• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.39-53
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• 2013

The emergence of the internet technology and SNS has increased the information flow and has changed the way people to communicate from one-way to two-way communication. Users not only consume and share the information, they also can create and share it among their friends across the social network service. It also changes the Social Media behavior to become one of the most important communication tools which also includes Social TV. Social TV is a form which people can watch a TV program and at the same share any information or its content with friends through Social media. Social News is getting popular and also known as a Participatory Social Media. It creates influences on user interest through Internet to represent society issues and creates news credibility based on user's reputation. However, the conventional platforms in news services only focus on the news recommendation domain. Recent development in SNS has changed this landscape to allow user to share and disseminate the news. Conventional platform does not provide any special way for news to be share. Currently, Social News Service only allows user to access the entire news. Nonetheless, they cannot access partial of the contents which related to users interest. For example user only have interested to a partial of the news and share the content, it is still hard for them to do so. In worst cases users might understand the news in different context. To solve this, Social News Service must provide a method to provide additional information. For example, Yovisto known as an academic video searching service provided time dependent metadata from the video. User can search and watch partial of video content according to time dependent metadata. They also can share content with a friend in social media. Yovisto applies a method to divide or synchronize a video based whenever the slides presentation is changed to another page. However, we are not able to employs this method on news video since the news video is not incorporating with any power point slides presentation. Segmentation method is required to separate the news video and to creating time dependent metadata. In this work, In this paper, a time dependent metadata-based framework is proposed to segment news contents and to provide time dependent metadata so that user can use context information to communicate with their friends. The transcript of the news is divided by using the proposed story segmentation method. We provide a tag to represent the entire content of the news. And provide the sub tag to indicate the segmented news which includes the starting time of the news. The time dependent metadata helps user to track the news information. It also allows them to leave a comment on each segment of the news. User also may share the news based on time metadata as segmented news or as a whole. Therefore, it helps the user to understand the shared news. To demonstrate the performance, we evaluate the story segmentation accuracy and also the tag generation. For this purpose, we measured accuracy of the story segmentation through semantic similarity and compared to the benchmark algorithm. Experimental results show that the proposed method outperforms benchmark algorithms in terms of the accuracy of story segmentation. It is important to note that sub tag accuracy is the most important as a part of the proposed framework to share the specific news context with others. To extract a more accurate sub tags, we have created stop word list that is not related to the content of the news such as name of the anchor or reporter. And we applied to framework. We have analyzed the accuracy of tags and sub tags which represent the context of news. From the analysis, it seems that proposed framework is helpful to users for sharing their opinions with context information in Social media and Social news.

• Management & Information Systems Review
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• v.39 no.2
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• pp.181-193
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• 2020

This study is a study that analyzes consumer perception by utilizing text mining, which is a recent issue. we analyzed the consumer's perception of Samsung Galaxy by analyzing consumer reviews of Samsung Galaxy YouTube ads. for analysis, 1,819 consumer reviews of YouTube ads were extracted. through this data pre-processing, keywords for advertisements were classified and extracted into nouns, adjectives, and adverbs. after that, frequency analysis and emotional analysis were performed. Finally, clustering was performed through CONCOR. the summary of this study is as follows. the first most frequently mentioned words were Galaxy Note (n = 217), Good (n = 135), Pen (n = 40), and Function (n = 29). it can be judged through the advertisement that consumers "Galaxy Note", "Good", "Pen", and "Features" have good functional aspects for Samsung mobile phone products and positively recognize the Note Pen. in addition, the recognition of "Samsung Pay", "Innovation", "Design", and "iPhone" shows that Samsung's mobile phone is highly regarded for its innovative design and functional aspects of Samsung Pay. second, it is the result of sentiment analysis on YouTube advertising. As a result of emotional analysis, the ratio of emotional intensity was positive (75.95%) and higher than negative (24.05%). this means that consumers are positively aware of Samsung Galaxy mobile phones. As a result of the emotional keyword analysis, positive keywords were "good", "good", "innovative", "highest", "fast", "pretty", etc., negative keywords were "frightening", "I want to cry", "discomfort", "sorry", "no", etc. were extracted. the implication of this study is that most of the studies by quantitative analysis methods were considered when looking at the consumer perception study of existing advertisements. In this study, we deviated from quantitative research methods for advertising and attempted to analyze consumer perception through qualitative research. this is expected to have a great influence on future research, and I am sure that it will be a starting point for consumer awareness research through qualitative research.

