• 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.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• The Korean Journal of Blood Transfusion
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• v.23 no.2
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• pp.115-126
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• 2012

Background: Umbilical cord (UC) is a promising source of mesenchymal stromal cells (MSCs). We compared the characteristics of MSCs from cryopreserved UC with those from fresh tissues, and demonstrated the possibility of UC cryopreservation for acquisition of MSCs from cryopreserved UC. Methods: Each UC was sliced into two types ($1{\sim}2mm^3$ vs. 0.5 cm), and cryopreserved in liquid nitrogen using different media (autologous cord blood plasma, aCBP vs. RPMI 1640). A fresh aliquot of $1{\sim}2mm^3$-sized UC was used as control tissue. After one week, the cryopreserved tissues were thawed and cultured. For the 0.5 cm UC, a slicing step into $1{\sim}2mm^3$ was needed. Cell count, viability, proliferative activity, and surface antigens were determined from harvested MSCs. Several growth factors (EGF, IGF-1, PDGF, TGF-${\beta}$, bFGF, and VEGF), were measured from the culture supernatant. Results: Eleven UC were enrolled in the study. Efficiencies of obtaining MSCs were higher in cryopreserved UC using RPMI 1640, compared with use of aCBP; the same result was observed for 0.5 cm sized UC, compared with $1{\sim}2mm^3$ sized UC. No difference in proliferative activity was observed between MSCs from fresh and cryopreserved UC. The amount of growth factors in culture supernatant using RPMI 1640 was larger than that of fresh tissues. Conclusion: We obtained growth factors from the supernatant as well as MSCs from cryopreserved UC. As with a cord blood bank, in the future, cryopreservation of UC for acquisition of both MSCs and growth factors would be possible in a time of need.

• Review of Culture and Economy
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• v.21 no.2
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• pp.141-173
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• 2018

In this article, we explore how artistic fame is formed by analyzing antecedents of fame the extent to which the name of an actor or his/her work is positively known by his/her audiences among Korean handicraft artists. Drawing on prior literature on reputation and fame, we clarify the differences between the concept of reputation and the concept of fame and further distinguish three types of reputation among individual artists, depending on its sources expert reputation, market reputation, and peer reputation. We employ the mixed method in this study, in which we first conducted open-end interviews with three kinds of constituents (i.e., critics, market intermediaries, and artists) and then developed and tested the hypotheses derived from the insights we had obtained from the interviews. We further considered the impact of reputational work, defined as the level of effort devoted and activities performed by an artist him(her)self geared toward promoting his(her) work, on artistic fame. We find that there are large differences in factors associated with artistic fame between non elite and elite Korean handicraft artist groups, where elite status is captured by artists' educational background (i.e., Seoul National University and Hongik University, which are considered elite schools in accordance with prior research). Specifically, findings suggest that among non elite status artists, recognition by experts, or what we call expert reputation, acquired through national awards and invitations from prominent exhibitions as well as artists' own reputational work that incurs high cost, such as self-financed exhibition openings, were shown to be highly significant factors associated with artistic fame, which was measured as the number of media exposures related to her/his art work. By contrast, among elite status artists, peer reputation acquired through an artist's institutional affiliations and relatively low cost artists' own reputational work, such as self listing on a highly publicized magazine, were shown to be significant factors associated with fame. Taken together, this paper contributes to research on cultural industries and markets by highlighting the importance of understanding artistic fame not just as the outcome of her/his talent but as the social product that arises at the intersection of actors (artists) and her/his audiences in the social evaluation process.

• Journal of Christian Education in Korea
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• v.67
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• pp.301-337
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• 2021

The researcher looked at the differences in views and various controversies surrounding Korean youth sexuality education in the wake of the Nth Room incident, which had a great impact on modern Korean society. Sex education for adolescents in Korea can be divided into public sex education through school sex education and the Youth Sexuality Center, and conservative/traditional Protestant sex education. Public sex education is partly influenced by feminist sexual ethics and comprehensive sex education abroad. Based on gender sensitivity and the right to sexual self-determination, four major projects are prevention of sexual harassment, prostitution, sexual violence, and domestic violence. However, the school sex education standard was criticized for stereotypes of gender roles and gender-discriminatory content, reinforced distorted myths about sexual violence, and exclusion of sexual diversity and various family types. Conservative/traditional Protestantism is based on the normal family ideology such as bisexual marriage, premarital chastity, and sexual ethics recognized only within marital relationships. It is a form of confrontation with public sex education while strongly opposing it. The researcher first analyzed the characteristics of public sex education, conservative/traditional Protestant sexual ethics and sex education, feminist sex ethics and sex education, and overseas youth sex education, respectively, while composing the curriculum for Korean youth sexuality education. And as a more fundamental solution to youth sexuality education, I pointed out that there are limits to asceticism, premarital chastity, gender sensitivity and sexual self-determination education, and found an alternative to the concept of body and sex in feminist theology. The researcher pointed out that it is necessary to reconceptualize the body and sex under the recognition that the most fundamental cause of distorted sexual culture is dualistic sex and understanding the body, centering on the research of various feminist theologians. And this was conceptualized into three concepts: holistic sexuality, mutual solidarity understood in relationships with others, and sexuality as a spirituality that extends to the global community. And with each curriculum, 1) Holistic Sexuality: Breathing, Narrative, Making the Shape of One's Body and Mind 2) mutual solidarity : Feeling the Breath of Others, Media Literacy through Conscientization, Sending a Good Wind 3) Sexuality as a spirituality that extends to global concern: It was proposed to pay attention to nature and to co-cultivate it, to listen to the earth's moans and create a new way of life, and to write a prayer with the earth and fellow living beings.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.89-115
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• 2019

