoint is for identifying the types of relations and interactions between text documents as like post, comment, reply and so on. The semantic viewpoint is for identifying semantic elements which extracted from analyzing text data linguistically and are represented as tags for classifying types of entity as like people, place or location, time, event and so on. After then we extract and choose common requirements for visualizing text data. The requirements are categorized as four types which are structure information, content information, relation information, trend information. Each type of requirements comprised with required visualization techniques, data and goal (what to know). These requirements are common and key requirement for design a framework which keep that a visualization system are loosely coupled from data processing or analyzing system. Finally we designed a common text visualization framework, TexVizu which is reusable and expansible for various visualization projects by collaborating with various Text Data Loader and Analytical Text Data Visualizer via common interfaces as like ITextDataLoader and IATDProvider. And also TexVisu is comprised with Analytical Text Data Model, Analytical Text Data Storage and Analytical Text Data Controller. In this framework, external components are the specifications of required interfaces for collaborating with this framework. As an experiment, we also adopt this framework into two text visualization systems as like a social opinion mining system and an online news analysis system.

• 대한공업교육학회지
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• v.41 no.2
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• pp.48-68
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• 2016

This study was conducted to identify the NCS-related research trends, Keywords, the Keywords Networks and the extension of the Keywords using the sementic network analysis and to seek for the development plans about NCS. For this, the study searched 345 the papers, with the National Competency Standards or NCS as a key word, among master's theses, dissertations and scholarly journals that RISS provides, and selected a total of 345 papers. Annual frequency analysis of the selected papers was carried out, and Semantic Network Analysis was carried out for 68 key words which can be seen as key terms of the terms shown by the subject. The method of analysis were KrKwic software, UCINET6.0 and NetDraw. The study results were as follows: First, NCS-related research increased gradually after starting in 2002, and has been accomplishing a significant growth since 2014. Second, as a result of analysis of keyword network, 'NCS, development, curriculum, analysis, application, job, university, education,' etc. appeared as priority key words. Third, as a result of sub-cluster analysis of NCS-related research, it was classified into four clusters, which could be seen as a research related to a specific strategy for realization of NCS's purpose, an exploratory research on improvement in core competency and exploration of college students' possibility related to employment using NCS, an operational research for junior college-centered curriculum and reorganization of the specialized subject, and an analysis of demand and perception of a high school-level vocational education curriculum. Fourth, the connection forming process among key words of domestic study results about NCS was expanding in the form of 'job${\rightarrow}$job ability${\rightarrow}$NCS${\rightarrow}$education${\rightarrow}$process, curriculum${\rightarrow}$development, university${\rightarrow}$analysis, utilization${\rightarrow}$qualification, application, improvement${\rightarrow}$plan, operation, industry${\rightarrow}$design${\rightarrow}$evaluation.'

• KDI Journal of Economic Policy
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• v.14 no.2
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• pp.29-54
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• 1992

Recent studies on the economic effects of trade liberalization and economic integration have emphasized the significant gains associated with product differentiation and scale economies. Securing access to markets in other countries will make it possible to increase product variety and capture scale economies, thus, expanding the gains from trade. Liberalization is also expected to introduce foreign competition into the previously closed market. Concurrently, the liberalization will improve the competitive market environment for firms selling in the domestic market. Firms will be pressed to either exit or reduce cost. The output per firm, then, will increase due to the exit of rival firms, and the average total cost will decline due to the economies of scale. 'Rationalization' of the production process will eventually follow. This paper addresses the economic effects of (counterfactual) bilateral tariff elimination between Korea and Japan. It computationally assesses the gains from liberalization as well as the resource allocations and welfare effects associated with the tariff reduction. The endogenous determination of the key parameters distinguishes this paper from others. The firm's perceived elasticity of demand and elasticity of substitution in the present model are calibrated to be consistent with the base year data. Korea, Japan, and the rest of the world are modeled explicitly. The sectoral coverage of the model includes twenty-three tradable product categories based on three-digit SITC industries and seven nontradable categories based on one-digit SITC industries. Product categories are also classified into perfectly competitive and imperfectly competitive ones. In the imperfectly competitive industries, product differentiation exists at the firm level, while the perfectly competitive industries are characterized by national product differentiation. The simulation results of bilateral tariff reduction are reported. Tariff elimination tends to increase intra-industry trade flows so that the total amount of exports and imports of both countries expand. Yet, Japan is expected to increase the bilateral trade surplus in the wake of the mutual tariff reduction. Terms-of-trade for Korea will not change, while for Japan it will deteriorate. Equivalent variations reflecting the change in consumer surplus (welfare) will favor Korean consumers. Total output, however, will not change substantially, recording 0.5 and 0.6% for Japan and Korea, respectively. An interesting finding in the analysis is that the gains from increased competition and scale efficiency are not as prevailing as expected in theory.

