• (The)Study of the Eastern Classic
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• no.33
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• pp.385-411
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• 2008

This thesis aims at examining his understandings about the The Great Learning centering on the of the founder of the YiYongHuSaeng School (利用厚生學派: A school who pursued prosperous economy and welfare of people) orthe BukHak School(北學派: A positive school that pursued mercantilism) from the Joseon Dynasty, Dam-Heon Hong Dae Yong (1731-1783). 1) From what is indicated in the , his studies mainly focused on the annotations from DaeHakJangGuDaeJeonJipJu ("大學章句大全集註": A book that edited different phrases from the Great Learning into chapters and paragraphs), Questioning of the Great Learning", and "JuJaUhRyu (朱子語類: A book of Confucian literature written by Yeo Jung Deok" of Zhu Xi who was a representative scholar of the Neo-Confucianism in the Song Dynasty. 2) Acknowledging entirely the arguing points of Zhu Xi, he is taking a critical position in a way that partial doubts are divided into seven chapters and questioned. 3) For the main characteristic and direction of the questioning, he is estimating that Zhu Xi only stressed the 'means' and 'interior' out of the world of 'means and ends' and 'interior and exterior' in Zhu Xi's recognizing and handling cases; instead, he emphasized putting equivalent value on the 'ends' and 'exterior' as well. 4) In fact, such questions raised partially were misconceived since they were not carried out through profound understanding nor systematic logic expansion of what Zhu Xi insisted. 5) Despite this, at the point where Neo-Confucian thoughts were fixed and weakened only with its form left in the late Joseon Dynasty, his perspective on the study of Confucian classics that the 'ends' and 'exterior' should be as equally valued as the 'means' and 'interior' by examining through the core text of the Neo-Confucianism, The Great Learning has its significance in his YiYongHuSaeng dogma that says politicians, by all means, should provide the ruled with economic convenience and welfare and this is their very right virtue.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.251-273
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• 2022

Recently, research on applying text analysis to deep learning has steadily continued. In particular, researches have been actively conducted to understand the meaning of words and perform tasks such as summarization and sentiment classification through a pre-trained language model that learns large datasets. However, existing pre-trained language models show limitations in that they do not understand specific domains well. Therefore, in recent years, the flow of research has shifted toward creating a language model specialized for a particular domain. Domain-specific pre-trained language models allow the model to understand the knowledge of a particular domain better and reveal performance improvements on various tasks in the field. However, domain-specific further pre-training is expensive to acquire corpus data of the target domain. Furthermore, many cases have reported that performance improvement after further pre-training is insignificant in some domains. As such, it is difficult to decide to develop a domain-specific pre-trained language model, while it is not clear whether the performance will be improved dramatically. In this paper, we present a way to proactively check the expected performance improvement by further pre-training in a domain before actually performing further pre-training. Specifically, after selecting three domains, we measured the increase in classification accuracy through further pre-training in each domain. We also developed and presented new indicators to estimate the specificity of the domain based on the normalized frequency of the keywords used in each domain. Finally, we conducted classification using a pre-trained language model and a domain-specific pre-trained language model of three domains. As a result, we confirmed that the higher the domain specificity index, the higher the performance improvement through further pre-training.

• Journal of The Korean Association For Science Education
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• v.43 no.2
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• pp.139-150
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• 2023

This study started with the awareness of the need to explore various aspects of science education and was conducted according to the necessity of practical research on science cultural activities targeting adults. Accordingly, adults' book discussions of science fiction were selected as research cases, and science-related attitudes in science cultural activities were explored. There are four participants in the study, all of whom have engaged in a book club and have not majored or are working in science disciplines. Three science fictions were selected after establishing specific standards for the selection discussed with participants. For four months, a total of three unstructured book discussions of science fiction, post-interviews for each discussion, and in-depth individual interviews after the end of the entire activity were conducted. Various data such as recorded and transcribed reading discussion discourse, post- and in-depth individual interviews, researchers' observation records, and participants' book journals were collected and analyzed using a continuous comparison method. As a result of the study, as scientific thinking is illustrated in SF, the participants also demonstrated scientific attitudes during their discussions. In addition, the textual feature(storytelling) of science fiction was found to lessen cognitive overload and the burden of understanding science by providing scientific knowledge with context. Finally they demonstrated a shift in attitude toward science, valuing science cultural activities in themselves, rather than simply viewing science as a subject of understanding and learning. The conclusions and meanings of this study based on the above results are presented to enhance a positive attitude toward science for adults even after school education.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.79-104
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• 2020

