• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.505-518
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• 2023

The key to invasive pest management lies in preemptive action. However, most current research using species distribution models is conducted after an invasion has occurred. This study modeled the potential distribution of the globally notorious sweet potato pest, the sweet potato weevil(Cylas formicarius), that has not yet invaded Korea using MaxEnt. Using global occurrence data, bioclimatic variables, and topsoil characteristics, MaxEnt showed high explanatory power as both the training and test areas under the curve exceeded 0.9. Among the environmental variables used in this study, minimum temperature in the coldest month (BIO06), precipitation in the driest month (BIO14), mean diurnal range (BIO02), and bulk density (BDOD) were identified as key variables. The predicted global distribution showed high values in most countries where the species is currently present, with a significant potential invasion risk in most South American countries where C. formicarius is not yet present. In Korea, Jeju Island and the southwestern coasts of Jeollanam-do showed very high probabilities. The impact of climate change under shared socioeconomic pathway (SSP) scenarios indicated an expansion along coasts as climate change progresses. By applying the 10th percentile minimum training presence rule, the potential area of occurrence was estimated at 1,439 km² under current climate conditions and could expand up to 9,485 km² under the SSP585 scenario. However, the model predicted that an inland invasion would not be serious. The results of this study suggest a need to focus on the risk of invasion in islands and coastal areas.

• Journal of Korean Elementary Science Education
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• v.43 no.3
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• pp.415-432
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• 2024

This study developed and applied the teacher education model and its principles for science classes using Virtual and Augmented Reality (VR/AR) content and analyzed preservice elementary teachers' feedback on the teacher education model and the changes in their perceptions as to the use of VR/AR content. First, existing Technological Pedagogical Content Knowledge (TPACK) teacher education models and prior studies on the use of the VR/AR contents were reviewed to derive the teacher education model to cultivate the VR/AR-TPACK and set the key principles for each of its stages. The developed teacher education model has five stages: exploration, mapping, collaborative design, practice, and reflection. Second, to examine the appropriateness of the model's five stages and principles, we applied it within the regular course of instruction at the university of education, which was attended by 25 preservice elementary teachers. This study collected data from surveys on the perception of the usage of VR/AR contents before and after the course, as well as the group lesson plans prepared by the preservice teachers, and their feedback on the teacher education model. The feedback on the teacher education model and the survey conducted by the preservice teachers before and after the course were analyzed through open coding and categorization. As a result, most preservice teachers expressed positive opinions about the activities and experiences at each stage of the implementation of the teacher education model. Perceptions related to the usage of the VR/AR content changed in three aspects: first, the vague positive perception of the VR/AR content has changed to a positive perception based on specific educational affordance. Second, they recognized the need for preparedness by anticipating potential problems associated with the use of the VR/AR content. Third, they came to view the VR/AR contents as a useful instructional resource that the teachers could use. Based on these results, we discussed the implications for the VR/AR-TPACK teacher education model and assessed the limitations of the research.

• Korean Journal of Heritage: History & Science
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• v.57 no.3
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• pp.24-35
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• 2024

Recently, research using deep learning technologies such as artificial intelligence, convolutional neural networks, etc. has been actively conducted in various fields including healthcare, manufacturing, autonomous driving, and security, and is having a significant influence on society. In line with this trend, the present study attempted to apply deep learning to the classification of archaeological artifacts, specifically ancient Korean roof-end tiles. Using 100 images of roof-end tiles from each of the Goguryeo, Baekje, and Silla dynasties, for a total of 300 base images, a dataset was formed and expanded to 1,200 images using data augmentation techniques. After building a model using transfer learning from the pre-trained EfficientNetB0 model and conducting five-fold cross-validation, an average training accuracy of 98.06% and validation accuracy of 97.08% were achieved. Furthermore, when model performance was evaluated with a test dataset of 240 images, it could classify the roof-end tile images from the three dynasties with a minimum accuracy of 91%. In particular, with a learning rate of 0.0001, the model exhibited the highest performance, with accuracy of 92.92%, precision of 92.96%, recall of 92.92%, and F1 score of 92.93%. This optimal result was obtained by preventing overfitting and underfitting issues using various learning rate settings and finding the optimal hyperparameters. The study's findings confirm the potential for applying deep learning technologies to the classification of Korean archaeological materials, which is significant. Additionally, it was confirmed that the existing ImageNet dataset and parameters could be positively applied to the analysis of archaeological data. This approach could lead to the creation of various models for future archaeological database accumulation, the use of artifacts in museums, and classification and organization of artifacts.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.481-491
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• 2024

