• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Journal of Korean Society of Forest Science
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• v.108 no.1
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• pp.88-96
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• 2019

The purpose of this study is to understand when forest fire as a natural phenomenon becomes constructed as social issues in Korea; how the forest fire-related discourses in the editorials reflecting the social perceptions have been changed regarding the principal subject and the measures of the forest fire management; and whether the social perception on the forest fire affects the forest fire policy of the state. From the analysis of a total of 44 editorials related to forest fires from 1988 to 2017. By the using, in the forest fire-related editorials the social perceptions on forest fires are forest fire editorials categories, main keywords, contents of social perception on 'the main subject responsible for forest fire management,' 'forest fire prevention measures,' categorization, frequency analysis and context analysis of words used. It is found that in the first-period forest fire management measures were recognized as a part of the overall forest management. In the second period, the approaches of ecological management emerged on the part of forest fire management. As forest fires were managed as a type of social disaster during the third period, such perceptions were gradually reinforced that the state should protect the people from the forest fire. In the 3rd, 4th, and 5th National Forest Plan, the forest fire management policy of each period was focused in enlightening the general public, protecting forest resources ecosystems, and preventing loss of lives, respectively. As a result of the analysis of social perceptions and comparing them to the forest fire policies through the analysis of editorials on forest fires, it is found that the social perception on the forest fire and forest fire management plan has changed having interconnections.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.12-28
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• 2021

Based on the global smart city promotion trend, in 2018, the "Fourth Industrial Revolution Committee" selected "sustainability" and "people-centered" as keywords in relation to the direction of domestic smart city policy. Accordingly, the Living Lab program, which is an active citizen-centered innovation methodology, is applied to each stage of the domestic smart city construction project. Through the Living Lab program, and in collaboration with the public and experts, the smart city discovers local issues as it focuses on citizens, devises solutions to sustainable urban problems, and formulates a regional development plan that reflects the needs of citizens. However, compared to citizen participation in urban regeneration projects that have been operated for a relatively long time, participation in smart city projects was found to significantly differ in level and sustainability. Therefore, this study conducted a comparative analysis of the characteristics of citizen participation at each stage of an urban regeneration project and, based on Arnstein's "Participation Ladder" model, examined the level of citizen participation activities in the Living Lab program carried out in a smart city commercial area from 2018 to 2019. The results indicated that citizen participation activities in the Living Lab conducted in the smart city project had a great influence on selecting smart city services, which fit the needs of local residents, and on determining the technological level of services appropriate to the region based on a relatively high level of authority, such as selection of smart city services or composition of solutions. However, most of the citizen participation activities were halted after the project's completion due to the one-off recruitment of citizen participation groups for the smart city construction project only. On the other hand, citizens' participation activities in the field of urban regeneration were focused on local communities, and continuous operation and management measures were being drawn from the project planning stage to the operation stage after the project was completed. This study presented a plan to revitalize citizen participation for the realization of a more sustainable smart city through a comparison of the characteristics and an examination of the level of citizen participation in such urban regeneration and smart city projects.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.374-390
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• 2021

Growth and yield of field vegetable crops would be affected by climate conditions, which cause a relatively large fluctuation in crop production and consumer price over years. The yield prediction system for these crops would support decision-making on policies to manage supply and demands. The objectives of this study were to compile literatures related to onion and garlic and to perform data-mining analysis, which would shed lights on the development of crop models for these major field vegetable crops in Korea. The literatures on crop growth and yield were collected from the databases operated by Research Information Sharing Service, National Science & Technology Information Service and SCOPUS. The keywords were chosen to retrieve research outcomes related to crop growth and yield of onion and garlic. These literatures were analyzed using text mining approaches including word cloud and semantic networks. It was found that the number of publications was considerably less for the field vegetable crops compared with rice. Still, specific patterns between previous research outcomes were identified using the text mining methods. For example, climate change and remote sensing were major topics of interest for growth and yield of onion and garlic. The impact of temperature and irrigation on crop growth was also assessed in the previous studies. It was also found that yield of onion and garlic would be affected by both environment and crop management conditions including sowing time, variety, seed treatment method, irrigation interval, fertilization amount and fertilizer composition. For meteorological conditions, temperature, precipitation, solar radiation and humidity were found to be the major factors in the literatures. These indicate that crop models need to take into account both environmental and crop management practices for reliable prediction of crop yield.