Recently, as deep learning has attracted attention, the use of deep learning is being considered as a method for solving problems in various fields. In particular, deep learning is known to have excellent performance when applied to applying unstructured data such as text, sound and images, and many studies have proven its effectiveness. Owing to the remarkable development of text and image deep learning technology, interests in image captioning technology and its application is rapidly increasing. Image captioning is a technique that automatically generates relevant captions for a given image by handling both image comprehension and text generation simultaneously. In spite of the high entry barrier of image captioning that analysts should be able to process both image and text data, image captioning has established itself as one of the key fields in the A.I. research owing to its various applicability. In addition, many researches have been conducted to improve the performance of image captioning in various aspects. Recent researches attempt to create advanced captions that can not only describe an image accurately, but also convey the information contained in the image more sophisticatedly. Despite many recent efforts to improve the performance of image captioning, it is difficult to find any researches to interpret images from the perspective of domain experts in each field not from the perspective of the general public. Even for the same image, the part of interests may differ according to the professional field of the person who has encountered the image. Moreover, the way of interpreting and expressing the image also differs according to the level of expertise. The public tends to recognize the image from a holistic and general perspective, that is, from the perspective of identifying the image's constituent objects and their relationships. On the contrary, the domain experts tend to recognize the image by focusing on some specific elements necessary to interpret the given image based on their expertise. It implies that meaningful parts of an image are mutually different depending on viewers' perspective even for the same image. So, image captioning needs to implement this phenomenon. Therefore, in this study, we propose a method to generate captions specialized in each domain for the image by utilizing the expertise of experts in the corresponding domain. Specifically, after performing pre-training on a large amount of general data, the expertise in the field is transplanted through transfer-learning with a small amount of expertise data. However, simple adaption of transfer learning using expertise data may invoke another type of problems. Simultaneous learning with captions of various characteristics may invoke so-called 'inter-observation interference' problem, which make it difficult to perform pure learning of each characteristic point of view. For learning with vast amount of data, most of this interference is self-purified and has little impact on learning results. On the contrary, in the case of fine-tuning where learning is performed on a small amount of data, the impact of such interference on learning can be relatively large. To solve this problem, therefore, we propose a novel 'Character-Independent Transfer-learning' that performs transfer learning independently for each character. In order to confirm the feasibility of the proposed methodology, we performed experiments utilizing the results of pre-training on MSCOCO dataset which is comprised of 120,000 images and about 600,000 general captions. Additionally, according to the advice of an art therapist, about 300 pairs of 'image / expertise captions' were created, and the data was used for the experiments of expertise transplantation. As a result of the experiment, it was confirmed that the caption generated according to the proposed methodology generates captions from the perspective of implanted expertise whereas the caption generated through learning on general data contains a number of contents irrelevant to expertise interpretation. In this paper, we propose a novel approach of specialized image interpretation. To achieve this goal, we present a method to use transfer learning and generate captions specialized in the specific domain. In the future, by applying the proposed methodology to expertise transplant in various fields, we expected that many researches will be actively conducted to solve the problem of lack of expertise data and to improve performance of image captioning.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.35 no.3
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• pp.32-40
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• 2017

The introduction of neo-Confucianism as the ideological foundation of Joseon, and its root Confucianism have become the origin of the life, scholarship and ideology of the Korean people. Additionally, it was considered the best to follow the teachings of the discipline's advocates including Confucius (孔子), Mencius (孟子), Zisi (子思), ZhuXi (朱子). Among these teachers, ZhuXi was the one who overtly presented the way of self-discipline, of which goal lies in attaining the character by the manifestation of vitality (氣 ki) and rationality (理 i) and contemplating on them. As he regarded natural places with mountains and waters as stages and tools for practicing toward the enlightenment, Confucian scholars in Joseon also followed his example in the spirit of honoring and studying ZhuXi (尊朱子, 學朱子), which became the basic thoughts and practical philosophy among them. Ryu, Junggyo, the neo-Confucian dogmatist, was no exception to applaud the nature, as he designated and ruled Okgye Gugok. On the basis of these backgrounds, this study aims to estimate the geographic places of Okgye Gugok, which was set by Ryu, Junggyo, a Confucian scholar in late-Joseon period, by collecting and analyzing the basic data, starting from Gareung-gun Okgye Sansugi(嘉陵郡玉溪山水記) which is the primary text authored by Seongjae Ryu, Junggyo. The literature study is followed by ten field trips to the estimated locations of Okgye Gugok, and verification of the estimations by three locals who were born and raised in Okgye Gugok. Coordinates and photographs were obtained as spatial data for each location of nine Gok(曲) estimated through this study. They will serve as a primary and critical data for story-telling and tourism resource in Okgye Gugok. The significance of this study is that it provides the primary data for designating the locations of Gok(曲) in Okgyeo Gugok.

