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A Study on Postconventional Christian Education for Intercultural Conflict Resolution (문화 간 갈등해소를 위한 탈인습적 기독교교육에 관한 연구)

  • Kim, Jinyoung
    • Journal of Christian Education in Korea
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    • v.62
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    • pp.257-283
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    • 2020
  • Our current society is experiencing a mass upheaval through globalization: mobility, hybridity, and cultural diversity are part of this world phenomenon. We can say that these changes are a result of people crossing borders due to international travel, immigration, emigration, studying abroad, labor, international marriages, fast and comfortable transportation, and the Internet. According to 2018 UNPD(Untied Nations Population Division)'s data, the international migrants have exceeded 258 million as of 2017. The increased number of migrants signifies that people with various backgrounds move from their own culture to a drastically different one. Interacting with different cultures can give people the chance to experience abundant lifestyles and improve life qualities. During that process, however, the differences between cultures can cause not only misunderstandings, conflicts, and violent collisions, but also xenophobia or radical nationalism. The current society is confronted with a problem: the people cannot stubbornly cling to a homogenous ethnicity anymore, which makes the coexistence between the citizens and immigrants necessary. Through these circumstances, I aim to suggest an educational model and a practical curriculum from a Christian perspective as the aim of this study. It seeks to encourage Christians to flexibly respond to these conflicts and collisions, and to fulfill their social responsibilities faithfully. For this reason, I will explore and seek sharing practical values through both shalom's communality as a theological approach and postconventionality in mature adults as a social-scientific approach. Consequently, I have few requests for the readers. First, approach with openness, understanding, and respect for other culture. Second, see this study as one step of confronting the global problem for coexistence and coprosperity of all social agents in the earth, a limited space. Third, notice that this study uses the interdisciplinary approach (theological and social scientific view) for a shareable, practical value that consistently leads the curriculum of my thesis, and a scientific method to eliminate bias. Lastly, understand that this study will eventually be used in educational practice, and as a result it prioritizes giving thought to the Christian educational environment. This study begins by exploring the conflicts and collisions between diverse cultures of our current society in international and national cases. Afterwards, I will reflect on how we can manage these conflicts and collisions by exploring the social-scientific view, postconventionality in mature adults, the theological view, and shalom's communality as a complement for the postconventionality's personal dimension. In conclusion, I suggest a curriculum that achieves peace as a practical value based on postventionality and shalom's communality for this study's goal.

A Study on 21st Century Fashion Market in Korea (21세기 한국패션시장에 대한 연구)

  • Kim, Hye-Young
    • The Journal of Natural Sciences
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    • v.10 no.1
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    • pp.209-216
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    • 1998
  • The results of the study of diving the 21st century's Korea fashion market into consumer market, fashion market, and a new marketing strategy are as follows. The 21st consumer market is First, a fashion democracy phenomenon. As many people try to leave unconditional fashion following, consumer show a phenomenon to choose and create their own fashion by subjective judgements. Second, a phenomenon of total fashion pursuit. Consumer in the future are likely to put their goals not in differentiating small item products, but considering various fashion elements based on their individuality and sense of value. Third, world quality-oriented. With the improvement of life level, it accomplishes to emphasize consumers' fashion mind on the world wide popular use of materials, quality, design and brand image. Fourth, with the entrance of neo-rationalism, consumers show increasing trends to emphasize wisdom, solidity in goods strategy pursuing high quality fashion and to demand resonable prices. Fifth, concept-oriented. Consumers are changing into pursuing concept appropriate to individual life scene. Prospecting the composition of the 21st century's fashion market, First, sportive casual zone will draw attention more than any other zone. This is because interest in sports will grow according to the increase of leisure time and the expasion of time and space in the 21st century, and also ecology will become the important issue of sports sense because of human beings's natural habit toward nature. Second, the down aging phenomenon will accelerate its speed as a big trend. Third, a retro phenomenon, a concept contrary to digital and high-tech, will become another big trend for its remake, antique, and classic concept in fashion market with ecology trend. New marketing strategy to cope with changing fashion market is as follows. First, with the trend of borderless concept, borders between apparels are becoming vague, for example, they offer custom-made products to consumers. Second, as more enterprises take the way of gorilla and guerrilla where guerrillas who aim at niche market show up will develop. Basically, they think highly of individual creative study, and pursue the scene adherence with high sensitiveness. However this polarization becomes mutually-supplementing relationship showing gorilla's guerilla movement, and guerilla's gorilla high-tech. Third with the development of value retailing, enterprises pursuing mass merchandising of groups called category killers are expanded and amplified to new product fields, and expand business' share. Fourth, using outsourcing, the trend to use exterior function leaving each enterprise's strength by inspecting its own work is gradually strong. Fifth, with the expansion of none store sale, the entrance of the internet and the CD-ROM sales added to communication sales such as catalogues are specified. An eminent American think tank expect that 5-5% of the total sale of clothes and home goods in 2010 will be done by none store sale. Accordingly, to overcome the problems, First international, global level marketing, Second, the improvement of technology, Third, knowledge-creating marketing are needed.

