• Journal of Korea Water Resources Association
• /
• v.55 no.8
• /
• pp.589-601
• /
• 2022

Although drought is a natural phenomenon, its damage occurs in combination with regional physical and social factors. Especially, related to the supply and demand of various waters, drought causes great socio-economic damage. Even meteorological droughts occur with similar severity, its impact varies depending on the regional characteristics and water supply system. Therefore, this study assessed regional drought risk considering regional socio-economic factors and water supply system. Drought hazard was assessed by grading the joint drought management index (JDMI) which represents water shortage. Drought vulnerability was assessed by weighted averaging 10 socio-economic factors using Entropy, Principal Component Analysis (PCA), and Gaussian Mixture Model (GMM). Drought response capacity that represents regional water supply factors was assessed by employing Bayesian networks. Drought risk was determined by multiplying a cubic root of the hazard, vulnerability, and response capacity. For the drought hazard meaning the possibility of failure to supply water, Goesan-gun was the highest at 0.81. For the drought vulnerability, Daejeon was most vulnerable at 0.61. Considering the regional water supply system, Sejong had the lowest drought response capacity. Finally, the drought risk was the highest in Cheongju-si. This study identified the regional drought risk and vulnerable causes of drought, which is useful in preparing drought mitigation policy considering the regional characteristics in the future.

• Journal of The Korean Association For Science Education
• /
• v.42 no.2
• /
• pp.265-275
• /
• 2022

In this study, focusing on science education in the future society, we explored students' key competencies to be cultivated for the future society, and the role and PCK expertise necessary for science teachers, who are the main agents of competency-based education to nurture these key competencies. A survey conducted among earth science teachers across the country results in 105 valid responses being obtained. The research results are discussed in terms of students' key competencies to be nurtured for the future society, the role and the expertise of science teachers required for competency-based education, and the structural relationship between the teacher role and teacher expertise. We also conducted network analysis to examine the relationship between student competency and teacher expertise, and the structure between the teacher's role and expertise. Main results include that communication and collaboration skills are the most important for students in the future society as core competencies. For science teachers, providing opportunities for collaboration-oriented activities are deemed as the most important. Regarding the structural relationship between the teacher's role and the teacher's expertise, there is a clear relationship with roles such as providing opportunities for collaboration-oriented activities and utilizing various materials and contents in relation to the expertise related to the science teaching practice. Based on the results, ways to promote student's agency based on raising teachers' awareness of the student's competencies, the inter-relatedness of the teacher's role and the teacher's expertise, and the totality of teachers' expertise were suggested.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.25 no.2
• /
• pp.59-71
• /
• 2022

This study considered regional differences in the university-industry collaboration of Korean universities and performed cluster analysis to identify the spatial range with high university-industry collaboration connectivity. By university establishment type, it was found that the university-industry collaboration capacity of the major national university was superior overall, especially in the technology transfer & commercialization sector and the infrastructure sector, compared to private universities and general national universities. The spatial pattern of university-industry collaboration capacity showed relatively clear differences by city and province. In terms of university-industry collaboration capacity by sector, it was confirmed that the regional gap was not large in the talent training sector and the infrastructure sector, but the regional gap was relatively large in the technology transfer & commercialization sector and the start-up sector. As a result of the cluster analysis to identify a spatial range with high connectivity in terms of similarity and spatial proximity of university-industry collaboration patterns, it is divided into 15 clusters. It is found that most of major national universities are included in one of 15 clusters where all sectors of university-industry collaboration are strong. Therefore, as a policy measure to achieve regional innovative growth through enhancing the effectiveness of university-industry collaboration, we propose the establishment of a hub & spoke network-type collaboration system in which a major national university acts as a hub and nearby local universities play a spoke role.