• Journal of Korean Home Economics Education Association
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• v.32 no.3
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• pp.97-110
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• 2020

The purpose of this study is to develop milk education materials for adults based on the scientific basis of right milk consumption in the format of card news that can be easily accessed on a mobile phone or the internet and has high impact. The topics to be included in the card news were selected based on the findings from literature analysis and focus group interviews with 10 adults(32.0±6.4 years). For the eight selected topics, effective communication was made by suggesting some information that users want to know while reflecting adult eating habits, lifestyle habits, and nutrition and health interests. The card news draft was reviewed by researcher and consulting experts, and then questionnaire survey was conducted using Likert 5-point scales by 50 adults(42.7±10.2 years). Based on the results of the review, consultation and questionnaire survey, a final draft of the card news consisting of 11 cuts was completed. Card news proposal is expected to produce educational effects, since the respondents showed high satisfaction with the card news (higher than 4 on the 5-point scales) according to the questionnaire survey. Adults can easily access and use the card news developed in this study, and thus this card news is expected to increase milk consumption in adulthood and improve nutrition and health through friendly and systematic milk education.

• Archives of design research
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• v.19 no.4 s.66
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• pp.41-50
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• 2006

It is generally regarded a design system in post-industrial society, which products designed by in-house designers or design consultancy are manufactured in factory and distributed in market for the consumer. Although it is treated an old design system in traditional society, the traces of vernacular design has been remaining in the state of adopted to the periodical needs in these days, also proving the attribute of design culture to constitute human's material environment as well as existing design systems. There were discovered various design artifacts in daily surroundings vary from the established design in several manners, user modifications or manufactures in everyday lives formalized them. It was approached a case study that analyze the changes of artifact configuration and designer/user context and creation process of the non-professional design artifacts, Creativity Template Theory and ACM(Artifact Context Model) have been utilized for the analysis model. From the analysis result, It assume that the everyday artifacts may be ordinary but extra-ordinary including particular ideas and identity represented by everyday designers or users. Beside these characteristics induce the potentiality that reflect on creative motives for the designers or a complementary artifact generator filling up with drawbacks in established design system. The everyday design domain, various explorations and alternatives are made, is seems to be another design practice domain dissimilar to the one in the industry-based design. Moreover it provides an more easily accessability for the approaching user-friendly design, user customization because they conduct the reliable modeling of consumer and end-user. Finally, based on the exploratory study regarding interpretation of context and configuration in the everyday artifacts, new approach for the design process and design education through more detailed cognitive modeling of everyday designers will be a further study.

• Cartoon and Animation Studies
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• s.35
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• pp.29-65
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• 2014

Visual culture art education (VCAE) seems to be the new paradigm for art education after postmodernism. Getting beyond the traditional art education, VCAE has expanded its scope of interest to include the visual environment that surrounds our life, thus pushing the boundary of art education beyond the traditional fine arts to cover pop culture and visual art. VCAE shares the issues as well as a lot of elements of culture and art education and in fact serves as a major theoretic background for culture and art education, in that it pays attention to the sociocultural context of images and emphasizes visual literacy and constructionist learning. In this paper, I have reviewed the theoretical background and related issues of VCAE with a view to presenting a direction for animation education, which is gaining in importance coming into the Age of Digital Media. VCAE was born in the progressive cultural atmosphere from the 1970s and thereafter, and its gist consists in figuring out visual artifacts and their action in order to improve individual and social life. Yet, VCAE continues with its development according to the changing aspects of visual culture, and currently, it is expanding its scope of interest to cover the esthetic, experiential education in visual culture and construction of meaning through digital story-telling. In the visual environment of the Digital Age, animation is establishing itself as the center of the visual culture, being a form that goes beyond an art genre or technology to realize images throughout the visual culture. Also, VCAE, which has so far emphasized visual communication and critical reading of culture, would need to reflect the new aspects of the visual culture in digital animation across the entire gamut from experiencing to understanding and appreciating art education. In this paper, I emphasize on Cross-Curricula, social reconstruction, the expansion of animation education, interests in animation as a digital media, and animation literacy. A study of animation education from the perspective of VCAE will not only provide a theoretical basis for establishing animation education, but also enrich the content of VCAE, traditionally focused on critical text reading, and promote its contemporary and futuristic orientation.

• Korean Journal of Environmental Agriculture
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• v.22 no.2
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• pp.148-152
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• 2003

The phosphorus(P) adsorption capacities of various filter media were investigated in relation to the size and types of fitter media to screen the optimum condition. The objective of this study was to evaluate the constructed wetland longevity by improving P adsorption capacity. The maximum P adsorption capacities of filter media A($4{\sim}10\;mm$), B($2{\sim}4\;mm$) and C($0.1{\sim}2\;mm$) were 8, 10 and 22 mg/kg, respectively, showing those increased as the filter media size decreased. Among the experimental media, the optimum filter media size was $0.1{\sim}2\;mm$. When the filter Medium was supplemented with organic materials which were piled up and decayed in the constructed wetland, the P adsorption capacity was significantly enhanced Under the conditions of optimum fitter media size, the respective Maximum P adsorption capacities of filter media C when supplemented with Ca, Mg, Al and Fe were higher than that of filter media C. However the addition of Ca, Mg, Al and Fe to constructed wetland were not recommended because of the possibility of their secondary pollution. The maximum P adsorption capacity of filter media C was 22 mg/kg, but this was increased to 36 mg/kg when filter media C was supplemented with 2% oyster shell.