• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.461-470
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• 2020

This study analyzed the determinants of land compensation costs using the CALS (Continuous Acquisition & Life-Cycle Support) system to generate data for the construction (planning, design, building, management) process. For analysis, variables used in the related research on land costs were used, which included eight variables (Land Area, Individual Public Land Price, Appraisal & Assessment, Land Category, Use District 1, Terrain Elevation, Terrain Shape, and Road). Also, the variables were analyzed using the machine learning-based Xgboost algorithm. Individual Public Land Price was identified as the most important variable in determining land cost. We used a linear multiple regression analysis to verify the determinants of land compensation. For this verification, the dependent variable included was the Individual Public Land Price, and the independent variables were the numeric variable (Land Area) and factor variables (Land Category, Use District 1, Terrain Elevation, Terrain Shape, Road). This study found that the significant variables were Land Category, Use District 1, and Road.

• Journal of Wetlands Research
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• v.22 no.2
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• pp.106-112
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• 2020

Wetlands play an important function and role in hydrological, environmental, and ecological, aspects of the watershed. Water level in wetlands is essential for various analysis such as for the determination of wetland function and its effects on the environment. Since several wetlands are ungauged, research on wetland water level prediction are uncommon. Therefore, this study developed a water level prediction model using multiple regression analysis, principal component regression analysis, artificial neural network, and DNN to predict wetland water level. Geumjeong-Mountain Wetland located in Yangsan-city, Gyeongsangnam-do province was selected as the target area, and the water level measurement data from April 2017 to July 2018 was used as the dependent variable. On the other hand, hydrological and meteorological data were used as independent variables in the study. As a result of evaluating the predictive power, the water level prediction model using DNN was selected as the final model as it showed an RMSE value of 6.359 and an NRMSE value of 18.91%. This research study is believed to be useful especially as a basic data for the development of wetland maintenance and management techniques using the water level of the existing unmeasured points.

• Journal of The Korean Association For Science Education
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• v.21 no.4
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• pp.677-688
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• 2001

The purposes of this study are to investigate the school science high achievers' achievements in enrichment physics, logical thinking level, and to analyze the relationship between logical thinking level and the achievement in enrichment physics of high achievers in science. The subjects were 357th and 8th graders who achieved highly in school science. To assess their achievements in enrichment physics, we developed a new test consisting of descriptive problems which were based on middle school curriculum. Those problems require one or two steps of thinking process, not simple knowledge of science. To assess logical thinking level, we used the instrument called GALT(Group Assessment of Logical Thinking) developed by Roadranka et al. The results showed that the school science high achievers' average achievement in enrichment physics was low, 56.3 out of 150, which indicated that they had not done much of enrichment learning beyond middle school science curriculum. Just only 54% of the school science high achievers are in formal logical thinking level. From the analysis of relationship between their logical thinking level and the achievement in enrichment physics, the value of the correlation coefficient was 0.174, which means that they are not almost correlated. Therefore, it is not desirable to judge science gifted children just from achievement in school science or enrichment physics, so both(logical thinking and the achievement in enrichment physics) tests should be taken for selecting gifted student.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1881-1890
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• 2021

Particulate matter (PM) affects the human, ecosystems, and weather. Motorized vehicles and combustion generate fine particulate matter (PM_2.5), which can contain toxic substances and, therefore, requires systematic management. Consequently, it is important to monitor and predict PM_2.5 concentrations, especially in large cities with dense populations and infrastructures. This study aimed to predict PM_2.5 concentrations in large cities using meteorological and chemical variables as well as satellite-based aerosol optical depth. For PM_2.5 concentrations prediction, a random forest (RF) model showing excellent performance in PM concentrations prediction among machine learning models was selected. Based on the performance indicators R², RMSE, MAE, and MAPE with training accuracies of 0.97, 3.09, 2.18, and 13.31 and testing accuracies of 0.82, 6.03, 4.36, and 25.79 for R², RMSE, MAE, and MAPE, respectively. The variables used in this study showed high correlation to PM_2.5 concentrations. Therefore, we conclude that these variables can be used in a random forest model to generate reliable PM_2.5 concentrations predictions, which can then be used to assess the vulnerability of schools to PM_2.5.

