• Communications of Mathematical Education
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• 제35권2호
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• pp.173-191
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• 2021

This study noted that a survey of teachers in a leading study conducted in Korea during the Pandemics period pointed out that the "real-time interactive" classes account for a significantly small portion of the remote class format. Contentually, the study reported cases of developing and applying "real-time interactive" class materials based on "planar decision requirements" of high school mathematics subject geometry. The teacher who participated in the development was a math teacher who worked at a Seoul-based high school with 28 years of high school teaching experience, and a teacher who was in charge of geometry in the math department in 2020. The development teacher decided to develop real-time interactive classes. In particular, the materials were developed by organizing the class guidance plan in four stages: 'Meeting and Class Guidance', 'Giving motivation', 'Suggesting tasks', 'Individual Investigative Activities and Teacher Feedback' and 'Reflection and Evaluation' which were selected through the process of selecting the class contents and selecting online class tools. At this time, the development teacher produced and presented about five minutes of video material using the videooscribe, a whiteboard animation program. And in case of task number 8, it consisted of recording the students' free thoughts after class, which served as a role of assessment by students themselves and providing feedback to their teachers. This study is a case study that introduces a series of courses in which field teachers develop class materials, and in addition to presenting class materials that can be applied directly to classes, is a result of a study that focuses on the role of presenting samples for future class data development. The materials developed were verified as class materials based on the opinions of the students who participated in the class and the results of the evaluation commissioned by the three math teachers.

• Journal of Korea Water Resources Association
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• 제54권8호
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• pp.629-641
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• 2021

In this study, a two-dimensional numerical model (Nays2DH) was applied to analyze the process of morphological changes in the river channel bed depending on the changes in the amount of flooding after fully opening the Sejong weir, which was constructed upstream of the Geum River. For this, numerical simulations were performed by assuming the flow conditions, such as a non-uniform flow (NF), unsteady flows (single flood event, SF), and a continuous flood event (CF). Here, in the cases of the SF and CF, the normalized hydrograph was calculated from real flood events, and then the hydrograph was reconfigured by the peak flow discharge according to the scenario, and then it was employed as the flow discharge at the upstream boundary condition. In this study, to quantitatively evaluate the morphological changes, we analyzed the time changes in the bed deformation the bed relief index (BRI), and we compared the aerial photographs of the study area and the numerical simulation results. As simulation results of the NF, when the steady flow discharge increases, the ratio of lower width to depth decreases and the speed of bar migration increases. The BRI initially increases, but the amount of change decreased with time. In addition, when the steady flow discharge increases, the BRI increased. In the case of SF, the speed of bar migration decreased with the change of the flow discharge. In terms of the morphological response to the peak flood discharge, the time lag also indicated. In other words, in the SF, the change of channel bed indicates a phase lag with respect to the hydraulic condition. In the result of numerical simulation of CF, the speed of bar migration depending on the peak flood discharges decreased exponentially despite the repeated flood occurrences. In addition, as in the result of SF, the phase lag indicated, and the speed of bar migration decreased exponentially. The BRI increased with time changes, but the rate of increase in the BRI was modest despite the continuous peak flooding. Through this study, the morphological changes based on the hydrological characteristics of the river were analyzed numerically, and the methodology suggested that a quantitative prediction for the river bed change according to the flow characteristic can be applied to the field.

• 한국노년학
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• 제41권2호
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• pp.197-215
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• 2021

This study aims to evaluate Person Centered Care practice and characteristics of care services in Korean long-term care facilities using Dementia Care Mapping as a tool. DCM, systematic observational evaluation tool for measuring dementia patients' QOL, was transformed into self-report rating scale. The process of transforming DCM into a scale of 34 items involves operationalization of DCM concepts and it's adaptation into Korean long-term care practices. Review by research team of Bradford university was added to maintain DCM concept and meaning in this scale. The scale with Cronbach alpha of .88 was surveyed on 343 care workers. Survey result shows PCC value practiced by them is 3.77(of 5 likert scale) and values on each categories of PCC reveal the characteristics of care in Korean facilities; attachment(4.02), comfort(3.95), inclusion(3.89), identity(3.67) and occupation(3.41). Dementia care in Korean facilities focuses on recipients'safety, comfort but lacks individualistic care and the meaningful and fulfilling occupation for patients. Looking at the organizational and individual factors influencing DCM values, the small facilities showed higher PCC values and there are no significant difference in PCC values between public and private facilities. Managers and care workers with career of 1~2 years showed higher PCC values compared to other career ranks and lengthes. This study suggests care practice should be centered on personhood of patients in long-term care facilities, for which introduction of unit care and education of PCC for service providers including support personnel are needed. DCM and Korean DCM scale developed in this study are suggested for the PCC-based assessment on care quality.

