• The Journal of Korean Academy of Prosthodontics
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• v.57 no.3
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• pp.203-210
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• 2019

Purpose: The purpose of this study was to verify the effect of the abutment superimposition process on the final virtual model in the scanning process of single and 3-units bridge model using a dental model scanner. Materials and methods: A gypsum model for single and 3-unit bridges was manufactured for evaluating. And working casts with removable dies were made using Pindex system. A dental model scanner (3Shape E1 scanner) was used to obtain CAD reference model (CRM) and CAD test model (CTM). The CRM was scanned without removing after dividing the abutments in the working cast. Then, CTM was scanned with separated from the divided abutments and superimposed on the CRM (n=20). Finally, three-dimensional analysis software (Geomagic control X) was used to analyze the root mean square (RMS) and Mann-Whitney U test was used for statistical analysis (${\alpha}=.05$). Results: The RMS mean abutment for single full crown preparation was $10.93{\mu}m$ and the RMS average abutment for 3 unit bridge preparation was $6.9{\mu}m$. The RMS mean of the two groups showed statistically significant differences (P<.001). In addition, errors of positive and negative of two groups averaged $9.83{\mu}m$, $-6.79{\mu}m$ and 3-units bridge abutment $6.22{\mu}m$, $-3.3{\mu}m$, respectively. The mean values of the errors of positive and negative of two groups were all statistically significantly lower in 3-unit bridge abutments (P<.001). Conclusion: Although the number of abutments increased during the scan process of the working cast with removable dies, the error due to the superimposition of abutments did not increase. There was also a significantly higher error in single abutments, but within the range of clinically acceptable scan accuracy.

• Journal of the Korean Society for information Management
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• v.36 no.1
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• pp.137-168
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• 2019

This study measures and analyzes the university library user's sense of community, service quality assessment, user satisfaction and loyalty. In addition, the effect of the university library user's sense of community on university library user satisfaction and loyalty mediated by the assessment of the quality of service is investigated. On the basis of study result, to improve user satisfaction and user loyalty, the direction and implications of library development are presented. In order to achieve the purpose of the study, precedent research and literature were investigated, and the study model and hypothesis were established based on theoretical background. In order to verify the hypothesis, a total of 300 questionnaires were distributed to subject who had experience using the Central Library among undergraduate students at the C National University, and the final 282 sample was used for analysis. To analyze the differences depending on the general characteristics of the samples, It is the result of an independent sample t-test and one-way ANOVA. The results of the mediated effects analysis using the PROCESS macro-programs models 4 and 6 of Hayes for hypothesis testing are as follows. First, The university library user's sense of community (Service Benefits Perception and Satisfaction, Mutual sense of influence) effect the user satisfaction of university library mediated by service quality assessment at statistical significance. This showed that the higher the university library user's sense of community, the higher the service quality assessment, and the higher the user satisfaction level of university library. Second, The university library user's sense of community (Service Benefits Perception and Satisfaction, Mutual sense of influence) effect the user loyalty of university library mediated by service quality assessment and user satisfaction. This showed that the higher the university library user's sense of community, the higher the service quality assessment, the higher user satisfaction level of university library and the higher the user loyalty level of university library. The results of this study showed that the university library user's sense of community has a direct and indirect effect on enhancing user satisfaction and loyalty through the service quality assessment.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Phonetics and Speech Sciences
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• v.11 no.1
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• pp.9-18
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• 2019

The purpose of this study is to determine whether the mean fundamental frequency (F0) changes depending on language, task, or language proficiency for Korean-English bilinguals. A total of forty-eight Korean-English speakers (28 balanced bilinguals and 20 Korean dominant bilinguals) participated in the study. Participants were asked to read aloud two types of tasks in English and Korean. For statistical analyses, the language ${\times}$ task two-way repeated ANOVAs were conducted within the balanced bilingual group first, and then group ${\times}$ language two-way mixed ANOVAs. The results showed that the females in both bilingual groups changed their mean F0 depending on the language they used and the tasks (p<.05), whereas no significant results were found in the males in either group under any conditions. The mean fundamental frequency in the Korean reading task was significantly higher than that in the English reading task for females in both balanced and Korean dominant bilingual groups. Thus, changes in mean F0 depending on language and context may reflect gender-specific characteristics, and females seem to be more sensitive to the socio-cultural standards that are imposed on them.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.29-41
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• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

