• Journal of The Korean Association For Science Education
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• v.43 no.6
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• pp.495-507
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• 2023

Teachers often encounter challenges in supporting students with question generation and the development of investigation plans in sensemaking activities. A primary challenge stems from the ambiguity surrounding how students apply their conceptual understandings in this process. This study aims to explore how students apply their conceptual understandings to generate questions and design investigation processes in a sensemaking activity. Two types of student group activities were identified and examined for comparison: One focused on designing a process to achieve the goal of sensemaking, and the other focused on following the step-by-step scientific inquiry procedures. The design of investigation process in each group was concretized with epistemic criteria used for evaluating the designs. The students' use of conceptual understandings in discussions around each was then examined. The findings reveal three epistemic criteria employed in generating questions and designing investigation processes. First, the students examined the interestingness of natural phenomena, using their conceptual understandings of the structure and function of entities within natural phenomena to identify a target phenomenon. This process involved verifying their existing knowledge to determine the need for new understanding. The second criterion was the feasibility of investigating specific variables with the given resources. Here, the students relied on their conceptual understandings of the structure and function of entities corresponding to each variable to assess whether each variable could be investigated. The third epistemic criterion involved examining whether the factors of target phenomena expressed in everyday terms could be translated into observable variables capable of explaining the phenomena. Conceptual understandings related to the function of entities were used to translate everyday expressions into observable variables and vice versa. The students' conceptual understanding of a comprehensive mechanism was used to connect the elements of the phenomenon and use the elements as potential factors to explain the target phenomenon. In the case where the students focused on carrying out step-by-step procedures, data collection feasibility was the sole epistemic criterion guiding the design. This study contributes to elucidating how the process of a sensemaking activity can be developed in the science classroom and developing conceptual supports for designing sensemaking activities that align with students' perspectives.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.563-576
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• 2023

In this study nitrogen dioxide (NO₂), formaldehyde (HCHO) from the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI), OMI/ Microwave Limb Sounder (MLS) tropospheric column ozone (TCO), and Airkorea ground-based O₃ data were analyzed to examine the photochemical reaction relationship between tropospheric ozone and its precursors nitrogen oxides (NOx) and volatile organic compounds (VOCs). As a result of analyzing the trend of long-term changes from 2006 to 2020 using OMI satellite data, TCO showed an increasing trend, NO₂ steadily decreased, and HCHO continued to increase in Northeast Asia. In addition, formaldehyde nitrogen dioxide ratio (FNR; HCHO/NO₂ ratio), an indicator of ozone sensitivity, is gradually increasing, which means that the VOC-limited regime is decreasing. This study conducted a sensitivity analysis of ozone generation using TROPOMI FNR and ground-based ozone (O₃) over the recent years (2019~2022) to identify the possible cause for the continuous increase of ozone in Korea. Similar to the previous studies, VOC-limited and transitional regimes appeared in megacities, and VOC-limited regimes also appeared in areas where major power plants were located. In VOC-limited regimes, in other words, areas where NOx is excessively saturated, the reduction in NOx emissions may have weakened the ozone titration and thus led to the increase of ozone. Therefore, VOC emissions should be reduced in the short term rather than NOx emissions to reduce ozone concentrations under the VOC-limited regime.

• Journal of Life Science
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• v.33 no.10
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• pp.783-790
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• 2023

Modern people have an increased incidence of metabolic diseases due to changed eating habits, and diabetes is considered the most significant metabolic disease. Given that existing diabetes treatments are accompanied by side effects, the aim of this study was to identify traditional natural products that have anti-diabetic activity. The potential anti-diabetic and antioxidant activities of natural products were examined using 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assay, α-glucosidase assay, and protein tyrosine phosphatase 1B (PTP1B) inhibition assay. Methanol extracts of Ulmus davidiana var. japonica, Acer tegmentosum branches, Nelumbo nucifera seeds, and Carthamus tinctorius seeds were found to have high anti-diabetic activity and further fractionated with solvents using ethyl acetate and butanol. Consequently, the ethyl acetate fraction of C. tinctorius seeds (MG-11-E) with high α-glucosidase and PTP1B inhibitory activity was selected. MG-11-E was subjected to preparative thin layer chromatography, and fraction #6 showed high α-glucosidase and PTP1B inhibitory activity. Fraction #6 was analyzed and fractionated via high performance liquid chromatography with 50% methanol as the mobile phase, and anti-diabetic activity was observed in the sample that eluted after 4 min as a single peak. The α-glucosidase inhibitory activity exhibited by this sample seemed to be greater than the PTP1B inhibitory activity; thus, it was concluded that a greater anti-diabetic therapeutic effect may be achieved by combining this agent with natural products that inhibit PTP1B activity.