• Clinical and Experimental Pediatrics
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• v.48 no.9
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• pp.924-928
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• 2005

Purpose : Treatment efficacy for children with speech and language delay has been the subject of considerable debate in recent years. We evaluated the clinical features of children with delayed speech and language and their prognoses according to their etiologies after 6 months of speech and language therapy. Methods : From January, 2000 to March, 2004, we retrospectively reviewed 56 children with speech and language delay who were administered speech and language therapy for 6 months in Uijongbu St. Mary's Hospital. Results : Of 56 cases, the proportion of developmental language disorder was 66.1 percent, structural malformation 19.6 percent, mental retardation 12.5 percent, hearing defect 1.8 percent. The ratio of male to female was 4.6 : 1 and the most frequent age group was over 47 months. The mean age of first spontaneous words with useful meaning was 15.9 months. The mean gestational age of the subjects was 39.8 weeks. The proportion of full-term infants was 96.4 percent and of premature infants was 3.6 percent. As for the birth order, the proportion of the first baby was 51.8 percent, the one of second babies it was 42.9 percent, and percent of third babies it was 7.1 percent. After 6 months of language intervention, 32.4 percent of patients with developmental language disorder showed normal linguistic development. All the patients with mental retardation showed sustained language and speech delay. As for the patients with structural malformations, five out of 11 patients showed normal linguistic development. Conclusion : The relatively advanced old age of majority of participants in this study suggests the necessity of screening test for language delay in this local community.

• Cartoon and Animation Studies
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• s.51
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• pp.181-201
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• 2018

The cartoon industry in Korea has continued to decline due to the contraction of published comics market and decrease in the number of comic books rental stores until the 2000s when it rapidly started to experience qualitative changes and quantitative growth due to the emergence of webtoon. The market size of webtoon industry, valued at 420 billion won in 2015, is expected to grow to 880.5 billion won by 2018. Notably, most cartoonists who draw cartoon strips are using digital devices and producing scripts in data, thereby overcoming the geographical, spatial and physical limitation of contents. As a result, a favorable environment for the creation of local ecosystems is generated. While the infrastructures of human resources are steadily growing by region, cartoon industries that are supported by the government policy have shown good performance combined with factors of creative infrastructures in local areas such as webtoon experience centers, webtoon campuses and webtoon creation centers, etc. Nevertheless, it is true that cartoon infrastructures are substantially based on a capital area which leads to an imbalanced structure of cartoon industry. To see the statistics, companies of offline cartoon business in Seoul and Gyeonggi Province make up 87%, except for distribution industry. In addition, companies of online cartoon business which are situated outside of Seoul and Gyeonggi Province form merely 7.5%. Studies and research on local webtoon are inadequate. The existing studies on local webtoon usually focus on its industrial and economic values, mentioning the word "local" only sometimes. Therefore, this study looked into the current status of local webtoon of the present time for the current state of local cartoon ecosystem, middle and long-term support from the government, and an alternative in the future. Main challenges include the expansion of opportunities to enjoy cartoon cultures, the independence of cartoon infrastructure, and the settlement of regionally specialized cartoon cultures. It means that, in order to enable the cartoon ecosystem to settle down in local areas, it is vital to utilize and link basic infrastructures. Furthermore, it is necessary to consider independence and autonomy beyond the limited support by the government. Finally, webtoon should be designated as a culture, which can be a new direction of the development of local webtoon. Furthermore, desirable models should be continuously researched and studied, which are suitable for each region and connect them with regional tourism, culture and art industry. It will allow the webtoon industry to soft land in the industry. Local webtoon, which is a growth engine of regions and main contents of the fourth industrial revolution, is expected to be a momentum for the decentralization of power and reindustrialization of regions.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.21-44
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• 2018