This study was conducted to present the stylistic differences between Arthur Conan Doyle and Agatha Christie, famous as writers of classical mystery novels, through data analysis, and further to present the analytical methodology of the study of style based on text mining. The reason why we chose mystery novels for our research is because the unique devices that exist in classical mystery novels have strong stylistic characteristics, and furthermore, by choosing Arthur Conan Doyle and Agatha Christie, who are also famous to the general reader, as subjects of analysis, so that people who are unfamiliar with the research can be familiar with them. The primary objective of this study is to identify how the differences exist within the text and to interpret the effects of these differences on the reader. Accordingly, in addition to events and characters, which are key elements of mystery novels, the writer's grammatical style of writing was defined in style and attempted to analyze it. Two series and four books were selected by each writer, and the text was divided into sentences to secure data. After measuring and granting the emotional score according to each sentence, the emotions of the page progress were visualized as a graph, and the trend of the event progress in the novel was identified under eight themes by applying Topic modeling according to the page. By organizing co-occurrence matrices and performing network analysis, we were able to visually see changes in relationships between people as events progressed. In addition, the entire sentence was divided into a grammatical system based on a total of six types of writing style to identify differences between writers and between works. This enabled us to identify not only the general grammatical writing style of the author, but also the inherent stylistic characteristics in their unconsciousness, and to interpret the effects of these characteristics on the reader. This series of research processes can help to understand the context of the entire text based on a defined understanding of the style, and furthermore, by integrating previously individually conducted stylistic studies. This prior understanding can also contribute to discovering and clarifying the existence of text in unstructured data, including online text. This could help enable more accurate recognition of emotions and delivery of commands on an interactive artificial intelligence platform that currently converts voice into natural language. In the face of increasing attempts to analyze online texts, including New Media, in many ways and discover social phenomena and managerial values, it is expected to contribute to more meaningful online text analysis and semantic interpretation through the links to these studies. However, the fact that the analysis data used in this study are two or four books by author can be considered as a limitation in that the data analysis was not attempted in sufficient quantities. The application of the writing characteristics applied to the Korean text even though it was an English text also could be limitation. The more diverse stylistic characteristics were limited to six, and the less likely interpretation was also considered as a limitation. In addition, it is also regrettable that the research was conducted by analyzing classical mystery novels rather than text that is commonly used today, and that various classical mystery novel writers were not compared. Subsequent research will attempt to increase the diversity of interpretations by taking into account a wider variety of grammatical systems and stylistic structures and will also be applied to the current frequently used online text analysis to assess the potential for interpretation. It is expected that this will enable the interpretation and definition of the specific structure of the style and that various usability can be considered.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.1
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• pp.57-75
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• 2019

Soundscapes have the potential to help people experience the historical background and cultural traditions by the scenery of a local area and to be used as a cultural and tourism resource. This concept was first explained in detail by M. Schafer and has been developed as a new way of experiencing landscapes using various senses. This research studied the soundscape of Kyodong Island, the so-called "Island of Peace" and designed new cultural acoustic content for education and tourism. Kyodong Island is located right below the Northern Limit Line and the whole island is in the Civilian Controlled Area. The political and economic status of the island has been changed dynamically by the Korean War and the division of the country. These days, the island needs to realize the vision of the "Island of Peace" in a more creative way using local resources, including its "cold war landscape" and the natural scenery of the region. This research applied the concept of a soundscape to document the island, and to reproduce it in an artistic way. A workshop was conducted to learn concepts and techniques of soundscapes with a sound artist. Listening, recording, conducting interviews, and literature research was used to study the soundscape of the island. After that, this research reconstructed the soundscape of the island through a soundscape composition. The main theme of the composition story was the "Hope and Wish for the Harmony and Peace" to show the vision of the "Island of Peace". The initial sub-theme for the introduction part was "First Encounter with Kyodong Island" arranging the representative soundscape, which could be the first impression of the region. The second sub-theme was "War and Tension" using several soundscapes as a metaphor for the tragedy of the Korean War. The third sub-theme was "Everyday Life of Kyodong Island" which described the energy of the present day, after the wounds of the war have healed. The final sub-theme was "Harmony and Peace" using traditional music and keynote sounds of the region as a reminder of the peaceful past, before the war. The recording files were documented as two types of sound maps. One was a two-dimensional map to show the soundscapes from one point of view, and the other used the online application called "Sound Around You". The final artwork was displayed at an exhibition and uploaded on YouTube to be shared publicly. Through this project, we discovered the potential of soundscapes as a medium to preserve the history and local identity, as well as presenting a new vision. The artwork will be exhibited at historically and culturally meaningful places on the Island to utilize the underused places as local tourist attractions and educational resources.