Recent droughts make hydroelectric power generation (HPG) decreasing. Due to climate change in the future, the frequency and intensity of drought are expected to increase, which will increase uncertainty of HPG in multi-purpose dams. Therefore, it is necessary to estimate the amount of HPG according to climate change scenarios and analyze the effect of drought on the amount of HPG. This study analyzed the future HPG of the Soyanggang Dam and Chungju Dam according to the SSP2-4.5 and SSP5-8.5 scenarios. Regression equations for HPG were developed based on the observed data of power generation discharge and HPG in the past provided by My Water, and future HPGs were estimated according to the SSP scenarios. The effect of drought on the amount of HPG was investigated based on the drought severity calculated using the standardized precipitation index (SPI). In this study, the future SPIs were calculated using precipitation data based on four GCM models (CanESM5, ACCESS-ESM1-5, INM-CM4-8, IPSL-CM6A) provided through the environmental big data platform. Overall results show that climate change had significant effects on the amount of HPG. In the case of Soyanggang Dam, the amount of HPG decreased in the SSP2-4.5 and SSP5-8.5 scenarios. Under the SSP2-4.5 scenario the CanESM model showed a 65% reduction in 2031, and under the SSP5-8.5 scenario the ACCESS-ESM1-5 model showed a 54% reduction in 2029. In the case of Chungju Dam, under the SSP2-4.5 and SSP5-8.5 scenarios the average monthly HPG compared to the reference period showed a decreasing trend except for INM-CM4 model.

• Journal of the Korean Chemical Society
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• v.68 no.5
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• pp.259-273
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• 2024

This study aimed to investigate changes in metamodeling recognition among chemistry teachers through a teacher educational program related to redox models and water electrolysis experiments. To this end, a science model education program was developed for 9 chemistry teachers and conducted over 10 lessons for a total of 40 hours. In addition, a pre- and post-survey was administered to determine teachers' metamodeling recognition in non-contextual and contextual situations. As a result of the study, through the science model education program, teachers showed educational effects in both non-contextual and contextual situations. In the case of non-contextual situations, the stages of scientific metamodeling knowledge development of chemistry teachers came out differently depending on the type of question. For example, the nature or purpose of the model, the modeling process, or the evaluation and improvement of the model improved from low to high, but there was no significant change because the perception of model change and diversity was already high in advance. In the case of contextual situations, the stage of scientific metamodeling knowledge development improved from objectivity to subjectivity in both the redox model theory class and the water electrolysis model experiment class. Therefore, through the 5E circular learning model-based education program, chemistry teachers' perception of metamodeling was clearly improved. However, the modeling activities of teachers in the water electrolysis model experiment class were different from the change in metamodeling perception. The types that teachers selected as additional experiments for modeling were analyzed in two ways. The first type is when they are interested in finding an ideal condition in which the ratio of hydrogen and oxygen gas is close to 2:1 through additional experiments. The second type is when additional experiments are designed with interest in why the experimental results are coming out like that. It was analyzed that the second type was the experiment necessary for modeling. In addition, modeling activities were analyzed into two types. The first was a type in which water molecules were directly decomposed in two electrodes to generate hydrogen and oxygen gas. This type was the case of regression to the textbook model regardless of the experimental results, and 6 chemistry teachers out of 8 were analyzed as this type. The second type was the type in which water reacted at the (+) electrode to generate other substances, and hydrogen ions reacted at the (-) electrode to generate hydrogen gas. Teachers who performed these modeling activities corresponded to the second type in additional experiments, and 2 chemistry teachers out of 8 corresponded to this. Therefore, it is necessary to provide an experience of activities corresponding to the second type of experiment and modeling through an educational program that provides an experience of directly modeling through experiments in order to develop modeling capabilities, unlike the development of metamodeling knowledge.