In recent years, the rapid development of internet technology and the popularization of smart devices have resulted in massive amounts of text data. Those text data were produced and distributed through various media platforms such as World Wide Web, Internet news feeds, microblog, and social media. However, this enormous amount of easily obtained information is lack of organization. Therefore, this problem has raised the interest of many researchers in order to manage this huge amount of information. Further, this problem also required professionals that are capable of classifying relevant information and hence text classification is introduced. Text classification is a challenging task in modern data analysis, which it needs to assign a text document into one or more predefined categories or classes. In text classification field, there are different kinds of techniques available such as K-Nearest Neighbor, Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, and Artificial Neural Network. However, while dealing with huge amount of text data, model performance and accuracy becomes a challenge. According to the type of words used in the corpus and type of features created for classification, the performance of a text classification model can be varied. Most of the attempts are been made based on proposing a new algorithm or modifying an existing algorithm. This kind of research can be said already reached their certain limitations for further improvements. In this study, aside from proposing a new algorithm or modifying the algorithm, we focus on searching a way to modify the use of data. It is widely known that classifier performance is influenced by the quality of training data upon which this classifier is built. The real world datasets in most of the time contain noise, or in other words noisy data, these can actually affect the decision made by the classifiers built from these data. In this study, we consider that the data from different domains, which is heterogeneous data might have the characteristics of noise which can be utilized in the classification process. In order to build the classifier, machine learning algorithm is performed based on the assumption that the characteristics of training data and target data are the same or very similar to each other. However, in the case of unstructured data such as text, the features are determined according to the vocabularies included in the document. If the viewpoints of the learning data and target data are different, the features may be appearing different between these two data. In this study, we attempt to improve the classification accuracy by strengthening the robustness of the document classifier through artificially injecting the noise into the process of constructing the document classifier. With data coming from various kind of sources, these data are likely formatted differently. These cause difficulties for traditional machine learning algorithms because they are not developed to recognize different type of data representation at one time and to put them together in same generalization. Therefore, in order to utilize heterogeneous data in the learning process of document classifier, we apply semi-supervised learning in our study. However, unlabeled data might have the possibility to degrade the performance of the document classifier. Therefore, we further proposed a method called Rule Selection-Based Ensemble Semi-Supervised Learning Algorithm (RSESLA) to select only the documents that contributing to the accuracy improvement of the classifier. RSESLA creates multiple views by manipulating the features using different types of classification models and different types of heterogeneous data. The most confident classification rules will be selected and applied for the final decision making. In this paper, three different types of real-world data sources were used, which are news, twitter and blogs.

• Journal of the Korean earth science society
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• v.41 no.1
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• pp.75-91
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• 2020

The purposes of this study are 1) to develop a pre-education program for teaching the basic concepts of systems thinking and STEAM program based on systems thinking and 2) to investigate the effects of the program on middle school students' systems thinking. The subjects were 4 seventh-graders and 4 ninth-graders in a middle school located in the province of Gyeongsangbuk-do. Data related to students' systems thinking was analyzed using the rubrics developed by Hung(2008). The results were reviewed by experts to verify the validity of the rubrics and the reliability of students' system thinking. In addition, the data analyzed with the rubrics, students' awareness of systems thinking, word associations, causal maps and interviews were systematically analyzed to investigate the effects of the program on students' systems thinking. The findings of this study were as follows: First, a pre-education program and teachers' guidebook for teaching and learning the concept of systems thinking and causal maps were developed. The pre-education program consisted of familiar TV entertainment program-Infinite Challenge (Muhandojeon)-with a theme of Global Warming. Second, a STEAM education program based on systems thinking which was composed of 5 steps: Analysis-Design-Build-Assessment-Systems thinking. The major theme of the program was an air extinguisher. The developed STEAM education program had positive effects on improving middle school students' systems thinking abilities such as understanding systems, relations within a system and system generalization. Therefore, it was concluded that the STEAM program could be instrumental for cultivating students' STEAM literacy with improved systems thinking.

• 대한공업교육학회지
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• v.39 no.1
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• pp.189-208
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• 2014

The purpose of this research was to investigate the critical issues and practical strategies that Korean technology teachers perceived. To accomplish the purpose of this study, a qualitative study was conducted to identify critical issues and practical strategies of Korean technology education targeted on Korean technology teachers. A purposeful sampling for choosing technology teachers was used for this study with three selection conditions: 1) 'Excellent Korean technology teacher' award winning teachers, or 2) technology teachers actively involved in both on-line and off-line teachers' association, and 3) leaders in local technology teachers' association. This study conducted exploratory in-depth interviews with selective 15 technology teachers regarding critical issues and practical strategies of Korean technology teachers. The interpretation of the interview content was conducted by two researchers using the thematic analysis which analyzed the frequency of concepts, words, and meanings held from collected data. In the conclusion, critical issues researchers identified were 1) curriculum problems, 2) education environment and facilities problems, 3) teachers' problems, 4) students' problems, 5) related research institution and college problems, 6) social problems. Secondly, Korean technology teachers agreed with following practical strategies 1) separating technology education from home economic education, 2) sharing practices on managing and improving educational environment and laboratory for technology education, 3) actively involving in technology teachers' group, 4) motivating students using hands-on activity 5) improving the quality and the quantity on technology teachers preparatory institution, 6) advertising the values of technology education to the public. Lastly, the positive factors to succeed technology education were 1) technology education satisfying social needs and 2) technology teachers' will or passion toward improving their technology classrooms. The negative factors to hinder technology education were 1) low self-respect of Korean technology teachers and 2) rejection or retarded acceptance toward social transition. Several recommendations based the conclusion were suggested as 1) implementing supplementary study toward selected critical issues and 2) conducting exemplary case studies regarding concrete practical strategies for improving challenges of Korean technology education.

