• Economic and Environmental Geology
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• v.52 no.2
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• pp.169-188
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• 2019

This study was carried out unmanned aerial photography and terrestrial laser scanning to establish digital database on original wall of Gyejoksanseong fortress, and measured ground control points for continuity of the monitoring. It also performed precise examination with the naked eye, unmanned aerial photogrammetry, endoscopy, total station and handy measurement to examine the structural stability of the original walls. The ground control points were considered as a point where visual field can be secured, 3 points were selected around each of the south and north walls. For the right side of the south original wall, aerial photogrammetry was conducted using drones and a deviation analysis of 3-dimensional digital models was performed for short-term monitoring. As a result, the two original walls were almost matched in range within 5mm, and no difference indicating displacement of stones was found, except for partial deviation. Regular monitoring of the areas with structural deformation such as bulging, weak and fracture zone by precisely examining with the naked eye and using high-resolution photo data revealed no distinct change. The inner foundation observed through endoscopy found out that filling stones of the original walls were still remained, while most filling soil was lost. As a result of measuring the total station focusing around the points with structural deformation on the original walls, the maximum displacements of the north and south walls were somewhat high with 6.6mm and 3.8mm, respectively, while the final displacements were relatively stable at below 2.9mm and 1.4mm, respectively. Handy measurement also did not reveal clear structural deformation with displacements below 0.82mm at all points. Even though the results of displacement monitoring on the original walls are stable, it is hard to secure structural stability due to the characteristics of ramparts where sudden brittle fracture occurs. Therefore, it is necessary to conduct conservational scientific diagnosis, precise monitoring, and structural analysis based on the 3-dimensional figuration information obtained in this research.

• 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.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• Journal of The Korean Association For Science Education
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• v.43 no.1
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• pp.17-28
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• 2023

In line with the entry into the digital-based intelligent information society, the science curriculum emphasizes the cultivation of scientific competencies, and computer-based test (CBT) is drawing attention for assessment of competencies. CBT has advantages to develop items that have high fidelity, and to establish a feedback system by accumulating results into the database. However, it is necessary to solve the problems of improving validity of assessment results, lowering measurement efficiency, and increasing management factors. To examine students' responses to the introduction of the new assessment tools in the process of transitioning from paper-based test (PBT) to CBT, in this study, we analyzed the results of the PBT and the CBT conducted in 2021 National Assessment of Educational Achievement (NAEA). In particular, we sought to find the effects on student achievement when only the mode of assessment was changed without change of items, and the effect on student achievement when the items were composed including technology enhanced features that take advantage of CBT. This study is derived through the analysis of the results of 7,137 third-grade middle school students taking one among the three kinds of assessments, which were the PBT or two kinds of CBT. After the assessment, the percentage of correct answers and the item discriminations were collected for each group, and expert opinions on characteristics of response were collected through the expert council involving 8 science teachers with experience in NAEA. According to the results, there was no significant difference between students' achievement results in the PBT and the CBT-M, which means simple mode conversion type of CBT, so it could be explained that the mode effect did not appear. However, it was confirmed that the percentage of correct answers for the construct response items was somewhat high in the CBT, and this result was analyzed to be related to the convenience of the response. On the other hand, there were the items with a difference of more than 10%p from the correct answer rate of similar items, among the items to which technology enhanced functions were applied following the introduction of CBT. According to the analysis of response rate of options, these results could be explained that the students' level of understanding could be more closely grasped through the innovative items developed through the technology enhanced function. Based on the results, we discussed some guidance to be considered when introducing CBT and developing items through CBT, and presented implications.

• Journal of Preventive Medicine and Public Health
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• v.30 no.2 s.57
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• pp.437-461
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• 1997

Because of a significant improvement in the economic situation and development of scientific techniques in Korea during the last 30 years, the life expectancy of the Korean people has lengthened considerably and as a result, the number of the elderly has markedly increased. Such an increase of the number of aged population brought about many social, economic, and medical problems which were never seriously considered before. This study was conducted to assess the trend of medical care utilization and medical expenditure of the elderly. The data of each patient in the study were taken from computer database maintained for administrative purpose by the Korea Medical Insurance Corporation. The study population was 132,670 who were 60 years old or more and registered in Korean Medical Insurance Corporation from 1989 to 1993. The study subjects were predominantly female(56.3%) and 10,000-20,000 Won premium group(50.6%). The following are summaries of findings : The total increase of the number of inpatient cases was 40.5% from 1989 through 1993. The average annual increase was 3.7% in inpatient medical expenditures per case, 4.4% in inpatient medical expenditures per day and 0.08% in length of stay per case from 1989 through 1993. Cataract was the most prevalent disease of 10 leading frequent diseases in all ages from 1989 through 1993. The case mix in 1993 compared to 1989 revealed that cataract and ischemic cerebral disease were increased whereas essential hypertension and pulmonary tuberculosis were decreased . The average annual increase of medical expenditures was 3.8% in general hospitals, 6.3% in hospitals and 2.4% in clinics. From 1989 through 1993, medical expenditures used by high-cost patients accounted for about 14% to 20% of all expenditures for inpatient care, while they represented less than 2.5% of the elderly population. Time series analysis revealed that total medical expenditures and doctor's fee for inpatient will be progressively increased whereas drug expenditures for inpatient will be decreased. And there will be no change in length of stay. Based on the above results, the factors increasing medical cost and utilization should be identified and the method of cost containment for the elderly health care should be developed systematically.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.127-147
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• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.