• Journal of Korean Elementary Science Education
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• v.42 no.4
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• pp.560-576
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• 2023

The purpose of this investigation is to: (1) to derive an improvement factor for inquiry-based simulated teaching-learning in pre-service teacher training programs, and pre-service teachers practice simulated teaching that reflect the improvement factor, (2) to analyze the difference in science intrinsic motivation according to science self-efficacy and inquiry-based simulated teaching-learning experience. To achieve these goals, we recruited five elementary and secondary teachers as experts to help us develop an improvement factor based on expert interviews. Subsequently, third-year pre-service teachers of a university of education participated in our analysis of differences in science intrinsic motivation, according to their level of science self-efficacy and experience with inquiry-based simulated teaching-learning. Our methodology involved applying the analytic hierarchy process to expert interviews to derive improvement factor for inquiry-based simulated teaching-learning, followed by a two-way ANOVA to identify significant differences in science intrinsic motivation between groups with varying levels of science self-efficacy. We also conducted post-analysis through MANOVA statements. The results of our study indicate that inquiry-based simulated teaching-learning can be improved through activities that foster digital literacy, ecological literacy, democratic citizenship, and scientific inquiry skills. Moreover, small group activities and student-centered teaching-learning approaches were found to be effective in developing core competencies and promoting science achievements. Specifically, pre-service teachers prepared a teaching-learning course plan and inquiry-based simulated teaching-learning in seventh-grade in the Earth and Space subject area. Pre-service teachers' science intrinsic motivation analyze significant differences in all levels of science self-efficacy before and after simulated teaching-learning and significant difference in the interaction effect between simulated teaching-learning and scientific self-efficacy. Particularly, group with low scientific self-efficacy, the difference in science intrinsic motivation according to simulated teaching-learning was most significant. Teachers' scientific self-efficacy and intrinsic motivation are needed to improve science achievement and affective domains of students in class. Therefore, this study contributes to suggest inquiry-based simulated teaching-learning reflecting school practices from the pre-service teacher curriculum.

• Journal of Life Science
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• v.33 no.11
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• pp.868-875
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• 2023

Kinesin-1 is a motor protein identified as the first member of the kinesin superfamily (KIF), which plays a role in intracellular cargo transport by acting as microtubule-dependent motor proteins within cells. Kinesin-1 consists of two heavy chains (KHCs, also known as KIF5s) and two light chains (KLCs). The 93 amino acids in the carboxyl (C)-terminal tail region of KIF5A are not homologous to the C-terminal tail region of KIF5B or the C-terminal tail region of KIF5C. In this study, we used a yeast two-hybrid screen to identify the binding proteins that interacted with the C-terminal region of KIF5A. We found an association between KIF5A and CUE domain containing 2 (CUEDC2), which is proposed to function as an adaptor protein involved in ubiquitination pathways and protein trafficking. CUEDC2 bound to the C-terminal region of KIF5A and did not interact with KIF5B (the motor of kinesin-1), KIF3A (the motor of kinesin-2), or kinesin light chain 1 (KLC1). KIF5A specifically bound to the C-terminal region of CUEDC2. Furthermore, KIF5A did not interact with another isoform: CUEDC1. In addition, glutathione S-transferase (GST) pull-downs showed that KIF5A directly bound GST-CUEDC2 but did not interact with GST-CUEDC1 and GST alone. When myc-KIF5A and EGFP-CUEDC2 were co-expressed in HEK-293T cells, CUEDC2 co-immunoprecipitated with kinesin-1, and myc-KIF5A and FLAG-CUEDC2 colocalized in the cells. These results suggest that in intracellular cargo transport by kinesin-1, CUEDC2 serves as an adaptor protein connecting kinesin-1 and cargo by binding to KIF5A.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.393-404
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• 2023