• Journal of Korea Port Economic Association
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• v.40 no.2
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• pp.65-78
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• 2024

This study investigates the correlation between financial constraints and investment activities in Korean logistics firms. A sample of 340 companies engaged in the transportation sector, as per the 2021 KSIC, was selected for analysis. Financial data obtained from the DART were used to compile a panel dataset spanning from 1996 to 2021, totaling 6,155 observations. The research model was validated, and tests for heteroscedasticity and autocorrelation in the error terms were conducted considering the panel data structure. The relationship between investment activities in the previous period and current investment activities was analyzed using panel Generalized Method of Moments(GMM). The validation results of the research indicate that Korean logistics firms tend to increase investment activities as their level of financial constraints improves. Specifically, a positive relationship between the level of financial constraints and investment activities was consistently observed across all models. These findings suggest that investment decision-making varies based on the financial constraints faced by companies, aligning with previous research indicating that investment activities of constrained firms are subdued. Moreover, while the results from the model examining whether investment activities in the previous period affect current investment activities indicated an influence of investment activities from the previous period on current investment activities, the investment activities from two periods ago did not show a significant relationship with current investment activities. Among the control variables, firm size and cash flow variables exhibited positive relationships, while debt size and asset diversification variables showed negative relationships. Thus, larger firm size and smoother cash flows were associated with more proactive investment activities, while high debt levels and extensive asset diversification appeared to constrain investment activities in logistics companies. These results interpret that under financial constraints, internal funding sources such as cash flows exhibit positive relationships, whereas external capital sources such as debt demonstrate negative relationships, consistent with empirical findings from previous research.

• Journal of the Korea Organic Resources Recycling Association
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• v.17 no.1
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• pp.58-72
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• 2009

In this study, the organic matter and biomass was characterized by using respirometry based on ASM No.2d (Activated Sludge Model No.2d). The activated sludge models are based on the ASM No.2d model, published by the IAWQ(International Association on Water Quality) task group on mathematical modeling for design and operation of biological wastewater treatment processes. For this study, OUR(Oxygen Uptake Rate) measurements were made on filtered as well as non-filtered wastewater. Also, GC-FID and LC analysis were applied for the estimation of VFAs(Volatile Fatty Acids) COD(S_A) in slowly bio-degradable soluble substrates of the ASM No.2d. Therefore, this study was intended to clearly identify slowly bio-degradable dissolved materials(S_S) and particulate materials(X_I). In addition, a method capable of determining the accurate time to measure non-biodegradable COD(S_I), by the change of transition graphs in the process of measuring microbial OUR, was presented in this study. Influent fractionation is a critical step in the model calibrations. From the results of respirometry on filtered wastewater, the fraction of fermentable and readily biodegradable organic matter(S_F), fermentation products(S_A), inert soluble matter(S_I), slowly biodegradable matter(X_S) and inert particular matter(X_I) was 33.2%, 14.1%, 6.9%, 34.7%, 5.8%, respectively. The active heterotrophic biomass fraction(X_H) was about 5.3%.

