• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.646-661
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• 2020

Technological innovations and fast-growing new internet businesses are changing the paradigm of traditional business management, having various impacts on society. The development of internet technology is also increasing the adverse effects on technological innovation, and in particular, cybercrime related to computers continues to increase with each technological innovation. The purpose of this study is to construct a cybercrime business model (CBM) by using the business model canvas (BMC) theory for cybercrime in order to reduce cybercrime, and this model is applied and analyzed based on types of Korean cybercrimes. For this study, a systematic literature review was conducted to determine the components of cybercrime, and 60 relevant documents were classified through a keyword-based literature search. Besides, qualitative research in the classified literature has led to the derivation of cybercrime into 18 sub-blocks and nine building blocks. This study applies BMC theory to this derivation of cybercrime and builds the CBM through proper redefinition. Lastly, the developed CBM could be applied to cybercrime in Korea to help cyber incident-response staff understand cybercrimes analytically. This study contributes to the development of a new analysis framework that can reduce cybercrime.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.1
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• pp.59-72
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• 2011

The research of psychological supporting systems as safety and welfare for disaster victims damaged psychologically as well as physically by a sudden disaster to return to effectively their social life has been carried. The domestic National Emergency Management Agency(NEMA) is operating the Disaster Victim Psychology Support Center that helps with curing damaged psychology and studies the transmission system of psychology management services, the classification of victims for disaster psychology support, and emergency consultation method to systemically support disaster psychology management. However, current psychology supporting centers provide the simple information for supporting centers such as medical and social welfare organizations. The development research of IT-based management systems to obtain needed information to construct the proposed systems curing psychological damage is still primitive step. Therefore, this paper shall propose a GIS-based integrated management system for victims and managers to effectively share related information one another and to return to victims' social life as soon as possible. Also, we implement a simple prototype system based on the Web. The proposed system supports the spatial search and statistical analysis based on map as well as keyword search, because having the location information on disaster victims, damage occurrence places, welfare and medical institutions, and psychological supporting centers. In addition, this system has the advantage reducing the frequency of disaster damage by providing aids in making efficient policy systems for the managers.

• Journal of Physiology & Pathology in Korean Medicine
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• v.29 no.4
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• pp.313-321
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• 2015

The purpose of this study is to analyze differences between domestic and international research about convergence in Korean medicine (KM) and to find plans to facilitate further convergence. Articles published from 1995 to 2015 were searched on domestic database, NDSL and international database, PUBMED using the keyword concerning to five subjects (device, treatment, education, drug, effect and mechanism). Two authors checked independently searched articles to decide inclusion on the analysis and the stage of convergence, and made a conclusion through discussion. 58 and 27 articles were included in domestic and international research respectively on five subjects mentioned above. Articles in treatment and effect and mechanism were the most in domestic (62%) and international research (37%) individually. On the stage of convergence (It is divided by the degree of mixing between resource, experience, and theory of KM and other fields of study), most of articles were included in the first and second stage in domestic (62%) and international research (85%) respectively. Domestic and international research had different characteristics on the main subjects as well as the stage of convergence. It is needed that more active research and realistic application to facilitate further convergence.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.688-701
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• 2020

In this study, a total of 68 domestic and international papers were selected from 1993 to August 2020 in order to examine the research trends related to artificial intelligence for the visually impaired. The papers were compared and analyzed by the number of papers published by year, research method, research topic, keyword analysis status, research type, and implementation method. As a result of the study, the number of papers during the study period seemed to increase steadily. But in the case of domestic research, It can be seen that it has become active since 2016. As for research methods, development research accounted for 89.7% of both domestic and foreign research. Keywords was in Visually Impaired, Deep Learning, and Assistive Device order in domestic research. And it was in Visually Impaired, Deep learning, Artificial intelligence order in foreign research. There was a difference in the frequency of words. Research type were Design, development and implementation both in domestic and foreign. Implementation method were in System 13.2%, Solution 7.4%, App. 4.4% order in domestic research, and it was in System 32.4%, App. 13.2%, Device 7.4% order in foreign research. As for the applied technology of the implementation method, were in YOLO 2.7%, TTS 2.1%, Tensorflow 2.1% order in domestic research, and it was used in CNN 8.0%, TTS 5.3%, MS-COCO 4.3% order in foreign research. The purpose of this study was to compare and analyze the trends of artificial intelligence-related research targeting the visually impaired, to immediately know the current status of domestic and foreign research, and to present the direction of artificial intelligence research for the visually impaired in the future.