• The Korean Journal of Archival Studies
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• no.46
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• pp.153-187
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• 2015

This study aims to discuss issues about non-existent information of the information disclosure system and to provide alternative strategies for the issues. For the theoretical discussion it reviews the definitions and standards of non-existent information and analyzes legal aspects and statistical changes of non-existent information. Furthemore, in order to discuss a current status and problems of non-existent information at the central administrative agencies, it analyzes the cases of the non-existent information notification. According to analysis results, non-existent information status of the surveyed institutions is a total of 4,421 cases for three years and it shows the continuous increasing trend year after year. The number of institutions that have the number of non-existent information equal to the number of nondisclosures or over it reached about 40%. It means excluding non-existent information from the reasons of nondisclosure influenced disclose rates and nondisclosure rates of many agencies. In the type analysis of the non-existent information reasons, the most main reason, the case of not producing or receiving the requested information by public institutions takes over 75% among the whole reasons. The next reason is the case of collecting or processing information takes over 7-10%. This study found the operational issues, as analyzing notifications of non-existent information. The operational issues are 1) the incomplete explanation of non-existent information, 2) the unclear scope of the collection and processing, 3) the problem of the transfer processing, and 4) the problem of recording management. Therefore, this study suggested some improvements of the perspective and the technical and procedural aspects. First, information disclosure issues including non-existent information are to be understood as an extension of records management. Second, disclosure service should improve overall based on advanced understanding. Third, the management procedures of non-existent information should be improved. Fourth, specific guidelines for handling non-existent information should be developed.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.2
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• pp.92-96
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• 2018

Purpose In case of nuclear medical hepatobiliary scan, To quantitatively evaluate contractility of a gallbladder, gallbladder ejection fraction (GBEF%) is calculated from anterior images using fatty meal. However, when a gallbladder and other organs overlap on an anterior image, the gallbladder ejection fraction is not accurately evaluated. In order to reduce this error, the objective of our study was to figure out whether there is a significant difference in GBEF% calculated from the anterior and right lateral images. Materials and Methods After intravenous injection of 99mTc-Mebrofenin 370 MBq to randomly 50 patients who visited our hospital, we started to examine nuclear hepatobiliary scan. Using skylight(Philips, United States), we acquired anterior and right lateral image at 10 minutes, 20 minutes, 30 minutes, 60 minutes, 90minutes after injection. Using images at 60 and 90 minutes, gallbladder ejection fraction (GBEF%) was calculated from the anterior and right lateral images using JETstream workspace. For drawing more accurate ROI, CT images were referenced and 4 radiologists calculated the GBEF% in the same image and calculated the average value. We assessed whether there was a significant difference in GBEF% calculated from the anterior and right lateral images using SPSS program(Statistical Package for the Social Science, SPSS Ver.18 Inc. USA). Results About randomly 50 patients, the average value of the GBEF% calculated from the anterior image was 63.212 and the average value of the GBEF% calculated from the right lateral image was 62.666. GBEF% decreased 0.433% on the right lateral image compared with anterior image. Result of paired sample t-test, p value is over 0.05. So, there was no significant difference in GBEF% calculated from the anterior and right lateral images. Conclusion In the case that a gallbladder and other organs are not separated on an anteior image, Right lateral image would be better to acquire more accurate GBEF% than using anterior image.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.501-513
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• 2019