• Journal of The Korean Association For Science Education
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• v.41 no.2
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• pp.155-169
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• 2021

This study aims at exploring the features of science teaching orientation (STO) and its relationships with other PCK (pedagogical content knowledge) components. To do this, based on the definition of STO by Friedrichsen, Driel, & Abell(2011) and PCK model by Magnusson, Krajcik, & Borko(1999), we observed one experienced elementary teacher's science lessons for 21 lesson hours (10 hours of 'Motion of Objects' and 11 hours of 'Light and Lens') and carried out qualitative analyses of the data obtained from lessons observation, teacher interviews, and CoRe (content representation) responses. We analyzed the teacher's three aspects of STO (i.e. beliefs about the goals and purpose of science teaching, beliefs about the nature of science, and beliefs about science teaching and learning) which can converge into an overall STO of 'inquiry'. And these aspects of STO appear to interact differently with four PCK components (i.e. curriculum knowledge, learner knowledge, instructional knowledge, and assessment knowledge) depending on the topic of the lesson. It is hoped that this in-depth understanding of the features of STO and its relationship with other PCK components would provide useful information on how to monitor and improve STO and PCK of elementary teachers.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.457-468
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• 2022

In aged society, it is important to prevent older people from being disability needing long-term care. The purpose of this study is to develop a prediction model to discover high-risk groups who are likely to be beneficiaries of Long-Term Care Insurance. This study is a retrospective study using database of National Health Insurance Service (NHIS) collected in the past of the study subjects. The study subjects are 7,724,101, the population over 65 years of age registered for medical insurance. To develop the prediction model, we used logistic regression, decision tree, random forest, and multi-layer perceptron neural network. Finally, random forest was selected as the prediction model based on the performances of models obtained through internal and external validation. Random forest could predict about 90% of the older people in need of long-term care using DB without any information from the assessment of eligibility for long-term care. The findings might be useful in evidencebased health management for prevention services and can contribute to preemptively discovering those who need preventive services in older people.

• Journal of Dental Anesthesia and Pain Medicine
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• v.23 no.2
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• pp.101-110
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• 2023

Background: Dentists make various efforts to reduce patients' anxiety and fear associated with dental treatment. Dental sedation is an advanced method that dentists can perform to reduce patients' anxiety and fear and provide effective dental treatment. However, dental sedation is different from general dental treatment and requires separate learning, and if done incorrectly, can lead to serious complications. Therefore, sedation is performed by a limited number of dentists who have received specific training. This study aimed to investigate the proportion of dentists who practice sedation and the main sedatives they use in the context of the Republic of Korea. Methods: We used the customized health information data provided by the Korean National Health Insurance. We investigated the number of dental hospitals or clinics that claimed insurance for eight main sedatives commonly used in dental sedation from January, 2007 to September, 2019 at the Health Insurance Review and Assessment Service. We also identified the changes in the number of dental medical institutions by region and year and analyzed the number and proportion of dental medical institutions prescribing each sedative. Results: In 2007, 302 dental hospitals prescribed sedatives, and the number increased to 613 in 2019. In 2007, approximately 2.18% of the total 13,796 dental institutions prescribed sedatives, increasing to 3.31% in 2019. In 2007, 168 institutions (55.6%) prescribed N₂O alone, and in 2019, 510 institutions (83.1%) made claims for it. In 2007, 76 (25.1%) hospitals made claims for chloral hydrate, but the number gradually decreased, with only 29 hospitals (4.7%) prescribing it in 2019. Hospitals that prescribed a combination of N₂O, chloral hydrate, and hydroxyzine increased from 27 (8.9%) in 2007 to 51 (9%) in 2017 but decreased to 38 (6.1%) in 2019. The use of a combination of N₂O and midazolam increased from 20 hospitals (6.6%) in 2007 to 51 hospitals (8.3%) in 2019. Conclusion: While there is a critical limitation to the investigation of dental hospitals performing sedation using insurance claims data, namely exclusion of dental clinics providing non-insured treatments, we found that in 2019, approximately 3.31% of the dental clinics were practicing sedation and that N₂O was the most commonly prescribed sedative.

