• Journal of Korean society of Dental Hygiene
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• v.11 no.3
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• pp.325-341
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• 2011

Objectives : This research has investigated the reality of the education of the claim and the degree of the education for the claimed of the dentistry recuperation organization in the Daejeon and Chuncheong are for the improvement of the problem in the medical expenses. Methods : It use as a basic data for the vitalizations of the education and performed the survey in the dentistry recuperation organization in the Daejeon and ChungCheong Nam BukDo which are registered in the evaluating organization for judging the health insurance in the present May 2010, and concluded just like the below. Results : 1. The education of the claim in the requirer in the dentistry recuperation organization, and the education of the claim was especially lacking when the dentist was studying in the university, and the dental hygienist had the similar educational experience in the school and the clinic (p<0.05) 2. Most of the requirer in the dental recuperation organization was hoping to get the education related to the claim work, but the dentist and the nurse's aid was relatively low (p<0.05) 3. For fixing the error of the claim, the participation and the extension of the judging standard of the insurance was the highest among the university subordinate dental hospital/dental hospital, but the health center was relatively low (p<0.05). 4. The dentist feels the economic burden in employing the special employee because the raising of the special judging people, compared to others, but the staffs such as the dental hygienist preferred it as one of ways to fix the error of the claim of the dental insurance (p<0.05) 5. Both dentists and the dental hygienist said proper time to teach the insurance was all needed in the school, and the clinic, but other workers relatively believed it should be held in the clinic (p<0.05). 6. The important factors to decide the participation of the lecture was in order of the contents of the lecture, the place of the lecture, the amount for the lecture, the superintendent of the lecture, whether it has gone through the educational score, and whether it has passed the conserving educational score was relatively less important in the university subordinate dentist/dentist, but the medical center was very effective as 4.50 (p<0.05) 7. Health Insurance Review and assessment service was very high as the managing department for supplying the lecture and the information, 70.5%, and the next was the Korean Dental Association/ Korean dental hygiene association, but dentists were preferring the association to manage in than the Health Insurance Review and assessment service to manage (p<0.05) 8. In preferring lecture for the inquiring the insurance, periodontal surgery was the highest as 4.51, the diagnosis standard for injection was high in the university subordinate hospital/dentists, and the more the year of the insurance inquiry, the less the doctor who was hoping for the lecture about the basic treatment. Conclusions : Taken together, it is decided that the inquiry education about the medical expense in the dentist, so the consistent and systematic education should be held to the related people, and from this, it is thought to reduce the problem of the inquiry of the medical expenses by fostering the knowledge and supplying the information which are related to the inquiry of the dentists.

• The Korean Journal of Archival Studies
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• no.66
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• pp.229-265
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• 2020

This study examined the necessity of establishing a family archive as a means for the recovery of the family community and the direction for establishing the family archive as a social culture. With the lack of research on family archives worldwide, this study analyzed family archives focusing on three areas. The first is a review on the necessity of family archives. To this end first, studies in the fields of sociology and family studies were analyzed to understand the situation in which the crisis of the family community intensified in the recent social environment, and based on this analysis, the necessity of establishing a family archive using records in Korean society was suggested. The second is case studies of National Archives of advanced countries for social expansion of family archives. In the case of advanced countries in Western, family archives are closely related to family history or genealogy research, and more than half of visitors to archives are occupied by family history or genealogy researchers. This is because National Archives of Western countries provide a variety of services for building family archives. The third is an analysis of the meaning and characteristics of family archives. This is because in order for the family archive to become a pan-social recording culture, it is necessary to establish the values and roles of the family archive along with its own meaning and characteristics different from the existing public records. Accordingly, the aim was to establish the concept and goal of the family archive, and to explore the functions and values of the family archive in comparison with the existing theories of archives. As a result of the analysis focusing on these three areas, the family archive needs to focus on 'culture', not 'institution', and 'utilization' rather than 'management'. Theories and methodologies of archival science have been developed with an emphasis on systematically managing and preserving a vast amount of records like public records, and based on highly specialized knowledge, records management has been established as an institution. However, in order to spread the family archive socially, it must be established as a culture or lifestyle that can be practiced by all ordinary citizens in the process of daily life. Prior to the management and preservation of professional records, all members of the family must understand the meaning contained in the records. It is necessary to prioritize use so that they can be shared.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.240-247
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• 2017