• Korean Journal of Agricultural and Forest Meteorology
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• 제24권4호
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• pp.256-266
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• 2022

Empirical models including the Angstrom-Prescott (AP) model have been used to estimate solar radiation at sites, which would support a wide use of crop models. The objective of this study was to estimate two sets of solar radiation estimates using the AP coefficients derived for climate zone (AP_Frere) and specific site (AP_Choi), respectively. The daily solar radiation was estimated at 18 sites in Korea where long-term measurements of solar radiation were available. In the present study, daily solar radiation and sunshine duration were collected for the period from 2012 to 2021. Daily weather data including maximum and minimum temperatures and rainfall were also obtained to prepare input data to a process-based crop model, CERES-Rice model included in Decision Support System for Agrotechnology Transfer (DSSAT). It was found that the daily estimates of solar radiation using the climate zone specific coefficient, SFrere, had significantly less error than those using site-specific coefficients S_Choi (p<0.05). The cumulative values of S_Frere for the period from march to September also had less error at 55% of study sites than those of S_Choi. Still, the use of S_Frere and S_Choi as inputs to the CERES-Rice model resulted in slight differences between the outcomes of crop growth simulations, which had no significant difference between these outputs. These results suggested that the AP coefficients for the temperate climate zone would be preferable for the estimation of solar radiation. This merits further evaluation studies to compare the AP model with other sophisticated approaches such as models based on satellite data.

• The Mathematical Education
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• 제62권3호
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• pp.435-455
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• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.

• Korean Journal of Remote Sensing
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• 제39권2호
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• pp.169-181
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• 2023

Recently, in order to reduce carbon dioxide (CO₂) emissions, which is the main cause of global warming, Korea has declared carbon emission reduction targets and carbon neutral. Accurate assessment of regional emissions and atmospheric CO₂ concentrations is becoming important as a result. In this study, we identified the spatiotemporal differences between satellite-based atmospheric CO₂ concentration and CO₂ emissions for the Korean Peninsula region using column-averaged CO₂ dry-air mole fraction from the Orbiting Carbon Observatory-2 and emission inventory. And we explained these differences using solar-induced fluorescence (SIF), a photosynthetic reaction index according to vegetation growth. The Greenhouse Gas Inventory and Research Center (GIR) and Emissions Database for Global Atmospheric Research (EDGAR) emissions continued to increase in Korea from 2014 to 2018, but the satellite-based atmospheric CO₂ concentration decreased in 2018, respectively. Regionally, GIR and EDGAR emissions increased in 2018 in Gyeonggi-do and Chungcheongbuk-do, but satellite-based CO₂ concentrations decreased for the corresponding years. In addition, the correlation analysis between emissions and satellite-based CO₂ concentration showed a low correlation of 0.22 (GIR) and 0.16 (EDGAR) in Seoul and Gangwon-do. Atmospheric CO₂ concentrations showed a different correlation with SIF by region. In the CO₂-SIF correlation analysis for the growing season (May to September), Seoul and Gyeonggi-do showed a negative correlation coefficient of -0.26, Chungcheongbuk-do and Gangwon-do showed a positive correlation coefficient of 0.46. Therefore, it can be suggested that consideration of the CO₂ absorption process is necessary for analyzing the relationship between the atmospheric CO₂ concentration and emission inventory.

