• Journal of Korea Entertainment Industry Association
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• v.15 no.2
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• pp.123-135
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• 2021

The data processing of this study is focused on keywords related to 'Corona 19 and professional baseball' and 'Corona 19 and professional baseball no spectators', using text mining and social network analysis of textom program to identify problems and view quality. It was used to set the variable of For quantitative analysis, a questionnaire on viewing quality was constructed, and out of 270 survey respondents, 250 questionnaires were used for the final study. As a tool for securing the validity and reliability of the questionnaire, exploratory factor analysis and reliability analysis were conducted, and IPA analysis (importance-satisfaction) was conducted based on the questionnaire that secured validity and reliability, and the results and strategies were presented. As a result of IPA analysis, factors related to the image (image composition, image coloration, image clarity, image enlargement and composition, high-quality image) were found in the first quadrant, and the second quadrant was the game situation (support team game level, support player game level, star). Player discovery, competition with rival teams), game information (match schedule information, player information check, team performance and player performance, game information), interaction (consensus with the supporting team), and some factors appeared. The factors of commentator (baseball-related knowledge, communication ability, pronunciation and voice, use of standard language, introduction of game-related information) and interaction (real-time communication with the front desk, sympathy with viewers, information exchange such as chatting) appeared.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.1
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• pp.90-97
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• 2018

Purpose The lung segment ratio which is obtained through quantitative analyses of lung perfusion scan images is calculated to evaluate the lung function pre and post surgery. In this Study, the planar image production methods by using Q-Metrix (GE Healthcare, USA) program capable of not only quantitative analysis but also computation of the segment ratio after having performed SPECT/CT are comparatively evaluated. Materials and Methods Lung perfusion scan and SPECT/CT were performed on 50 lung cancer patients prior to surgery who visited our hospital from May 1, 2015 to September 13, 2016 by using Discovery 670(GE Healthcare, USA) equipment. AP(Anterior Posterior)method that uses planar image divided the frontal and rear images into three rectangular portions by means of ROI tool while PO(Posterior Oblique)method computed the segment ratio by dividing the right lobe into three parts and the left lobe into two parts on the oblique image. Segment ratio was computed by setting the ROI and VOI in the CT image by using Q-Metrix program and statistically analysis was performed with SPSS Ver. 23. Results Regarding the correlation concordance rate of Q-Metrix and AP methods, RUL(Right upper lobe), RML(Right middle lobe) and RLL(Right lower lobe) were 0.224, 0.035 and 0.447. LUL(Left upper lobe) and LLL(Left lower lobe) were found to be 0.643 and 0.456, respectively. In the PO method, the right lobe were 0.663, 0.623 and 0.702, respectively, while the left lobe were 0.754 and 0.823. When comparison was made by using the Paired sample T-test, Right lobe were $11.6{\pm}4.5$, $26.9{\pm}6.2$ and $17.8{\pm}4.2$, respectively in the AP method. Left lobe were $28.4{\pm}4.8$ and $15.4{\pm}5.6$. The right lobe of PO had values of $17.4{\pm}5.0$, $10.5{\pm}3.6$ and $27.3{\pm}6.0$, while the left lobe had values of $21.6{\pm}4.8$ and $23.1{\pm}6.6$, thereby having statistically significant difference in comparison to the Q-Metrix method for each of the lobes (P<0.05). However, there was no statistically significant difference in Right middle lobe (P>0.05). Conclusion The AP method showed low concordance rate in correlation with the Q-Metrix method. However, PO method displayed high concordance rate overall. although AP method had significant differences in all lobes, there was no significant difference in Right middle lobe of PO method. Therefore, at the time of production of lung perfusion scan results, utilization of Q-Metrix method of SPECT/CT would be useful in computation of accurate resultant values. Moreover, it is deemed possible to expect obtain more practical sectional computation result values by using PO method at the time of planar image acquisition.