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A Methodology for Automatic Multi-Categorization of Single-Categorized Documents (단일 카테고리 문서의 다중 카테고리 자동확장 방법론)

  • Hong, Jin-Sung;Kim, Namgyu;Lee, Sangwon
    • Journal of Intelligence and Information Systems
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    • v.20 no.3
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    • pp.77-92
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    • 2014
  • Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.

Design of Cloud-Based Data Analysis System for Culture Medium Management in Smart Greenhouses (스마트온실 배양액 관리를 위한 클라우드 기반 데이터 분석시스템 설계)

  • Heo, Jeong-Wook;Park, Kyeong-Hun;Lee, Jae-Su;Hong, Seung-Gil;Lee, Gong-In;Baek, Jeong-Hyun
    • Korean Journal of Environmental Agriculture
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    • v.37 no.4
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    • pp.251-259
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    • 2018
  • BACKGROUND: Various culture media have been used for hydroponic cultures of horticultural plants under the smart greenhouses with natural and artificial light types. Management of the culture medium for the control of medium amounts and/or necessary components absorbed by plants during the cultivation period is performed with ICT (Information and Communication Technology) and/or IoT (Internet of Things) in a smart farm system. This study was conducted to develop the cloud-based data analysis system for effective management of culture medium applying to hydroponic culture and plant growth in smart greenhouses. METHODS AND RESULTS: Conventional inorganic Yamazaki and organic media derived from agricultural byproducts such as a immature fruit, leaf, or stem were used for hydroponic culture media. Component changes of the solutions according to the growth stage were monitored and plant growth was observed. Red and green lettuce seedlings (Lactuca sativa L.) which developed 2~3 true leaves were considered as plant materials. The seedlings were hydroponically grown in the smart greenhouse with fluorescent and light-emitting diodes (LEDs) lights of $150{\mu}mol/m^2/s$ light intensity for 35 days. Growth data of the seedlings were classified and stored to develop the relational database in the virtual machine which was generated from an open stack cloud system on the base of growth parameter. Relation of the plant growth and nutrient absorption pattern of 9 inorganic components inside the media during the cultivation period was investigated. The stored data associated with component changes and growth parameters were visualized on the web through the web framework and Node JS. CONCLUSION: Time-series changes of inorganic components in the culture media were observed. The increases of the unfolded leaves or fresh weight of the seedlings were mainly dependent on the macroelements such as a $NO_3-N$, and affected by the different inorganic and organic media. Though the data analysis system was developed, actual measurement data were offered by using the user smart device, and analysis and comparison of the data were visualized graphically in time series based on the cloud database. Agricultural management in data visualization and/or plant growth can be implemented by the data analysis system under whole agricultural sites regardless of various culture environmental changes.

A Study on the Improvement of Recommendation Accuracy by Using Category Association Rule Mining (카테고리 연관 규칙 마이닝을 활용한 추천 정확도 향상 기법)

  • Lee, Dongwon
    • Journal of Intelligence and Information Systems
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    • v.26 no.2
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    • pp.27-42
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    • 2020
  • Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.