• Journal of the Daesoon Academy of Sciences
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• v.37
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• pp.191-227
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• 2021

In this study, values of truth and good are expressed in the form of beauty, and truth and good are analyzed from an aesthetic point of view. This enables an assessment of how truth is expressed and presented as an "aesthetic" in Daesoon Thought. Therefore, an approach to faith in Daesoon Jinrihoe (大巡眞理會) can be presented via traditional aesthetics or theological aesthetics that reflect on sense experience, feelings, and beauty. The concept of beauty in Daesoon Thought which focuses on The Canonical Scripture appears in keywords used in Daesoon Thought such as divine nature (神性), the pattern of Dao (道理), the singularly-focused mind (一心), and relationships (關係). Therein, one can find sublimation, symmetry, moderation, and harmony. The aesthetic features of Daesoon Thought, when considered as an aesthetic system can formulate thinking regarding the aesthetics of 'Reordering Works of Heaven and Earth' (天地公事), the aesthetics of Mutual Beneficence (相生), and the aesthetics of healing. The Reordering Works of Heaven and Earth contain a record of the Supreme God visiting the world as a human being. The realization that the human figure, Kang Jeungsan (1871-1909), is the Supreme God, Sangje (上帝), is the shocking aesthetic motif and theological starting point of the Reordering Works of Heaven and Earth. Mutual Beneficence can be seen aesthetically as indicating the sociality of mutual relations, and there is an aesthetic structure of Mutual Beneficence in the harmony and unification of those relations. Healing can be said to contain the sacred sublimation of Sangje, and moderation is a form of beauty that makes humans move toward Quieting the mind and Quieting the body (安心·安身), the Dharma of Presiding over Cures (醫統), and the ultimate value of healing, which is the end point of the Cultivation (修道) wherein one realizes that the ideals of humankind and the aesthetics of healing bestow the spiritual pleasures of a beautiful and valuable life. The aesthetic characteristics of Daesoon Thought demonstrate an aesthetic attitude that leads to healing through Sangje's Holy Works and the practice of Mutual Beneficence (相生) which were performed when He stayed with us to vastly save all beings throughout the Three Realms that teetered on the brink of extinction. It is not uncommon to see a beautiful woman and remark she is like a goddess (女神) or female immortal (仙女). Likewise, beautiful music is often praised as "the sound of heaven." That which fills us with joy is spoken of as "divine beings (神明)" of God. God is a symbol of beauty, and the world of God can be said to be the archetype of beauty. Experience of beauty guides our souls to God. The aesthetic experience of Daesoon Thought is a religious experience that culminates in emotional, intellectual, and spiritual joy, and it is an aesthetic experience that recognizes transcendent beauty.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.202-217
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• 2022

Purpose: The recent increased use of Personal Mobility (PM) has been accompanied by a rise in the annual number of accidents. Accordingly, the safety requirements for PM use are being strengthened, but the laws/systems, infrastructure, and management systems remain insufficient for fostering a safe environment. Therefore, this study comprehensively searches the main problems and improvement methods through a review of previous studies that are related to PM. Then the priorities according to the importance of the improvement methods are presented through the Delphi survey. Method: The research method is mainly composed of a literature study and an expert survey (Delphi survey). Prior research and improvement cases (local governments, government departments, companies, etc.) are reviewed to derive problems and improvements, and a problem/improvement classification table is created based on keywords. Based on the classification contents, an expert survey is conducted to derive a priority improvement plan. Result: The PM-related problems were in 'non-compliance with traffic laws, lack of knowledge, inexperienced operation, and lack of safety awareness' in relation to human factors, and 'device characteristics, road-drivable space, road facilities, parking facilities' in relation to physical factors. 'Management/supervision, product management, user management, education/training' as administrative factors and legal factors are divided into 'absence/sufficiency of law, confusion/duplication, reduced effectiveness'. Improvement tasks related to this include 'PM education/public relations, parking/return, road improvement, PM registration/management, insurance, safety standards, traffic standards, PM device safety, PM supplementary facilities, enforcement/management, dedicated organization, service providers, management system, and related laws/institutional improvement', and 42 detailed tasks are derived for these 14 core tasks. The results for the importance evaluation of detailed tasks show that the tasks with a high overall average for the evaluation items of cost, time, effect, urgency, and feasibility were 'strengthening crackdown/instruction activities, education publicity/campaign, truancy PM management, and clarification of traffic rules'. Conclusion: The PM market is experiencing gradual growth based on shared services and a safe environment for PM use must be ensured along with industrial revitalization. In this respect, this study seeks out the major problems and improvement plans related to PM from a comprehensive point of view and prioritizes the necessary improvement measures. Therefore, it can serve as a basis of data for future policy establishment. In the future, in-depth data supplementation will be required for each key improvement area for practical policy application.