• The Journal of Natural Sciences
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• v.7
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• pp.91-101
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• 1995

To establish the simple and practical test method of estimating resistance of rice varieties against rice leafblight, trials were made to correlate among the four test methods such as true resistance test,secondaryinfection test, secondary epidemic test and field test. The results obtained through the experiment on 25 ricevarieties and 3 pathogenic isolates designated to HB9O11, HB9022 and HB9033 can be summarized asfollows. 1 .Based on the results of true resistance test, 25 rice varieties can be classified into four groups:1 )Samgang variety group ;resistant to HB9011, 13 varieties, 2)Pungsan variety group ; resistant to HB9011 and HB9022, 5 varieties, 3)Samgang variety group ; resistant to all three isolates, 2 varieties, 4)Unbongvariety group: sensitive to all three isolates, 12 varieties. 2. The responses of rice varieties to isolates showed some discrepancies among on the test methods. These examples were found in 3 varieties including Yeongdeog varieties to HB9011, 3 varieties including Taebaeg variety to HB9022 and Taebaek vaieties to HB9033. 3. Correlation coefficiences between the secondary infection test and the secondary epidemic test for HB9011, HB9022 and HB9033 were 0.972, 0.894 and 0.919, respectively. It suggests that the two methods are not significantly different so that one of the two methods are not significantly different so that one of the two methods can be omitted from resistant test without affecting the result. 4. Between the true resistance test and the field test at the disease common area, there were no significant correlations. Unbong, Chucheong and Yeongdeog varieties are appeared as resistant varieties in the true resistant test, but their responses in the field test were different and appeared as sensitive varieties. 5. The disease index was used to express theresults from four test methods. The disease index was calculated as the sum of each numerical values of theresults from the four test methods by giving the same weights(0 to 25)to each test method. If the disease index for certain variety is less than 15, then the variety is considered to be resistant. 4 varieties such as Seohae, Hwajin, Yeongdeog and Pungsan varieties-disease indices were less than 15 were selected as field resistance varieties.

• Journal of Korean Society of Forest Science
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• v.103 no.1
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• pp.129-136
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• 2014

This study aims to investigate the effect of frequency of using forest environment on workers' stress. Workers in medical and counseling industry, which is recently known to require heavy emotional burden and thus cause a lot of stress and burnout syndrome, participated in the study. We classified 370 subjects, who were working at medical and counseling service institutions in Seoul metropolitan area, into two groups according to frequency of using forest environment by conducting a screening survey. 69 subjects submitted written consent and were recruited for either forest therapy program or control-group test; the "high" group (n=27) at the high frequency of using forest environment and the "low" group (n=42) at the low level. We measured the level of stress by using psychosocial indicators such as Worker's Stress Response Inventory (WSRI), Recovery Experience Questionnaire (REQ), and Maslach Burnout Inventory-General Survey (MBI-GS) and biological ones such as heart rate variability (HRV), cortisol, and Natural Killer cell (NK cell). The results suggested that the level of stress differed by frequency. The "high" group showed significantly low scores in the depression and work sub-scale and the total score of WSRI, emotional exhaustion, professional efficacy and total score of MBI-GS, and high scores in the total score of REQ. Similar tendencies were observed in the most of other indicators of psychosocial measures. Regarding the biological indicators, the "high" group showed the highest SDNN, RMSSD and TP measures of HRV and NK Cell activity and the low cortisol, although the statistical power did not reach the significant level. Our results suggest that the subjects who use forest environment frequently show favorable stress level both psychologically and biologically.

• Journal of the Korean Society of Food Science and Nutrition
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• v.31 no.3
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• pp.492-499
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• 2002

The objective of this study is to identify the attribute factors for fast food selection according to their characteristics of the use behaviors and demographics. The results of these findings suggest the attribute factors for selection were classified into ten : physical service, cleanliness/promptness, human service, convenience/promotion, accessibility, menu variety, food quality, service for child and parking, added service, and comfortness. “Cleanliness” and “good taste” were considered as determining factors in selecting a fast food restaurant. According to the consumer's use behaviors and demographics, attribute factors for fast food selection were significantly different. Therefore, the marketers and managers on the fast food industry should develop their own appropriate marketing strategies and implement effective targeting, positioning, and promotional strategies.

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

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

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.

• Journal of agriculture & life science
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• v.46 no.5
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• pp.73-82
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• 2012

Allele information from the analysis of the 13 microsatellite (MS) markers, were classified into the $F_0$, $F_1$ and $F_2$ generations, and probabilities of the same individual emergency in each generation was calculated. As a result, the 13 MS markers showed an estimate of $3.84{\times}10^{-23}$ on the premise of the randomly mated group of $F_2$, which implies that the same individuals may emerge by the use of 37 kinds of SNP markers. In this study, the experimental pigs were intercross between only 2 breeds (Korean native pig and Landrace). In addition, the success rate of paternity tests was analyzed on the whole group, by the use of the 13 MS markers and 37 SNP markers. As regards the exclusionary power of the second parent ($PE_{pu}$), MS markers and SNP markers showed 0.97897 and 0.99149, respectively. In relation to the parent exclusion power of both parent (PE), MS markers and SNP markers showed 0.99916 and 0.99949, respectively. In the case of the estimate to identify parental candidates that had the highest probability ($PNE_{pp}$), the two showed 1.00000 all. The Korean pig industry tends to mass produce hogs with limited numbers of alleles in limited parents. Such being the case, there is a need to organize a marker, for which it is imperative to find markers with high efficiency and high economic feasibility of the characteristics of DNA markers, sample size, the accuracy and expenses of genotyping cost, the manageability of data and the compatibility among analysis systems.