The Natural Monument Forest (NMF) is a form of natural and cultural heritage that has symbolized the harmony between nature and culture in Korea for a long time. Recently, the NMF has deteriorated due to industrialization and reckless city expansion. Given this situation, it is necessary to preserve and manage the ecosystem of the NMF through preferential research regarding the forest community structure. Accordingly, this study sought to identify the community structure by analyzing the vegetation classification, stratum structure,and species diversity using vegetation data collected from the Forest of Japanese Torreyas in Pyeongdae-ri, Jeju and the Subtropical Forest of Nabeup-ri, Jeju. The results classified the forest vegetation as a Litsea japonica community group divided into two communities: a Torreya nuciferacommunity and a Quercus glauca community. The T. nuciferacommunity was subdivided into the Idesia polycarpa group and Dryopteris erythrosora group, while the Q. glauca community was subdivided into the Mercurialis leiocarpa group and Arachniodes aristata group. The T. nucifera species showed the highest level of importance in vegetation units 1 (Litsea japonicacommunity group-Torreya nucifera community-Idesia polycarpa group) and 2 (Litsea japonica community group-Torreya nucifera community-Dryopteris erythrosora group), whereas Q. glauca showed the highest level of importance in vegetation units 3 (Litsea japonica community group-Quercus glauca community-Mercurialis leiocarpa group) and 4 (Litsea japonica community group-Quercus glauca community-Arachniodes aristata group). In terms of the species diversity, vegetation units 1, 2, 3, and 4 had 2.866, 2.716, 2.222, and 2.326 species, respectively. These findings suggest that it is necessary to prepare a differentiated management plan for each vegetation unit.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.976-983
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• 2023

Purpose: The dynamic behavior of a bridge structure under seismic loading depends on many uncertainties, such as the nature of the seismic waves and the material and geometric properties. However, not all uncertainties have a significant impact on the dynamic behavior of a bridge structure. Since probabilistic seismic performance evaluation considering even low-impact uncertainties is computationally expensive, the uncertainties should be identified by considering their impact on the dynamic behavior of the bridge. Therefore, in this study, a global sensitivity analysis was performed to identify the main parameters affecting the dynamic behavior of bridges with I-curved girders. Method: Considering the uncertainty of the earthquake and the material and geometric uncertainty of the curved bridge, a finite element analysis was performed, and a surrogate model was developed based on the analysis results. The surrogate model was evaluated using performance metrics such as coefficient of determination, and finally, a global sensitivity analysis based on the surrogate model was performed. Result: The uncertainty factors that have the greatest influence on the stress response of the I-curved girder under seismic loading are the peak ground acceleration (PGA), the height of the bridge (h), and the yield stress of the steel (fy). The main effect sensitivity indices of PGA, h, and fy were found to be 0.7096, 0.0839, and 0.0352, respectively, and the total sensitivity indices were found to be 0.9459, 0.1297, and 0.0678, respectively. Conclusion: The stress response of the I-shaped curved girder is dominated by the uncertainty of the input motions and is strongly influenced by the interaction effect between each uncertainty factor. Therefore, additional sensitivity analysis of the uncertainty of the input motions, such as the number of input motions and the intensity measure(IM), and a global sensitivity analysis considering the structural uncertainty, such as the number and curvature of the curved girders, are required.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1651-1669
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• 2023

Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.

• Journal of Venture Innovation
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• v.4 no.1
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• pp.51-65
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• 2021

The HR policy in the public sector was closed and operated mainly on written tests, but in 2006, a new evaluation, promotion and education system based on competence was introduced in the promotion and selection system of civil servants. In particular, the seniority-oriented promotion system was evaluated based on competence by operating an Assessment Center related to promotion. Competency evaluation is known to be the most reliable and valid evaluation method among the evaluation methods used to date and is also known to have high predictive feasibility for performance. In 2001, 19 government standard competency models were designed. In 2006, the competency assessment was implemented with the implementation of the high-ranking civil service team system. In the public sector, the purpose of the competency evaluation is mainly to select third-grade civil servants, assign fourth-grade civil servants, and promotion fifth-grade civil servants. However, competency assessments in the public sector differ in terms of competency assessment objectives, assessment processes and competency assessment programmes compared to those in the private sector. For the purposes of competency assessment, the public sector is for the promotion of candidates, and the private sector focuses on career development and fostering. Therefore, it is not continuously developing capabilities than the private sector and is not used to enhance performance in performing its duties. In relation to evaluation items, the public sector generally operates a system that passes capacity assessment at 2.5 out of 5 for 6 competencies, lacks feedback on what competencies are lacking, and the private sector uses each individual's competency score. Regarding the selection and operation of evaluators, the public sector focuses on fairness in evaluation, and the private sector focuses on usability, which is inconsistent with the aspect of developing capabilities and utilizing human resources in the right place. Therefore, the public sector should also improve measures to identify outstanding people and motivate them through capacity evaluation and change the operation of the capacity evaluation system so that they can grow into better managers through accurate reports and individual feedback