The increased investigation of the cerebral arteries with magnetic resonance angiography has resulted in an increase in the identification of unruptured intracranial aneurysms (UIAs). Knowledge of the distribution and factors associated with UIAs might be helpful for understanding the pathological mechanism of unruptured aneurysms. This study examined patients who visited a health care center and had a health examination from January 2007 to December 2016. Subjects who underwent magnetic resonance angiography with a health examination at the Health Screening were enrolled in this study. The incidence and risk factors of UIAs (age, sex, hypertension, diabetes mellitus, smoking, alcohol, and coronary artery disease) were investigated by comparing the size (more than 3 mm vs. less than 3 mm) and multiple aneurysm (single vs. multiple aneurysms). The frequency of aneurysm according to the site was also analyzed. Among the 187166 subjects, who received a health examination, 18954 underwent magnetic resonance angiography. Of them, 367 (1.93%) had UIAs. A comparison of the size of more than 3 mm and less than 3 mm showed that the mean age of the more than 3 mm group of patients was significantly higher than the other size groups (more than 3 mm $57.16{\pm}8.47$ vs. less than 3 mm $55.12{\pm}8.19$; p=0.07). High-density lipoprotein was significantly higher in the more than 3 mm group than in the less than 3 mm($55.95{\pm}16.03$ vs. less than 3 mm $50.85{\pm}13.65$; p=0.007). Hypertension was significantly higher in the multiple aneurysm group (single 153 in 399 (38.3%) VS multiple 19 in 35 (54.3%); p=0.065). An aneurysm of less than 3 mm in size was frequent in the distal internal carotid artery (34.3%) and MCA-bifurcation (16.4%) (p=0.003). Aneurysms of more than 3 mm were frequent in the distal internal carotid artery (43.4%) and MCA-bifurcation (13.4%), and anterior communicating artery (13.4%) (p=0.003). The difference in size and single or multiple aneurysm revealed other risk factors. These risk factors suggest that degenerative and hemodynamic disorders may lead to the presence of aneurysms.

• Journal of Nutrition and Health
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• v.51 no.3
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• pp.228-241
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• 2018

Purpose: The health risk of women increases after menopause. This study evaluated the effectiveness of a public health center-based nutrition education program for hypertension in women older than 50 years of age. Methods: The program included 8-week nutrition education and 8-week follow-up with keeping a health diary and nutrition counseling. The program was evaluated three times: before and after the nutrition education, and after the follow-up. The subjects were classified into hypertensives (n = 44) or normotensives (n = 71). Results: The rate of taking antihypertensive drugs in the hypertensive group was 86.4%. The systolic blood pressure decreased in the hypertensive and normotensive groups after nutrition education (p < 0.05). The body weight (p < 0.001), BMI (p < 0.001), waist circumference (p < 0.001), and percent body fat (p < 0.01) were also decreased after nutrition education in both groups. The hypertensive group showed an increase in HDL-cholesterol level (p < 0.001) and decreases in triglycerides (p < 0.01) and LDL-cholesterol (p < 0.05) levels after completion of the program. The normotensive group also displayed significant changes in HDL-cholesterol (p < 0.001) and triglycerides (p < 0.01). The dietary habits and nutrition knowledge on sodium and hypertension were improved in both groups (p < 0.001). The total score of dietary behavior related to the sodium intake was improved in the normotensive group (p < 0.001). The total score of the high sodium dish frequency questionnaire decreased in both groups after nutrition education and completion of the program compared to that before the program. Decreases in the consumption frequencies of noodles, pot stews and stews, Kimchi, and beverages were significant. The total self-efficacy score was increased in both groups by the program (p < 0.001). In particular, the hypertensive group showed improvement in all items. Conclusion: This public health center-based nutrition education program may contribute to the prevention and management of hypertension and chronic diseases in women over 50 years of age.

• Restorative Dentistry and Endodontics
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• v.34 no.2
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• pp.87-94
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• 2009

The purpose of this study was to assess the current materials, methods and difficulties according to the year of licence and educational background of Korean dentists in Class II direct composite resin restorations. Total 17 questions were included in the questionnaire. Questions were broadly divided into two parts: first. operator's information. and second. the materials and methods used in Class II posterior composite restoration. The questionnaire was sent to dentists enrolled in Korean Dental Association via e-mail. Total 12,193 e-mails were distributed to dentists. 2,612 e-mails were opened, and 840 mails (32.2%) were received from respondents. The data was statically analyzed by chi-square test using SPSS(v. 12.0.1, SPSS Inc. Chicago, IL, USA). Male dentists among respondents was 79%. 60.3% of the respondents acquired their licences recently (1998-2007), and 77% practiced in private offices. 83.4% have acquired their knowledge through school lectures, conferences and seminars. For the Class II restorations, gold inlays were preferred by 65.7% of respondents, while direct composite resin restorations were used by 12.1 % amalgam users were only 4.4% of respondents. For the restorative technique, 74.4% of respondents didn't use rubber dam as needed. For the matrix. mylar strip (53.4%), metal matrix (33.8%) and Palodent system (6.5%) were used. 99.6% of respondents restored the Class II cavity by incremental layering. Obtaining of the tight interproximal contact was considered as the most difficult procedure (57.2%) followed by field isolation (21 %). Among various bonding systems, 22.6% of respondents preferred SE Bond and 20.2% used Single Bond. Z-250 was used most frequently among a variety of composite resins.

