• Ecology and Resilient Infrastructure
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• v.9 no.1
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• pp.68-76
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• 2022

In this study, the Habitat Suitability Index (HSI) was calculated in the Miho stream of the Geum river system, and the environmental ecological flow by point was evaluated. Two points (St.3 and St.8) representing the up and downstream of Miho Stream were selected, in order to calculate the Habitat Suitability Index, the depth and velocity at point where each species is appeared were investigated. The Habitat Suitability Index (HSI) was calculated by the Washington Department of Fish and Wildlife (WDFW) method using the number collected by water depth and velocity section and the results of the flow rate survey. Two target species were selected in this study; dominant species and swimming species sensitive to flow. In the case of a single species of Zacco platypus, the water depth was 0.1 - 0.5 m and the velocity was 0.2 - 0.5 m/s. For species of swimming fish, the water depth was 0.2 - 0.5 m and the velocity was 0.2 - 0.5 m/s. The discharge-Weighted Useable Area (WUA) relationship curve and habitat suitability distribution were simulated at the Miho Stream points St.3 and St.8. At the upstream St.3 of Miho Stream, the optimal discharge was simulated as 4.0 m³/s for swimming fishes and 2.7 m³/s for Zacco platypus. At the downstream point of St.8, species of swimming fish were simulated as 8.8 m³/s and Zacco platypus was simulated as 7.6 m³/s. In both points, the optimal discharge of swimming fish was over estimated. This is a result that the Habitat Suitability Index for swimming fish requires a faster flow rate than the habitat conditions of the Zacco platypus. In the calculation of the minimum discharge, the discharge of Zacco platypus is smaller and is evaluated to provide more Weighted Useable Area. In the case of swimming fishes, narrow range of depth and velocity increases the required discharge and relatively decreases the Weighted Useable Area. Therefore, when calculating the Habitat Suitability Index for swimming fishes, it is more advantageous to calculate the index including the habitat of all fish species than to narrow the range.

• Journal of Korean Home Economics Education Association
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• v.34 no.4
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• pp.143-161
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• 2022

The aim of this study is to identify the learning performance of online classes using problem-based learning(PBL) for clothing and textiles majors in college with the increased use of online learning tools after the COVID-19 pandemic. In order to achieve this goal, the PBL was developed and applied to the 'Fashion Marketing and Merchandising' class conducted in real-time online at University in North Chungcheong Province, Korea for four weeks. After a four-week PBL class, a survey was conducted on 35 students in the 'Fashion Marketing and Merchandising' class and the 35 completed questionnaires were used for analysis. The measurement tools of this study were self-directed learning, cooperative learning ability, problem-solving ability, and learning achievement regarded as an important learning effect in PBL class. In addition, students' self-reflective essays were also analyzed to examine the educational effect of PBL applying online classes. As a result of this study, bivariate correlations among the four variables, students' self-directed learning, cooperative learning ability, problem-solving ability, and learning achievement were significantly positive. Furthermore, the results of multiple regression analysis showed that the three independent variables had significant effects on students' perceived learning achievement, in the order of cooperative learning ability, self-directed learning, and problem-solving ability. The students' self-reflective essays indicated that problem-based learning worksheet was helpful for identifying problems, and clarifying what they already and what they need to study more. Based on this study, it could be recommended that online class applying PBL could contribute to the improvement of student's learning performance.

• The Mathematical Education
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• v.62 no.3
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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.

• Journal of agricultural medicine and community health
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• v.48 no.1
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• pp.28-40
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• 2023

Objectives: This study aimed to identify the level of self-assessment of life satisfaction and various factors related to the life satisfaction of Korean physicians. Methods: This study is a secondary data analysis using the 2016 Korean physician survey Korean Physician Survey(KPS) data collected by the Research Institute for Healthcare Policy of the Korean Medical Association. The member database(DB) of the Korean Medical Association was used for sampling and the target population was formed and surveyed by using stratified quota sampling. A questionnaire was sent by E-mail as an online survey method and was conducted for a total of 7 weeks from November 21, 2016 to January 8, 2017. The final number of respondents was 8,564 (response rate 13.8%). In this study, a total of 7,228 physicians, excluding residents and public health doctors who are currently treating patients directly, were studied. Factors affecting the life satisfaction of physicians were analyzed using ordinal logistic regression analysis. Results: The physical factors positively related to the life satisfaction of physicians were those who were in their 60s, female, and thought they had good health status. As for psychological factors, stress was low. As for economic factors, satisfaction with income was high. As for social factors, the physicians lived with their families and were satisfied with the time they could spend with them. Also, the physicians were satisfied with the social respect they received as a doctors. Conclusions: Based on the results of this study, it is thought that a multifaceted approach is needed to increase the life satisfaction of physicians.