• (The) Research of the performance art and culture
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• no.37
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• pp.249-293
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• 2018

The Musical Theatre was a popular art genre that originated from the western musical tradition represented by the European opera. In the twentieth century, it bloomed around Broadway in the United States. It is also one of the commercial arts which is popularly loved by the public in the field of performing arts all over the world at present. Due to the nature of this genre, the development of dramas and the expression of characters use music, not words or gestures, as the main medium. And the style of music reacts sensitively to the taste of the public, not to a particular class. When Japan colonized Korea, the empire strongly believed modernization equaled westernization and Japan was the one who could awaken Korean. The Japanese colonial music education was intended to bring cooperation and obedience to Japan by forcibly injecting Japanese ideology and culture into Joseon people. The music education of colonialism with the textbook of the "Songs for public education(보통교육 창가집)" compiled by the Japanese government was a sparkstone for the conversion of the Korean musical identity to Japanese and Western music. In addition to the capitalistic economical mechanism for establishing a South Korean government friendly with the United States during the Cold War after liberation, and the rush of American Pop culture represented by 'the show stage in 8th US Arm' and 'movies' which are to be the influence of invisible 'new cultural imperialism', our traditional music was confined to the meaning of 'Korean music', meaning 'past music'. In Korea, after the liberation, the musical was introduced by the influx of American popular culture. In accordance with the cultural policy of Park Jeong-hee regime, which aimed to spread the 'healthy culture' through the modernization of traditional arts, 'The Yegreen(예그린악단)' was founded. However, the plan to create a contemporary performing art based on Korean national arts showed the possibility of success in 1966 with the success of , but soon after, they have been destined to fall into an institution that has lost their ability to operate on their own due to the suspension of the sponsorship of the regime. Due to the cultural imperialist strategy of the influence of Japanese imperialism's colonial music education and influx of American popular culture after liberation, in the early days of Korean musicals, our traditional aesthetic style brought about the situation of the 1960 's, which did not become an independent ethnic art through the exchange and expansion with Western music. This is the background of the western licensed musicals led by the Korean musical market in the 21st century as well as the main cause of musical creation based on western music.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.4
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• pp.124-136
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• 2011

In landscape architecture, plants play an important role in realizing the intention of the architect and user- behavior as well as an ecology and appearance of the space for them. However, it is true that many researches have focused on ecological characteristics of plants, their cultivation environment and symbolic meanings in traditional terms, while relatively few for the analysis of the aspects of each period through plants. For this, cherry trees that we often see around are selected and their introduction, propagation, development and symbolism from the view of chronicle are studied and the results are followings; Firstly, three-year seedlings of 1,500 pieces of cherry tree from Osaka and Tokyo were planted for the first time in Oieseongdae, Namsan Park, Seoul. Since then, they had been widely planted at traditional sites, modern parks, newly-constructed roads for street trees, and for this, the Japanese Government-General of Chosun had actively supported by its direct cultivation and selling of cherry trees. The spread of cherry trees planted raised the question of whether or not Prunus yedoensis is originated from Jeju Island. Secondly, such massive and artificial planting of them had become attractions over the time and mass media at that time also had actively promoted it. And such trend made the day and night picnic under the cherry blossoms one of the most representative cultures of enjoying spring in Seoul. Thirdly, although general people enjoyed cherry blossoms, but they had dual view and attitude for cherry trees, which were well expressed in their use of them: for example, cherry blossoms, aeng and sakura were used altogether for same meaning, but night aeng or night picnic under cherry blossoms were especially used instead of yojakura when mentioning just pleasure, which meant some saw night enjoying cherry blossoms a low culture. Fourth, symbolic space of Chosun had been transformed into the space for enjoyment and consumption. Anyone who paid entrance fee could enjoy performance of revugirl, cinema and entertainment along with enjoying cherry blossoms. The still-existing strict differentiation of enjoyment culture by social status, class and ethnicity was dismantled from that trend and brought about a kind of disorder. From this, we could find that cherry blossoms had made a great contribution to the change of traditional enjoyment culture over the Japanese colonial period and become a popular spring enjoyment.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.