• Journal of dental hygiene science
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• v.9 no.1
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• pp.109-113
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• 2009

The purpose of this study was to examine the quality of life of high schoolers related to oral health. The subjects in this study were 287 high school students, on whom a survey was conducted. After the collected data were analyzed, the following findings were given: 1. As for self-perceived oral health state, 34.8 percent of the high schoolers investigated found themselves to be in a good oral health, and 65.2 percent didn't. In regard to concern for oral health, 15.7 percent showed a lot of interest, and 52.6 percent were a little interested. 31.7 percent had no interest in that. 2. Out of the oral health impact profile (OHIP) areas, they scored highest on the area of physical pain(2.24) and lowest on the area of social disadvantage(1.35). The overall oral health impact profile was 1.66. 3. Concerning relationship between general characteristics and the OHIP areas, the high school boys got significantly higher scores on the area of social disadvantage, and those who had ever visited dentist's offices scored statistically significantly higher on the areas of physical pain and mental insecurity. 4. Regarding connections between concern for oral health and the OHIP areas, those who were very interested in oral health got statistically significantly higher scores on every area. 5. As to the correlation among the OHIP areas, there was a statistically significantly positive correlation among all the areas.

• Journal of Korean Home Economics Education Association
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• v.27 no.3
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• pp.99-119
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• 2015

The purpose of this study is to examine the educational contents of home economics textbooks that solely focus on forming adolescent empowerment. For this, an in-depth content analysis was conducted on the home economics textbooks in Korea and the U.S. The main results of this study are summarized as follows: First, the 23 content elements, which are designed to build adolescent empowerment, were ascertained: nine intrapersonal empowerment elements such as the self-identity, nine interpersonal empowerment elements such as the communication, and five social empowerment elements such as the leadership. Second, based on the content elements selected from above, the textbooks in Korea were observed to deal with 58% of the 23 content elements, while those in the U.S. discussed 90% of the 23 content elements. Korean textbooks primarily focused on helping students understand major concepts, whereas the U.S. textbooks focused primarily on helping students make connections between major concepts and their life. Lastly, both countries put the least amount of weight on social empowerment content elements(Korea: 37%, U.S.: 70%).

• Journal of the Korean Geographical Society
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• v.46 no.4
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• pp.534-553
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• 2011

Analogical thinking is a problem-solving strategy to use a familiar problem (or base analog) to solve a novel problem of the same type (the target problem). The purpose of this study is to provide new insight into geography teaching and learning by connecting cognitive science research on analogical thinking with issues of geography education and suggest that teaching with analogies can be a productive instructional strategy for geography. In this study, using the various examples of analogical thinking used in geography we defined analogical thinking, addressed the theoretical models on analogical transfer, and discussed conditions that make an effective analogical transfer. The major research findings include the following: a) the spatial analogy, indicating skills to find places that may be far apart but have similar locations, and therefore have other similar conditions and/or connections, can provide a useful way to design contents for place learning; b) representational transfer, specifying a common representation for two problems, can play a key role in solving geographic problems requiring data visualization and spatialization processes; and c) either asking learners to compare/analyze similar examples sharing common structure or providing them examples bridging the gap between concrete, real-life phenomena and the ideas and models can contribute to learning in geographic concepts and skills. The spatial analogy requiring both geographic content knowledge and visual/spatial thinking has the potential to become a content-specific problem-solving strategy. We ended with recommendations for future research on analogy that is important in geography education.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.1-7
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• 2020

We can build regular customer relationships combining SNS (social networking service) with shopping mall like offline trade. A customer who once purchased is registered as reaular and the relationship continues afterward. The registered regular customer get sthe information about objective product shipment and besides it, he contacts with a story of frams, growth of vegetables, sows to harvests. Consumer can purchase with one click necessary foods as he looks at timeline. Sellers give information about news. discounts to customers. Besides it, food storages, recipes can be given to consumers. The good point here is that selling and promoting can be performed within one account. This is better than link is provided for selling an promoting separately. Like this, besides personal connections using SNS, categorization function gives consumers on line shopping mall service. Once the consumer purchase, he is registered as regular. Besides, the consumers who do not know each other, can share information, suggest products, spread the news.

• International Area Studies Review
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• v.21 no.4
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• pp.195-222
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• 2017

This exploratory study analyses the factors, sources and effects of the regional competitive advantage of Jeju Island in Korea in global competition era. The competitive advantage of Jeju Province is analysed with the triple diamond model based on Porter's model for the competitive advantage of nations. The competitive advantage factors of Jeju Province are measured through the competitive advantage of the hospitality industry, which is one of the major industries of Jeju Island. These factors include outstanding natural landscape, domestic hospitality industry workforce, social overhead capital, massive domestic and international tourists, growth of related industries such as duty free shops and casinos, and coincidences such as Jeju Olle trail construction and Chinese government's international travel approval. Since these factors are based on local, domestic and international management resources, this study suggests that obtaining such resources is critical among Jeju hospitality industry in gaining the competitive advantage. Although the competitive advantage of Jeju hospitality industry is increasing, the organic connections with the regional economy are required for improvements on Jeju residents' quality of life. This study examines the factors and origins of competitive advantages on a regional level instead of a national level, and further investigates how the characters and origins of these factors affect the local economy. The results suggest that the triple diamond model is suitable for evaluating the regional competitive advantages.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.354-360
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• 2021

