• Journal of Korean Home Economics Education Association
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• v.33 no.1
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• pp.169-185
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• 2021

The purpose of this study is to apply the clothing teaching-learning plan from a critical science perspective developed to improve teenager's empowerment, and to examine it's effects. A total of 12 plans of 5 modules(Module A to E) developed from critical science perspective were implemented for four weeks. Second-year students (N 42) of K Middle School located in Y-si, Gyeonggi-do participated in the study in the study, and the survey results were analyzed quantitatively using t-tests. For the quality analysis, The student interview data, action reports and etc. were collected, and qualitative analysis was conducted using empowerment model as the analysis framework. The findings of study are follows. First, two hours each for modules A to D, and four hours for module E were assigned, because module E included an action project. In the action projects by for groups, students were expected to take the lead in conducting the activities such as developing promotional posters, posting opinions online, promoting videos, informing how to make recyclables, and donating to the community. Second, as a result of analyzing the pre-implementation vs post-implementation empowerment scores, a significant difference was found in social-political empowerment (t=-2.06, p<0.05). According to the analysis of student interviews and students project's reports, students were found to become aware of empowerment through the instruction. On the intrapersonal level, positive self-awareness and self-efficacy, and on the interpersonal level, smooth communication and democratic decision-making were confirmed. This study is meaningful in that regular a home economics instruction class from a critical science perspective have made a quantitative and qualitative impact on teenagers' improvement empowerment, providing opportunities to find their roles in the soceity, cooperate with others, and behave responsibly as members of society.

• Journal of the korean academy of Pediatric Dentistry
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• v.49 no.3
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• pp.285-299
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• 2022

The aim of this study is to investigate the awareness and perception of pediatric dentists regarding dental health insurance (DHI) system in Korea. Online surveys were sent to the members of the Korean Academy of Pediatric Dentistry (KAPD), and the responses were collected. The survey, consisting of 41 questions, was subdivided into 'general background of the respondents', 'the awareness on national health insurance (NHI) and DHI', 'the awareness on DHI pertaining to pediatric dentistry', 'issues that need improvement on DHI pertaining to pediatric dentistry', 'DHI claims', and 'the roles of KAPD in DHI'. In total, 302 responded, with a response rate of 28.9%. Excluding 2 questionnaires with insufficient answers, a total of 300 survey results were analyzed. According to the analysis, pediatric dentists thought that the coverage of DHI was not as sufficient compared to that of NHI, but were expecting its scope to broaden in the future. The satisfaction rate was higher in pit and fissure sealant and composite resin filling than in caries-detecting quantitative light-induced fluorescence. Pediatric dentists considered permanent tooth composite resin filling (65.7%) needed an increase in insurance copayment, while topical fluoride application (74.7%) to require insurance coverage. DHI claims were generally handled by dental hygienists and/or nursing assistants. Approximately half of the respondents answered that they have had experiences on appealing for insurance denials. Lastly, pediatric dentists generally had a positive attitude towards providing information for the DHI. This study is expected to be used as a sound dataset for the DHI policy development concerning pediatric dentistry.

• Korea Trade Review
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• v.48 no.4
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• pp.303-320
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• 2023

Recently, import and export companies have been using T/T remittance and Surrender B/L more frequently than L/C when selecting the process and method of trade payment settlement. The new trade and logistics environment is thriving in the era of the Fourth Industrial Revolution (4IR). Document-based trade transactions are undergoing a digitalization as bills of lading or smart contracts are being developed. The purpose of this study is to verify whether exporters choose export payment types based on negotiating factors. In addition, we would like to discuss the application of the characteristics of the new trade and logistics environment. Data for analysis was collected through surveys. The collection method consisted of direct visits to the company, e-mail, fax, and online surveys. The survey distribution period is from February 1, 2023, to April 30, 2023. The questionnaire was distributed in 2,000 copies, and 447 copies were collected. The final 336 copies were used for analysis, excluding 111 copies that were deemed inappropriate for the purpose of this study. The results of the study are shown below. First, among the negotiating factors, the product differentiation of exporters did not significantly affect the selection of export payment types. Second, among the negotiating factors, the greater the purchasing advantage recognized by exporters, the higher the possibility of using the post-transfer method. In addition to analyzing the results, this study suggests that exporters should consider adopting new payment methods, such as blockchain technology-based bills of lading and trade finance platforms, to adapt to the characteristics of the evolving trade and logistics environment. Therefore, exporters should continue to show interest in initiatives aimed at digitizing trade documents as a response to the challenges posed by bills of lading. In future studies, it is necessary to address the lack of social awareness in Korea by conducting advanced research abroad.

• Journal of the Daesoon Academy of Sciences
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• v.49
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• pp.187-227
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• 2024

The purpose of this article is to examine the prospects of the religious cultural experience program of Daesoon Jinrihoe by referring to the current status of Korea's Buddhist temple stays, which began with the 2002 World Cup and have become a regular program for the general public with the establishment of the Cultural Corps of Korean Buddhism in 2004. The motivation for Korean participation is mainly rest, while foreigners tend to be more interested in Korean traditional culture. During the experience, the perceived value felt by the participants led to satisfaction and an intention to revisit. Temple stays have contributed to the globalization of Korean Buddhism. The temple stay of Daesoon Jinrihoe is a religious cultural experience program for the public. If it became a regular program, the target could be expanded to include foreigners who wish to experience Korean culture. The activities such as wearing Hanbok, taking a Dojang Tour, praying, and dialogue over tea can be allocated to the program. As a result, the perceived value by participants could be taken as a cognitive value. For instance, they could learn about Sangje's Reordering of the Universe that transformed the order of Sanggeuk (Mutual Contention) into the order of Sangsaeng (Mutual Beneficence). They way that they live their lives could change as a result of these new understandings. The emotional value of the experience would come from experiencing traditional Korean religious culture. The prospect of implementing such a program is twofold: firstly, there are the tasks of proper preparation, and secondly, there are the positive effects. The tasks would first involve creating a systematic and organized center point. Next there would be the matter of preparing spaces for the temple stay, and lastly, an online platform for advertisement, recruitment, and application would also be greatly beneficial. This is a vision that could contribute to the improving public image of the order, its globalization, and to the overall improvement of the facilities and management that would produce a more socially friendly environment.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.