• Journal of Life Science
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• v.34 no.9
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• pp.609-619
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• 2024

Neurodegenerative diseases are marked by the accumulation of toxic misfolded proteins in neurons. Therefore, strategies for the effective prevention and clearance of aggregates are crucial for therapeutic interventions. Cytoplasmic dynein plays a crucial role in the clearance of aggregates by transporting them to the cell center, where lysosomes are enriched and the aggregates undergo extensive autophagic degradation. Previously, we reported evidence for the activation of dynein by N-acetylglucosamine kinase (NAGK) and Reln. In the present study, we explored the effects of NAGK and Reln upregulation on the clearance of aggregates. To upregulate NAGK and Reln genes in HEK293T cells (a human embryonic kidney cell line), CRISPR/dCas9 activation systems (CASs) were used with specific plasmids encoding target-specific 20 nt guide RNA. The effects of this genetic modulation were analyzed in Huntington's disease cellular models, including HEK293T cells and primary mouse cortical cells, where external mutant huntingtin (mHtt, Q74) aggregates were induced. The results showed that the CAS activation of NAGK or Reln, or their combination, significantly reduced the proportion of cells with Q74 aggregates (aggresomes). This effect was reversed by Ciliobrevin D (a dynein inhibitor) and chloroquine (an autophagy inhibitor), indicating the role of dynein-mediated autophagy in aggregate clearance. These findings provide the basis for therapeutic strategies aimed at enhancing neuronal health through targeted gene activation.

• Journal of Environmental Impact Assessment
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• v.33 no.4
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• pp.143-154
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• 2024

Heat waves caused by climate change are rapidly increasing health damage to vulnerable groups, and to prevent this, the national, regional, and local governments are establishing climate crisis adaptation policy. A representative climate crisis adaptation policy to reduce heat wave damage is to expand the number of cooling centers. Because it is highly effective in a short period of time, most metropolitan local governments, except Jeonbuk, include the project as an adaptation policy. However, the criteria for selecting a cooling centers are different depending on the budget and non-budget, so the utilization rate and effectiveness of the cooling centers are all different. Therefore, in this study, we developed logistic regression models that can predict and evaluate areas with a high probability of expanding cooling centers in order to implement adaptation policy in local governments. In Incheon Metropolitan City, which consists of various heat wave-vulnerable environments due to the coexistence of the old city and the new city, a logistic model was developed to predict areas where heat waves can be cooling centered by dividing it into Ganghwa·Ongjin-gun and other regions, taking into account socioeconomic and environmental differences. As a result of the study, the statistical model for the Ganghwa·Ogjin-gun region showed that the higher the ground surface temperature and the more and more the number of elderly people over 65 years old, the higher the possibility of location of cooling centers, and the prediction accuracy was about 80.93%. The developed logistic regression model can predict and evaluate areas with a high potential as cooling centers by considering regional environmental and social characteristics, and is expected to be used for priority selection and management when designating additional cooling centers in the future.

• Economic and Environmental Geology
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• v.57 no.4
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• pp.397-416
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• 2024

This study assessed the hydrogeological properties of the deep geological environment to develop safety criteria for the natural barriers used in the deep geological disposal of high-level radioactive waste in Korea. The assessment focused on the distribution and trends of hydraulic conductivity and permeability properties appropriate for the domestic geological environment, using various in-situ hydraulic test data collected for groundwater development and management. To develop a depth-hydrogeological property relationship model suitable for domestic conditions, the study reviewed various international research examples and applied a representative model that explains the trends of hydraulic conductivity and permeability with depth. The development of the model suitable for Korea involved applying ensemble regression analysis to account for the uncertainty of various factors in the collected data. The results confirmed that existing international depth-hydrogeological property relationship models adequately describe the characteristics of the domestic geological environment. Considering the preferred hydrogeological criteria suggested by countries like Sweden, Germany, and Canada, there is a high likelihood that a suitable geological environment exists in Korea. Additionally, the application of hydrogeological criteria indicative of low-permeability environments showed that suitable conditions for disposal construction increase at depths greater than 300 m, where the influence of fractures on groundwater flow might be minimal at depths exceeding 500 m. This research can serve as foundational information for establishing hydrogeological safety standards for natural barriers in Korea according to international regulatory guidelines.