In this study, which is based on the findings of the preceding studies, the researchers determined social support and Career Decision Self-efficacy as the key influencing variables for the successful Career Preparation Activities, to analyze the relationship between Career Preparation Activities and these variables, while identifying the mediating effect of Career Decision Self-efficacy in the relationship between social support and Career Preparation Activities. In addition, there is an objective to provide effective career counseling materials. For this study, a total of 174 North Korean adolescent defectors, who were in their middle and high schools, were interviewed and the resultant data were analyzed the data based on the questionnaire data of 204 copies from March 12 to 19, 2019. For the analysis of the data, SPSS and AMOS statistical suites were used to verify the hypothesis. The result of the analysis showed that, first, in the relationship between the social support, Career Decision Self-efficacy, and Career Preparation Activities of the North Korean adolescent defectors social support, Career Decision Self-efficacy, and Career Preparation Activities were all positively related. Especially, Career Decision Self-efficacy has been identified as the variable that is highly related to Career Preparation Activities. Second, rather than social support(${\beta}=.107$), Career Decision Self-efficacy(${\beta}=.388$) turned out to have more profound direct influence on Career Preparation Activities. Third, social support did not influence Career Preparation Activities directly(${\beta}=.107$, p>.05) but completely intermediated Career Decision Self-efficacy to influence Career Preparation Activities(Indirect effect=.307, p<.05, Z-value=2.924, p<.01). The findings of this study show that, in order to enhance the Career Preparation Activities of the North Korean adolescent defectors, it is necessary to examine how they perceive the emotional, informational, material, and evaluative supports from the surrounding environment are perceived and identify the abilities, values, and career desires of themselves through a behavioral planning that can establish a professional and value system in accordance with them.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.135-149
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• 2019

Today, a growing number of companies are in trouble because leaders are lack of authentic leadership. Small and midium sized companies have the same issue. To correct the issue, there must be a real change in the relationship between managers and employees of the company as well as outside the company. In 21st century, authentic leadership is required. However, the research about determinants of change supportive behavior is not sufficient. Therefore, the purpose of this study is how manager's transformational leadership and authentic leadership affects change supportive behavior of employees in small and midium sized companies. The study also has to prove the role of positive psychological capital as a parameter. Data were collected from 424 employees working for small and midium sized companies in metropolitan area around Seoul and Gyeonggi. The data were analyzed using statistical package SPSS ver.21.0 and AMOS ver.18.0. Based on the research, First, the transformational leadership does not affect the change supportive behavior. However, authentic leadership affects the change supportive behavior. Also, positive psychological capital playes a role as parameter when transformational and authentic leadership, that are independent variable, affect change supportive behavior. On the other hand, the research shows that authentic leadership has more influence than transformational leadership on positive psychological capital. Transformational leadership without genuine attitude cannot affect change support behavior of employees in small and medium sized companies. Therefore, to affect change supportive behavior of employee, authentic leadership with genuine mind is required. After discussing the conclusions and implications of this study. the direction of the study for the follow - up study was suggested.

• The Journal of Korean Academy of Prosthodontics
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• v.57 no.2
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• pp.110-117
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• 2019

Purpose: This study was to evaluate the wear resistance of 3D printed, milled, and conventionally cured provisional resin materials. Materials and methods: Four types of resin materials made with different methods were examined: Stereolithography apparatus (SLA) 3D printed resin (S3P), digital light processing (DLP) 3D printed resin (D3P), milled resin (MIL), conventionally self-cured resin (CON). In the 3D printed resin specimens, the build orientation and layer thickness were set to $0^{\circ}$ and $100{\mu}m$, respectively. The specimens were tested in a 2-axis chewing simulator with the steatite as the antagonist under thermocycling condition (5 kg, 30,000 cycles, 0.8 Hz, $5^{\circ}C/55^{\circ}C$). Wear losses of the specimens were calculated using CAD software and scanning electron microscope (SEM) was used to investigate wear surface of the specimens. Statistical significance was determined using One-way ANOVA and Dunnett T3 analysis (${\alpha}=.05$). Results: Wear losses of the S3P, D3P, and MIL groups significantly smaller than those of the CON group (P < .05). There was no significant difference among S3P, D3P, and MIL group (P > .05). In the SEM observations, in the S3P and D3P groups, vertical cracks were observed in the sliding direction of the antagonist. In the MIL group, there was an overall uniform wear surface, whereas in the CON group, a distinct wear track and numerous bubbles were observed. Conclusion: Within the limits of this study, provisional resin materials made with 3D printing show adequate wear resistance for applications in dentistry.