• Economic and Environmental Geology
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• v.57 no.1
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• pp.51-71
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• 2024

Seismic exploration is one of the widely used geophysical exploration methods with various applications such as resource development, geotechnical investigation, and subsurface monitoring. It is essential for interpreting the geological characteristics of subsurface by providing accurate images of stratum structures. Typically, geological features are interpreted by visually analyzing seismic sections. However, recently, quantitative analysis of seismic data has been extensively researched to accurately extract and interpret target geological features. Seismic attribute analysis can provide quantitative information for geological interpretation based on seismic data. Therefore, it is widely used in various fields, including the analysis of oil and gas reservoirs, investigation of fault and fracture, and assessment of shallow gas distributions. However, seismic attribute analysis is sensitive to noise within the seismic data, thus additional noise attenuation is required to enhance the accuracy of the seismic attribute analysis. In this study, four kinds of seismic noise attenuation methods are applied and compared to mitigate random noise of poststack seismic data and enhance the attribute analysis results. FX deconvolution, DSMF, Noise2Noise, and DnCNN are applied to the Youngil Bay high-resolution seismic data to remove seismic random noise. Energy, sweetness, and similarity attributes are calculated from noise-removed seismic data. Subsequently, the characteristics of each noise attenuation method, noise removal results, and seismic attribute analysis results are qualitatively and quantitatively analyzed. Based on the advantages and disadvantages of each noise attenuation method and the characteristics of each seismic attribute analysis, we propose a suitable noise attenuation method to improve the result of seismic attribute analysis.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.2
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• pp.101-115
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• 2024

The ocean heatwave is emerging as a major issue due to global warming, posing a direct threat to marine ecosystems and humanity through decreased food resources and reduced carbon absorption capacity of the oceans. Consequently, the prediction of ocean heatwaves in the vicinity of the Korean Peninsula is becoming increasingly important for marine environmental monitoring and management. In this study, an LSTM model was developed to improve the underestimated prediction of ocean heatwaves caused by the coarse vertical grid system of the Korean Peninsula Ocean Prediction System. Based on the results of ocean heatwave predictions for the Korean Peninsula conducted in 2023, as well as those generated by the LSTM model, the performance of heatwave predictions in the East Sea, Yellow Sea, and South Sea areas surrounding the Korean Peninsula was evaluated. The LSTM model developed in this study significantly improved the prediction performance of sea surface temperatures during periods of temperature increase in all three regions. However, its effectiveness in improving prediction performance during periods of temperature decrease or before temperature rise initiation was limited. This demonstrates the potential of the LSTM model to address the underestimated prediction of ocean heatwaves caused by the coarse vertical grid system during periods of enhanced stratification. It is anticipated that the utility of data-driven artificial intelligence models will expand in the future to improve the prediction performance of dynamical models or even replace them.

• 대한공업교육학회지
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• v.39 no.2
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• pp.101-121
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• 2014

The study aims to develop the NCS based vocational curriculum model for the practical and creative human resources. For effectiveness of the study, the study consists of literature studies of both domestic and international, contents analysis, case study, expert(9samples) consultation and review, and in-depth-interview of the three advisory members. The validity of the developed model is analyzed through mean, standard deviation and contents validity ratio(CVR). The main results of the model development in our study are as follow. First, our NCS based vocational curriculum model for the practical and creative human resources is developed with the analyses of NCS development manuals, training standard utilization and training curriculum organization manuals, NCS learning module development manual and case studies, NCS research report, NCS based curriculum pilot development resources directed toward the high schools and vocational school as well as the domestic and international literature study on career training model like NCS. Second, based on the findings of our analysis in combination with the findings from the consultations with the expert and advisory committee, total 19 sub-factors of each step and domain are extracted. The sub-factors of domain in step 1 are the competency unit, definition of competency unit, competency unit element, performance criteria, range of variable, guide of assessment, key competency; in step 2, they are subject title, subject objectives, chapter title, chapter objectives, pedagogical methods, assessment methods and basic job competence; and in step 2, they are NCS based subject matrix table, NCS based subject profile, NCS based job training curriculum table, NCS based subjects organization flowchart, NCS based job training operation plan. Third, the final model including step 3 NCS based subject profile are developed in association with the linked organizational sub-factors of step 1 and step 2. Forth, the validity tests for the final model by the step and domain yield the mean 4.67, CVR value 1.00, indicating the superior validity. Also, the means of each sub-factors are all over 4.33 with the CVR value 1.00, indicating the high validity as well. The means of the associated organizations within the model are also over 4.33 with the CVR value of 1.00. Standard deviations are all .50 or lower which are small. Fifth, based on the validity test results and the in-depth-interview of the expert and advisory committee, the model is adjusted complemented to establish final model of the NCS based vocational curriculum for the practical and creative human resources.