People hope to live a healthy and happy life achieving satisfaction by striking a good work-life balance. Therefore, there is a growing interest in well-aging which means living happily to a healthy old age without worry. This study identified important factors related to well-aging by analyzing news articles published in Korea. Using Python-based web crawling, 1,199 articles were collected on the news service of portal site Daum till November 2020, and 374 articles were selected which matched the subject of the study. The frequency analysis results of text mining showed keywords such as 'elderly', 'health', 'skin', 'well-aging', 'product', 'person', 'aging', 'female', 'domestic' and 'retirement' as important keywords. Besides, a social network analysis with 45 important keywords revealed strong connections in the order of 'skin-wrinkle', 'skin-aging' and 'old-health'. The result of the CONCOR analysis showed that 45 main keywords were composed of eight clusters of 'life and happiness', 'disease and death', 'nutrition and exercise', 'healing', 'health', and 'elderly services'.

• Journal of International Area Studies (JIAS)
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• v.14 no.1
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• pp.77-106
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• 2010

As for the matter of guardianship-benefit network which has been at the heart of the discussion of power elites and clan politics in Kazakhstan, it has been often maintained that it is basically formed by the framework of the regional and descent connection net called Zhuz or at least it has been heavily under Zhuz's influence. But it is pointed out that the controversy of Zhuz suffers from a lot of limitations in explaining the surface of power elites in the recent process of political changes and the rearrangement of power relations. Consequently, this paper tried to take a closer look at the matter focusing on the social backgrounds of elites from Junior zhuz, who have been estimated to be relatively pushed back in terms of the advancement into the central power. As a result, it was found that the backgrounds of clan and tribe origin within Zhuz couldn't have any foundation to be seen as a decisive element through which they could grow into power elites. The phenomenon of Kazakhstani elites is a legacy of concrete historic situations. The important consideration points for analyzing the emergence of elites which could be applied to a nomadic and traditional society can hardly be an invariable framework for analyzing modern elites since independence. Since 2000, Kazakhstan has experienced economic changes including privatization due to the absolute strengthening of presidential influence which turned into a foundation for a new authoritarian system, the rearrangement of the inner circle of power, and their decisions. These changes in situations have had profound effects on the character of power elites. The phenomenon that clandestine connections have shown their appearances as they have gotten intertwined with various factors, in particular, in the economic field which has been heavily under Junior zhuz makes us convinced that the elite organization in Kazakhstan has always been the product of political and economic changes. In reality, the behaviors of elites were the outcome continuously reflecting environmental situations surrounding them, and those situations lie in a complicated and multiple-layered connection net. Therefore, it is believed that having interests in elites' social backgrounds and maintaining many pieces of information on them will be able to be a more useful approach to analyzing the elite society in the future in that interests in their social backgrounds become an informant of various network formation nets which reflect real situations.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.107-120
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• 2014

This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.6
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• pp.60-71
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• 2014

In this study, on the assumption that the urban park originally is imbued with a public welfare ideology, said public welfare ideology and its characteristics were attended to among the various social roles that the urban park currently fulfills. Aspects of welfare meaning in urban parks were attempted to be identified with the former history of urban parks and the movements of the connections between modern parks and welfare territories. The ideologies, benefits and practices regarding the welfare role that the urban park has played from the past to the present were examined and the backgrounds and contexts within which the welfare ideologies have been expressed in the urban park were examined. In order to examine the implicated public welfare ideologies of the urban park, case studies were conducted to identify how they are expressed and practiced in the present times and the facilitation of these parks and public welfare both in the U.S. and the South Korea. The study results of the cases show that expressions of public welfare in urban parks are composed of more specific and visible programs and strategies in the present times, which are different from the simple proclamatory ways in the past. Particularly, in order to visibly practice a public welfare ideology, many-sided integrated designs are conducted along with various public welfare institutions and programs inside and outside of the urban park. The conclusions from this study are as follows. First, the urban park plays a role as a space to realize public welfare ideology, to create welfare benefits and to realize social welfare. Modern urban parks are used as an indicator to measure the actual conditions of social welfare and are a social environmental commodity that can offer universal benefits to urban residents. Second, many-sided integrated designs are tried along with various public welfare institutions at urban parks, which visibly practice public welfare ideologies in the present. In addition, public welfare institutions greatly influence the consistent development of the resources in the urban park. Third, if the detailed utilization of the regional facilities infrastructure could be brought along with multidimensional approaches about the resources in the urban park, it could be much closer to the lives of residents and could secure a space for increasing resident quality of life.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.