• Food Engineering Progress
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• v.21 no.2
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• pp.158-166
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• 2017

Although Semisulcospira libertina is generally regarded as a supplement for the alleviation of alcohol hangover, little is known about its effects on cell metabolism. Therefore, this study was conducted to analyze the constituents of the extracts prepared using different extraction methods and to compare their biochemical properties. The amino acid contents were found to be much higher in acidic and enzymatic hydrolysates than hot water extracts from S. libertina. DPPH radical scavenging activities in acidic and enzymatic hydrolysates were higher than those of hot water extracts. Three types of S. libertina hydrolysate was added to HepG2 cells damaged by acetaminophen (AAP), after which the survival rate of HepG2 cell were measured. In addition, lactate dehydrogenase (LDH) activities in the culture media were evaluated. The survival rates of HepG2 cells were $77.0{\pm}4.3%$ and $81.5{\pm}1.3%$ at 3 h and 5h enzymatic hydrolysates, respectively. These cell survival rates were higher compared to those of the negative control group ($67.8{\pm}4.3%$) treated only with acetaminophen. Cellular toxicities induced by treatment with AAP were also significantly alleviated in response to treatment with the extracts of S. libertina. In addition, the activities of 2 key enzymes that metabolize ethanol, alcohol dehydrogenase and aldehyde dehydrogenase, were upregulated by 4.7- and 2.7-fold respectively in response to treatment with a 3 h enzymatic hydrolysate of S. libertina. Taken together, these results provide biochemical evidence of the method by which S. libertina exerts its biological functions, including the alleviation of alcohol hangover and the protection of liver cells against toxic insults.

• Korea Science and Art Forum
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• v.37 no.5
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• pp.119-133
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• 2019

This study is as skyscrapers are becoming increasingly taller, more constructors have decided the height alone cannot be a sufficient differentiator. As a result, atypical architecture is emerging as a new competitive factor. Also, it can be used for symbolizing the economic competitiveness of a country, city, or business through its form. Before the introduction of digital media, there was a discrepancy between the structure and form of a building and correcting this discrepancy required a separate structural medium. Since the late 1980s, however, digitally-based atypical form development began to be used experimentally, and, until the 2000s, it was used mostly for super-tall skyscrapers for offices or for industrial chimneys and communication towers. Since the 2000s, many global brand hotels and commercial and residential buildings have been built as super-tall skyscrapers, which shows the recent trend in architecture that is moving beyond the traditional limits. Complex atypical structure is formed and the formative characteristics of diagonal lines and curved surfaces, which are characteristics of atypical architecture, are created digitally. Therefore, it's goal is necessary to identify a new relationship between the structure and forms. According to the data of Council on Tall Buildings and Urban Habitat (CTBUH), 100-story and taller buildings were classified into typical, diagonal, curved, and segment types in order to define formative shapes of super-tall skyscrapers and provide a ground of the design process related to the initial formation of the concept. The purpose of this study was to identify the correlation between different forms for building atypical architectural shapes that are complex and diverse. The study results are presented as follows: Firstly, complex function follows convergence form characteristics. Secondly, fold has inside of architecture with repeat. Thirdly, as curve style which has pure twist, helix twist, and spiral twist. The findings in this study can be used as basic data for classifying and predicting trends of the future super-tall skyscrapers.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.21-35
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• 2022

The recommended meal composition allows the general people to organize meals using the number of intakes of foods from each of six food groups (grains, meat·fish·eggs·beans, vegetables, fruits, milk·dairy products and oils·sugars) to meet Dietary Reference Intakes for Koreans (KDRIs) without calculating complex nutritional values. Through an integrated analysis of data from the 6th to 7th Korean National Health and Nutrition Examination Surveys (2013-2018), representative foods for each food group were selected, and the amounts of representative foods per person were derived based on energy. Based on the EER by age and gender from the KDRIs, a total of 12 kinds of diets were suggested by differentiating meal compositions by age (aged 1-2, 3-5, 6-11, 12-18, 19-64, 65-74 and ≥ 75 years) and gender. The 2020 Food Balance Wheel included the 6th food group of oils and sugars to raise public awareness and avoid confusion in the practical utilization of the model by industries or individuals in reducing the consistent increasing intakes of oils and sugars. To promote the everyday use of the Food Balance Wheel and recommended meal compositions among the general public, the poster of the Food Balance Wheel was created in five languages (Korean, English, Japanese, Vietnamese and Chinese) along with card news. A survey was conducted to provide a basis for categorizing nutritional problems by life cycles and developing customized web-based messages to the public. Based on survey results two types of card news were produced for the general public and youth. Additionally, the educational program was developed through a series of processes, such as prioritization of educational topics, setting educational goals for each stage, creation of a detailed educational system chart and teaching-learning plans for the development of educational materials and media.