• Korean Journal of Remote Sensing
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• 제39권5_1호
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• 제18권4호
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• pp.117-129
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• 2023

Organizations must seek change in order to adapt to environmental changes and achieve better performance. However, despite this obvious statement, empirical analysis has been almost non-existent due to the difficulty of manipulating organizational performance or change. In this study, we overcame these limitations and analyzed the causes and effects of organizational change by assuming a professional sports team as a venture company, which is relatively easy to objectively measure and evaluate organizational change or performance. We systematically collected and preprocessed traditional and advanced metrics of National Basketball Association (NBA) statistics along with preprocessed trade data from eight years of regular seasons (2014~2015-2021~2022) to analyze our research model. Assessment of process macro model 7 derives the following empirical result. The results of the empirical analysis depict that NBA teams with low organizational performance in the previous season are more likely to make organizational changes through player trades to improve performance. Into the bargain player trades mediate the static relationship between the winning percentage in the previous season and the winning percentage in the current season. However, the indirect effect of a team's previous season's performance on player trades appears to vary depending on the current situations and context of each NBA team. Teams that made the playoffs in the previous season tend to make fewer trades than teams that did not and the previous season's performance is highly correlated with the current season's performance. On the other hand, teams that did not make the playoffs in the previous season tend to make a relatively larger amount of player trades in total, and the mediating effect of trades vanishes in this case. In other words, teams that did not make the playoffs in the previous season experience a larger change in performance due to trades than teams that made the playoffs, even if they achieved the same winning percentage. This empirical analysis of the inverse relationship between organizational change and the performance of professional sports teams has both theoretical and practical implications in the field of sports industry and management by analyzing the fundamentals of organizational change and the performance of professional sports teams.

• Journal of The Korean Association For Science Education
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• 제29권8호
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• pp.990-1010
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• 2009

To derive brain-based evolutionary educational principles, this study examined the studies on the structural and functional characteristics of human brain, the biological evolution occurring between- and within-organism, and the evolutionary attributes embedded in science itself and individual scientist's scientific activities. On the basis of the core characteristics of human brain and the framework of universal Darwinism or universal selectionism consisted of generation-test-retention (g-t-r) processes, a Model of Brain-based Evolutionary Scientific Teaching for Learning (BEST-L) was developed. The model consists of three components, three steps, and assessment part. The three components are the affective (A), behavioral (B), and cognitive (C) components. Each component consists of three steps of Diversifying $\rightarrow$ Emulating (Executing, Estimating, Evaluating) $\rightarrow$ Furthering (ABC-DEF). The model is 'brain-based' in the aspect of consecutive incorporation of the affective component which is based on limbic system of human brain associated with emotions, the behavioral component which is associated with the occipital lobes performing visual processing, temporal lobes performing functions of language generation and understanding, and parietal lobes, which receive and process sensory information and execute motor activities of the body, and the cognitive component which is based on the prefrontal lobes involved in thinking, planning, judging, and problem solving. On the other hand, the model is 'evolutionary' in the aspect of proceeding according to the processes of the diversifying step to generate variants in each component, the emulating step to test and select useful or valuable things among the variants, and the furthering step to extend or apply the selected things. For three components of ABC, to reflect the importance of emotional factors as a starting point in scientific activity as well as the dominant role of limbic system relative to cortex of brain, the model emphasizes the DARWIN (Driving Affective Realm for Whole Intellectual Network) approach.

• Journal of Korea Water Resources Association
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• 제57권8호
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• pp.533-548
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• 2024

Due to climate change with extreme weather events, occurrences of unprecedented heavy rainfall have become more frequent. Since it is difficult to perfectly predict and prevent flood damages, the limitation of traditional prevention-centered approaches has come a issue. The concept of "resilience" has therefore been developed which emphasizes the ability to swiftly recover from damages to previous states or to even better conditions. In this study, we 1) developed a total of 20 domestic flood resilience indicators based on the 4R principles (Redundancy, Robustness, Rapidity, Resourcefulness), 2) conducted applicability evaluations targeting specific disaster-prone areas, and 3) assessed the importance of each indicator through Analytic Hierarchy Process (AHP) analysis with flood-related experts. To confirm the suitability of the developed flood resilience indicators, multicollinearity analysis was performed, and the results indicated that all 20 indicators had tolerance limits above 0.1 and Variance Inflation Factors (VIF) below 10, demonstrating suitability as factors. Furthermore, evaluations of proposed indicators were carried out targeting disaster-prone areas in 2022(21 areas), and AHP analysis was utilized to determine the relative importance of each indicator. The analysis revealed that the importance of each indicator was as follows: Robustness 0.46, Rapidity 0.22, Redundancy 0.17, and Resourcefulness 0.16, with Robustness exhibiting the highest importance. Regarding the sub-indicators that had the greatest influence on each 4R component, river embankment maintenance emerged as the most influential for Robustness, healthcare services for Rapidity, fiscal autonomy of local governments for Resourcefulness, and drainage facilities for Redundancy.