• Journal of Korea Water Resources Association
• /
• v.55 no.5
• /
• pp.345-356
• /
• 2022

A severe flooding occured at a small urban catchment in Daejeon-si South Korea on July 30, 2020 causing significant loss of property (inundated 78 vehicles and two apartments) and life (one casualty and 56 victims). In this study, a retrospective analysis of the inundation event was implemented using a physically-based urban flood model, H12 with high-resolution data. H12 is an integrated 1-dimensional sewer network and 2-dimensional surface flow model supported by hybrid parallel techniques to efficiently deal with high-resolution data. In addition, we evaluated the impact of the flooding barriers which were installed after the flood disaster. As a result, it was found that the inundation was affected by a combination of multiple components including the shape of the basin, the low terrain of the inundation area located in the downstream part of the basin, and lack of pipe capacity to drain discharge from the upstream during heavy rain. The impact of the flooding barriers was analyzed by modeling with and without barriers on the high-resolution terrain input data. It was evaluated that the flood barriers effectively lower the water depth in the apartment complex. This study demonstrates capability of high-resolution physically-based urban modeling to quantitatively assess the past inundation event and the impact of the reduction measures.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.42 no.1
• /
• pp.11-21
• /
• 2022

Drought occurs extensively over a long period and causes great socio-economic damage. Since drought risk consists of social, environmental, physical, and economic factors along with meteorological and hydrological factors, it is important to quantitatively identify their impacts on drought risk. This study investigated the relationship among drought hazard, vulnerability, response capacity, and risk in Chungcheongbuk-do using a structural equation model and evaluated their impacts on drought risk using Bayesian networks. We also performed sensitivity analysis to investigate how the factors change drought risk. Overall results showed that Chungju-si had the highest risk of drought. The risk was calculated as the largest even when the hazard and response capacity were changed. However, when the vulnerability was changed, Eumseong-gun had the greatest risk. The sensitivity analysis showed that Jeungpyeong-gun had the highest sensitivity, and Jecheon-si, Eumseong-gun, and Okcheon-gun had highest individual sensitivities with hazard, vulnerability, and response capacity, respectively. This study concluded that it is possible to identify impact factors on drought risk using regional characteristics, and to prepare appropriate drought countermeasures considering regional drought risk.

• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1167-1181
• /
• 2021

In relation to the algae bloom, four types of blue-green algae that emit toxic substances are designated and managed as harmful Cyanobacteria, and prediction information using a physical model is being also published. However, as algae are living organisms, it is difficult to predict according to physical dynamics, and not easy to consider the effects of numerous factors such as weather, hydraulic, hydrology, and water quality. Therefore, a lot of researches on algal bloom prediction using machine learning have been recently conducted. In this study, the characteristic importance of water quality factors affecting the occurrence of Cyanobacteria harmful algal blooms (CyanoHABs) were analyzed using the random forest (RF) model for Bohyeonsan Dam and Yeongcheon Dam located in Yeongcheon-si, Gyeongsangbuk-do and also predicted the occurrence of harmful blue-green algae using the machine learning and deep learning models and evaluated their accuracy. The water temperature and total nitrogen (T-N) were found to be high in common, and the occurrence prediction of CyanoHABs using artificial neural network (ANN) also predicted the actual values closely, confirming that it can be used for the reservoirs that require the prediction of harmful cyanobacteria for algal management in the future.

• Journal of Digital Convergence
• /
• v.20 no.5
• /
• pp.627-635
• /
• 2022

As the non-face-to-face situation continues for a long time due to COVID-19, the underlying technologies of the 4th industrial revolution such as IOT, AR, VR, and big data are affecting the metaverse platform overall. Such changes in the external environment such as society and culture can affect the development of academics, and it is very important to systematically organize existing achievements in preparation for changes. The Korea Educational Research Information Service (RISS) collected data including the 'metaverse platform' in the keyword and used the text mining technique, one of the big data analysis. The collected data were analyzed for word cloud frequency, connection strength between keywords, and semantic network analysis to examine the trends of metaverse platform research. As a result of the study, keywords appeared in the order of 'use', 'digital', 'technology', and 'education' in word cloud analysis. As a result of analyzing the connection strength (N-gram) between keywords, 'Edue→Tech' showed the highest connection strength and a total of three clusters of word chain clusters were derived. Detailed research areas were classified into five areas, including 'digital technology'. Considering the analysis results comprehensively, It seems necessary to discover and discuss more active research topics from the long-term perspective of developing a metaverse platform.