• Journal of the Korean School Mathematics Society
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• v.15 no.1
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• pp.81-108
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• 2012

One of the keyword in every nation's recent educational policy is key competencies. Considering national competitiveness originating from educational competitiveness, educational policy has been driven to identify key competencies and realize them through school education. Within this context some countries have developed competencies-based curriculum and discussed ways to relate key competencies and subject matter areas. However, there have been few researches on how to reflect or integrate key competencies into subject matter areas. Because of this reason, the ways to incorporate and integrate key competencies into three subject areas including mathematics were investigated. The recent trends of curriculum, teaching and learning, and assessment of domestic and foreign cases were explored by the subject of one Korean international middle school, one British foreign school in Seoul, one French foreign school in Seoul, and four middle schools in New Zealand. To establish competencies-based school education, there should be intimate connection system among curriculum, teaching and learning, assessment, and teacher education. Through analysis of domestic and foreign cases, some conclusions regarding how these aspects have changed with the emphasis of key competencies were drawn. In this paper, through classroom observation and teacher interview, a case of the competencies-based mathematics lessons of one French foreign school was investigated. As a result, summaries and recommendations related to ways to improve subject teaching and teacher education in light of key competencies were presented. In these recommendations, the ways to reconstruct subject-based curriculum, the content-specific teaching and learning, and educational assessment were included.

• Journal of the Korean School Mathematics Society
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• v.15 no.2
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• pp.215-238
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• 2012

One of the keyword in every nation's recent educational policy is key competencies. Considering national competitiveness originating from educational competitiveness, educational policy has been driven to identify key competencies and realize them through school education. Within this context some leading countries have developed competencies-based curriculum and discussed ways to relate key competencies and subject matter areas. However, there have been few researches on how to reflect or integrate key competencies into subject matter areas. Because of this reason, the ways to incorporate and integrate key competencies into three subject areas including mathematics were investigated. The recent trends of curriculum, teaching and learning, and assessment of domestic and foreign cases were explored by the subject of one Korean international middle school, one British foreign school in Seoul, one French foreign school in Seoul, and four middle schools in New Zealand. To establish competencies-based school education, there should be intimate connection system among curriculum, teaching and learning, assessment, and teacher education. Through analysis of domestic and foreign cases, some conclusions regarding how these aspects have changed with the emphasis of key competencies were drawn. In this paper, through classroom observations and teacher interviews, the reality of competencies-based mathematics teaching of New Zealand and France was investigated. As a result, summaries and recommendations related to ways to improve subject teaching and teacher education in light of key competencies were presented. In these recommendations, the ways to reconstruct subject-based curriculum, the content-specific teaching and learning, and educational assessment were included.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1055-1062
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• 2002

Recently, the lesson plan document that is imported in the educational area is not provided to the educational information systematically, and the teachers are not easy to compose the lessen plan documentation. So, it needs additional time and effort to develope the lesson plan documents. Because of increasing the distributing network. web-based lesson plan system is required to all of the education area. Therefore, we need to compose the lesson plan that is possible to obtain the various teacher's requirement by providing creation, retrival, and reusability of document using the standard XML on web. In this paper, we developed the system for creating the common DTD (Document Type Definition), providing the standard XML document through the common DTD over the lesson plan analysis. In this system, it provides the editor to compose the lesson plan and supports the searching function to improvement of reusability on the existing lesson plan. We design the searching functions such as the structure base, facet and keyword. The composed lesson plans are interoperated with Database. Consequently, we can share the information on web by composing the lesson plan using the XML and save the time and cost by directly writing the lesson plan on web. We can also provide the improved learning environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.345-351
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• 2020

Administrative agencies today are paying keen attention to big data analysis to improve their policy responsiveness. Of all the big data, news articles can be used to understand public opinion regarding policy and policy issues. The amount of news output has increased rapidly because of the emergence of new online media outlets, which calls for the use of automated bots or automatic document classification tools. There are, however, limits to the automatic collection of news articles related to specific agencies or departments based on the existing news article categories and keyword search queries. Thus, this paper proposes a method to process articles using classification glossaries that take into account each agency's different work features. To this end, classification glossaries were developed by extracting the work features of different departments using Word2Vec and topic modeling techniques from news articles related to different agencies. As a result, the automatic classification of newspaper articles for each department yielded approximately 71% accuracy. This study is meaningful in making academic and practical contributions because it presents a method of extracting the work features for each department, and it is an unsupervised learning-based automatic classification method for automatically classifying news articles relevant to each agency.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.412-425
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• 2008

One of the important elements for improving academic achievement of learners in education through e-learning is to support learners to study by finding questions they want with providing various evaluation questions. However, most of question retrieval systems usually depend on keyword search based on only a syntactical analysis and/or a hierarchical browsing system classified by the topics of subjects. In such a system it is not easy to find integrative questions associated with each other. In order to improve this problem, in this paper we proposed a question management and retrieval system which allows users to easily manage questions and also to effectively find questions for study on the Web. Then, we implemented a system that gives to access questions for the domain of C language programming. The system makes it possible to easily search questions related to not only a single theme but also questions integrated by interrelationship between topics and questions. This is done by supporting to be able to retrieve questions according to conceptual interrelationships between questions from user query. Consequently, it is expected that the proposed system will provide learners to understand the basic theories and the concepts of the subjects as well as to improve the ability of comprehensive knowledge utilization and problem-solving.