• Journal of The Korean Association For Science Education
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• v.32 no.4
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• pp.570-585
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• 2012

The Korean national curriculum for secondary school emphasizes scientific problem solving. In line with the national curriculum, many educational studies have been conducted in relation to science education. The objects of these studies were well-defined and well-structured problems. The studies were criticized for overlooking ill-defined and ill-structured problems. Some research has dealt with problem finding in ill-structured problems, which is related to creativity. There is a need for a study of scientific problem finding process in an ill-structured problem situation, because this study will help teachers wanting to teach scientific problem-finding in an ill-structured problem situation. The objective of this study was to conduct an empirical study on the scientific problem finding process in an ill-structured problem situation. One task of scientific problem finding in an ill-structured problem situation was assigned to 92 university students; thereafter, 32 of them participated in the research through interviews. Results indicated that the scientific problem finding process depended on initial clues and tentative solutions. Initial clues were affected by students' experiences, such as major classes, films, and novels. Tentative solutions were influenced by background knowledge of the tasks. Students screened information browsed on the Internet. They applied some standards for selection, particularly emphasized reliability standards, which are supposed to be studied in other contexts. All the students used assumptions to make their problems appear probable, which could be a useful tool to articulate.

• (The) Research of the performance art and culture
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• no.33
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• pp.243-271
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• 2016

When an aggressive war reached at the climax in 1940, a commemorative event called celebration' was held on a large scale in Japan for 'beginning former 2,600 years. It was performed for the policy that was going to break off the fatigue that was tired for nation dissatisfaction and war for the politics. I considered Urayasu-no-mai Dance played as part of a celebration event in a Shinto shrine of the all over Japan how was created and spread by this article Urayasu-no-mai Dance was created newly and was played in Shinto shrines of the whole country. The Urayasu-no-mai Dance was created based on Gagaku and Miko Mai (shrine maiden's dance) that has been read aloud not to go out of the ancient times. It was created in the situation of the war and spread and was spread. It will be said that Urayasu Dance is a typical example of 'forged traditional'. Urayasu Dance is a tradition made at modern time and remains for an unfortunate inheritance used again by the advertising tool of the national ideology. The Urayasu-no-mai Dance is expanded more now, without enough consideration about the historic procession other words, It played under a strong-arm society atmosphere is placed as new folk performing arts all too soon. In the complicated world situation at the time, Urayasu-no-mai Dance that emphasized a Japanese tradition for the inside and outside were spread. Urayasu-no-mai Dance created in modern times substitutes a traditional shaman dance, and there is even the tendency that ritual performing arts peculiar to each local Shinto shrine is unified to Urayasu-no-mai Dance. Such a movement shows a new aspect of the culture power that social turning to the right in Japan is not unrelated to becoming it. It is a traditional reinvention, or do you forge the tradition? I examined a process of a process and the spread of traditional creation produced consistently.

• Korean Journal of School Psychology
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• v.17 no.1
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• pp.17-38
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• 2020

This study examined the factor structure of the Child Behavior Checklist Dysregulation Profile(CBCL-DP) for school-aged children in Korea identified differences in the level of maladjustment and problematic behaviors between the clinical group which had characteristics of CBCL-DP and the control group which did not. Confirmative factor analysis was performed on three alternative models from the literature to determine which was the most appropriate factor structure for the CBCL-DP. The result showed that the bi-factor model fit the sample data better than both the one and second-factor models. To confirm that the bi-factor model was the most appropriate factor structure, regression paths with relevant variables examined. The showed that CBCL-DP with the bi-factor model was associated with executive function difficulty as reported by parents and with school adjustment and all sub-factors of strength and difficulty as reported by teachers. The results also showed that this model had a different relationship with anxiety/depression, aggressive behavior, and attention problems than the other models. The clinical group was shown to have more executive function difficulty, worse adjustment of school life and to be less likely to engage in desired behaviors than the control group. These results indicate the CBCL-DP is more related to negative outcomes than any other factor, and that the bi-factor model was found to best fit the sample data, consistent with other studies. The early discovery of CBCL-DP can be used to provide interventions for high-risk children who exhibit emotional and behavioral problems, making its detection a significant diagnostic tool. The implications of these result, the limitations of this study, and areas for future research are discussed in this paper.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.