• 대한공업교육학회지
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• v.45 no.1
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• pp.63-83
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• 2020

The purpose of this study is to provide the basic materials needed to plan the NCS Learning Module to be used effectively in practical courses. In this study, teachers and students' satisfaction surveys were collected about the NCS (National Competency Standards) learning module, career and field practice, practical environment used in the construction subject course. This study was conducted on public high schools in Chungcheong province (including Daejeon), which is operating practice course using the NCS learning module. The research questions are as follows; First, how was the satisfaction of teachers and students in the practical subject class using NCS learning module? Second, what is the degree of satisfaction of teacher's career and field practice guidance, student's career decision and field practice after the practical course using NCS learning module? Third, the satisfaction level of the developed NCS learning module and practical subject class using the same was determined by setting whether the number of training of NCS-related teachers or the presence or absence of on-the-job training of students were affected? The results of the study are as follows; As a result of comparing the teachers' and students' satisfaction, the students showed satisfaction in all items, whereas the teachers showed 'content level', 'interest', 'necessary knowledge', 'skill acquisition', 'Improvement of practical skills (level of skill performance)', 'scale of experimental practice', and 'items of experimental practice equipment' were dissatisfied. It was found that the number of NCS related teachers' training (or absence) or the presence of students on the field had an effect on the satisfaction of the developed NCS learning module and the practical course using it. In order to fully utilize the developed NCS learning module in the practical course, it is required to develop and construct the teaching material of the teacher who can serve as an intermediary for conceptualization and understanding of job skills. It is necessary to increase the number of education and training specialists to positively reflect the demands of the education field.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.99-118
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• 2015

Object-oriented programming languages have been widely selected for developing modern information systems. The use of concepts relating to object-oriented (OO, in short) programming has reduced efforts of reusing pre-existing codes, and the OO concepts have been proved to be a useful in interpreting system requirements. In line with this, we have witnessed that a modern conceptual modeling approach supports features of object-oriented programming. Unified Modeling Language or UML becomes one of de-facto standards for information system designers since the language provides a set of visual diagrams, comprehensive frameworks and flexible expressions. In a modeling process, UML users need to consider relationships between classes. Based on an explicit and clear representation of classes, the conceptual model from UML garners necessarily attributes and methods for guiding software engineers. Especially, identifying an association between a class of part and a class of whole is included in the standard grammar of UML. The representation of part-whole relationship is natural in a real world domain since many physical objects are perceived as part-whole relationship. In addition, even abstract concepts such as roles are easily identified by part-whole perception. It seems that a representation of part-whole in UML is reasonable and useful. However, it should be admitted that the use of UML is limited due to the lack of practical guidelines on how to identify a part-whole relationship and how to classify it into an aggregate- or a composite-association. Research efforts on developing the procedure knowledge is meaningful and timely in that misleading perception to part-whole relationship is hard to be filtered out in an initial conceptual modeling thus resulting in deterioration of system usability. The current method on identifying and classifying part-whole relationships is mainly counting on linguistic expression. This simple approach is rooted in the idea that a phrase of representing has-a constructs a par-whole perception between objects. If the relationship is strong, the association is classified as a composite association of part-whole relationship. In other cases, the relationship is an aggregate association. Admittedly, linguistic expressions contain clues for part-whole relationships; therefore, the approach is reasonable and cost-effective in general. Nevertheless, it does not cover concerns on accuracy and theoretical legitimacy. Research efforts on developing guidelines for part-whole identification and classification has not been accumulated sufficient achievements to solve this issue. The purpose of this study is to provide step-by-step guidelines for identifying and classifying part-whole relationships in the context of UML use. Based on the theoretical work on Meta-model Formalization, self-check forms that help conceptual modelers work on part-whole classes are developed. To evaluate the performance of suggested idea, an experiment approach was adopted. The findings show that UML users obtain better results with the guidelines based on Meta-model Formalization compared to a natural language classification scheme conventionally recommended by UML theorists. This study contributed to the stream of research effort about part-whole relationships by extending applicability of Meta-model Formalization. Compared to traditional approaches that target to establish criterion for evaluating a result of conceptual modeling, this study expands the scope to a process of modeling. Traditional theories on evaluation of part-whole relationship in the context of conceptual modeling aim to rule out incomplete or wrong representations. It is posed that qualification is still important; but, the lack of consideration on providing a practical alternative may reduce appropriateness of posterior inspection for modelers who want to reduce errors or misperceptions about part-whole identification and classification. The findings of this study can be further developed by introducing more comprehensive variables and real-world settings. In addition, it is highly recommended to replicate and extend the suggested idea of utilizing Meta-model formalization by creating different alternative forms of guidelines including plugins for integrated development environments.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• 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.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.