• Journal of Industrial Convergence
• /
• v.20 no.2
• /
• pp.1-9
• /
• 2022

As the need for improvement of transparency and fairness in the selection of national R&D projects has been continuously raised, we analyzed the impact on the evaluation selection results by evaluation indexes for The land transportation technology commercialization support project and searched for ways to improve indexes using the analysis results. As for the research data, it were applied as selection results of new R&D projects and evaluation indexes in two fields(SME innovation and start-up) in 2021. Logistic regression analysis is used for the influence of each evaluation indexes on the evaluation result, and for the regression model, evaluation indexes with low influence are removed in advance through artificial neural network multiple perceptron analysis to improve the reliability of the analysis results. As a result of the analysis, in the field of SME innovation, the influence of the evaluation index on the workforce planning was the lowest and the influence of the appropriateness of commercialization promotion plan was the highest. In the start-up field, the influence of the evaluation indexes for technology development suitability, marketability, and suitability for carrying out the project were estimated to be similar to each other, and the influence of the technology evaluation index was found to be the lowest. The analysis results of this thesis suggest the need for continuous improvement of selection and evaluation indexes, and by using the analysis results to select a fair R&D institution according to the selection of appropriate indexes, it will be possible to contribute to deriving excellent research results and fostering excellent companies in the field of land transportation.

• The Journal of the Korea Contents Association
• /
• v.22 no.2
• /
• pp.224-236
• /
• 2022

This study tests the hypotheses that city slogan reduces the retrieval of city memory unrelated to the slogan from the long term memory and that some variables moderate this effect, using the experimental method. The theoretical basis for the hypotheses is from the structure of the long term memory and the principle of memory retrieval discussed in ANM(Associative Network Model). For the test of hypotheses, the study adopted 4 experimental groups (2(slogan relevance: high or low) * 2(slogan concreteness: high or low)) and 1 control group. Each experimental group was exposed to one slogan corresponding to its condition while the control group was not. Then, the recall score was compared among experimental and control groups. One hundred and seventy-four undergraduate students belonging to the college of the authors participated in the study. The sample group was between 18 and 27 years of age, with an average of 22.4 years, and 54 percent comprised males. Results showed that city slogan had a negative effect on the retrieval of city memory unrelated to the slogan in most experimental conditions. This effect was more evident when the slogan had high relevance or high concreteness. But the main effect did not appear when the slogan had low relevance and low concreteness.

• Geophysics and Geophysical Exploration
• /
• v.25 no.1
• /
• pp.26-37
• /
• 2022

Recently, multiple methods using small aircraft for geophysical exploration have been suggested as a result of the development of information and communication technology. In this study, we introduce the hybrid unmanned aircraft electromagnetic system of the Korea Institute of Geosciences and Mineral resources, which is under development. Additionally, data processing and interpretation methods are suggested via the analysis of datasets obtained using the system under development to verify the system. Because the system uses a three-component receiver hanging from a drone, the effects of rotation on the obtained data are significant and were therefore corrected using a rotation matrix. During the survey, the heights of the source and the receiver and their offsets vary in real time and the measured data are contaminated with noise. The noise makes it difficult to interpret the data using the conventional method. Therefore, we developed a recurrent neural network (RNN) model to enable rapid predictions of the apparent resistivity using magnetic field data. Field data noise is included in the training datasets of the RNN model to improve its performance on noise-contaminated field data. Compared with the results of the electrical resistivity survey, the trained RNN model predicted similar apparent resistivities for the test field dataset.