• 한국노년학
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• v.40 no.4
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• pp.801-821
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• 2020

There are a number of prior studies on the poverty experience of Korean women, but little is known about the poverty experience of Korean elderly women in the U.S. The purpose of this study is to examine the poverty experiences of Korean elderly women who immigrated to the U. S. Qualitative case study methods were used to achieve these research objectives. Three Korean elderly women living in Oakland of California who received Supplemental Security Income (SSI) from the U.S. federal government were included in the study. The data were collected by conducting a total of six meetings per participant, and the researcher read the consent form directly to the participants and obtained a hand-written signature. The analysis and interpretation began by repeating the interview transcript several times, and the repeated keywords were to be understood in the context, focusing on time, space, and relationships with other people. The contextual understanding of Korean elderly women's experiences in poverty was interpreted in three dimensions: extending poverty in their mother country, double torture as female immigrants, and limiting labor due to aging and diseases. Before moving to the U.S., they had a difficult livelihood by farming and one of them had to live in poverty due to the bereavement to her husband. But even after moving to the U.S., they have continued to live in poverty. As female immigrants with low education and no special skills, they were incorporated into the periphery of the labor market in the industrialized U.S. and were forced to make a living with low wages. Korean elderly women were unable to return to the labor market in the surrounding areas due to aging and diseases, and were continuing their impoverished lives relying on SSI. From the findings, we discussed the role of the Korean immigrants community as a way to improve the quality of life for Korean elderly women in the U.S.

• Journal of Christian Education in Korea
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• v.71
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• pp.181-210
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• 2022

The purpose of this study was to investigate the research trends related to the children's department of church schools. The purpose of this study is to present basic data for the study of the children's department of church schools by analyzing the research period, research contents, research methods, and subjects of research related to the children's department of church schools. For this study, 50 domestic master's and doctoral dissertations searched through the National Assembly Library and the Research Information Sharing Service(RISS) were extracted with the keywords of 'church school' and 'children's department'. The frequency and percentage were calculated by analyzing the research related to the children's department of the church school according to four criteria: research period, research content, research method, and research subject. As a result of the study, first, the research trend of research papers in the children's department of church schools was found to be 49 articles (98%) for master's degrees and 1 article (2%) for doctoral degrees from 1980 to 2022. Trends by research period are focused on master's degrees. Second, the trend by research content was 27 practical studies (54%) and 23 theory studies (46%). In the research related to the children's department of church schools, the practical research accounted for a relatively high percentage compared to the theory research. Third, the trends by research method were in the order of 30 literature studies (60%), 19 quantitative studies (38%), and 1 qualitative study (2%). Research related to children's departments in church schools is being actively conducted with a focus on literature research. Fourth, as for the trends by study subject, the study was conducted focusing on physical subjects, with 35 subjects (70%) and 15 subjects (30%) of personal subjects. As research is conducted from physical objects to church schools and media, it is necessary to study the connection between church schools and families. As the research on church school kindergarten is focused on adults (teachers, parents, and educational preachers), in-depth research on children in church schools and qualitative research with voices from the field of children's department in church schools are required.