• Journal of agriculture & life science
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• v.50 no.3
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• pp.1-11
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• 2016

With increasing interest, there have been studies on LiDAR(Light Detection And Ranging)-based DEM(Digital Elevation Model) to acquire three dimensional topographic information. For producing LiDAR DEM with better accuracy, Filtering process is crucial, where only surface reflected LiDAR points are left to construct DEM while non-surface reflected LiDAR points need to be removed from the raw LiDAR data. In particular, the changes of input values for filtering algorithm-constructing parameters are supposed to produce different products. Therefore, this study is aimed to contribute to better understanding the effects of the changes of the levels of GroundFilter Algrothm's Mean parameter(GFmn) embedded in FUSION software on the accuracy of the LiDAR DEM products, using LiDAR data collected for Hwacheon, Yangju, Gyeongsan and Jangheung watershed experimental area. The effect of GFmn level changes on the products' accuracy is estimated by measuring and comparing the residuals between the elevations at the same locations of a field and different GFmn level-produced LiDAR DEM sample points. In order to test whether there are any differences among the five GFmn levels; 1, 3, 5, 7 and 9, One-way ANOVA is conducted. In result of One-way ANOVA test, it is found that the change in GFmn level significantly affects the accuracy (F-value: 4.915, p<0.01). After finding significance of the GFmn level effect, Tukey HSD test is also conducted as a Post hoc test for grouping levels by the significant differences. In result, GFmn levels are divided into two subsets ('7, 5, 9, 3' vs. '1'). From the observation of the residuals of each individual level, it is possible to say that LiDAR DEM is generated most accurately when GFmn is given as 7. Through this study, the most desirable parameter value can be suggested to produce filtered LiDAR DEM data which can provide the most accurate elevation information.

• Knowledge Management Research
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• v.24 no.2
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• pp.241-262
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• 2023

The phenomena and game records that occur in sports matches are being analyzed in the field of sports game analysis, utilizing advanced technologies and various scientific analysis methods. Among these methods, social network analysis is actively employed in analyzing pass networks. As football is a representative sport in which the game unfolds through player interactions, efforts are being made to provide new insights into the game using social network analysis, which were previously unattainable. Consequently, this study aims to analyze the changes in pass networks over time for a specific football team and compare them in different scenarios, including variations in the game's nature (Qatar World Cup games vs. A match games) and alterations in the opposing team (higher FIFA rankers vs. lower FIFA rankers). To elaborate, we selected ten matches from the games of the Korean national football team following Coach Bento's appointment, extracted network indicators for these matches, and applied four indicators (efficiency, cohesion, vulnerability, and activity/leadership) from a football team's performance evaluation model to the extracted data for analysis under different circumstances. The research findings revealed a significant increase in cohesion and a substantial decrease in vulnerability during the analysis of game performance over time. In the comparative analysis based on changes in the game's nature, Qatar World Cup matches exhibited superior performance across all aspects of the evaluation model compared to A matches. Lastly, in the comparative analysis considering the variations in the opposing team, matches against lower FIFA rankers displayed superior performance in all aspects of the evaluation model in comparison to matches against top FIFA rankers. We hope that the outcomes of this study can serve as essential foundational data for the selection of football team coaches and the development of game strategies, thereby contributing to the enhancement of the team's performance.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.25 no.4
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• pp.81-96
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• 2020

Berthlot's reaction spectrophotometric method is generally used for the analysis of dissolved ammonium in seawater, but in recent years, a fluorescence method using an orthophthaldialdehyde-sulfite (OPA) fluorescent reagent is actively used internationally. In this study, we investigated the effects of the detection limit between the analysis methods, the reagent refractive index inherent in the spectrophotometric method, and the use of different calibration curves to understand the cause of the difference in dissolved ammonium concentration (about 0.31 𝜇M) observed in the seawater samples and a nutrient reference material between two institutions (KIOST (spectrophotometric method, one-order linear regression gradient only), Australia CSIRO (fluorescence method, quadratic formula)) conducted onboard the Australian R/V Investigator in 2017. The method detection limit (0.063 𝜇M) and the reagent refractive index background value (0.054 𝜇M) of the spectrophotometric method measured in this study could explain the difference in dissolved ammonium concentration values of the two institutes about 20% and 17%, respectively. However, when the concentration of the calibration curve of the spectrophotometric method was calculated using the same quadratic as the fluorescence method or the slope and intercept of linear regression, the difference in the dissolved ammonium concentration between the two institutions was reduced to less than the detection limit of the spectrophotometric method. Therefore, the difference in the concentration of dissolved ammonium between the two institutions, found in the nutrient reference materials and the seawater field sample during the international onboard nutrient inter-comparison experiment, may be attributed to be the effect of the different calibration curves used in the two methods rather than the effect of the difference in two analytical methods. When comparing the dissolved ammonium data from seawater samples in the future, it is recommended to pay attention to the information on the baseline, number of standard solutions, and calibration curve used in the analysis.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.80-98
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• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• 한국노년학
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• v.30 no.4
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• pp.1429-1444
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• 2010

The purpose of this study was to examine the impact of elderly people's difficulties in emotional regulation on their quality of life and to suggest possible ways of improving their emotional regulation. The subjects in this study were 345 senior citizens who participated in community education programs and used senior centers. A survey was conducted in person, and the instrument used to check their difficulties in emotional regulation was Gratz & Roemer(2004)'s inventory that was rearranged to serve the purpose of this study. When a factor analysis was carried out, their emotional regulation difficulties were categorized into five factors, which were respectively named troubles in emotional response handling, difficulties in accurate emotional awareness, difficulties in emotional coping, and difficulties in emotional reception. The findings of the study were as follows: First, the senior citizens were different from one another in emotional regulation difficulties according to their personal characteristics involving gender, income, financial state, hospitalization experience over the past three months, and presence or absence of disease. Second, their quality of life significantly varied with gender, age, presence or absence of spouse, form of residence, education, income, financial state, hospitalization experience and presence or absence of disease. Third, as a result of investigating the influence of their emotional regulation difficulties on the overall quality of life, a better quality of life was found among those who were male and who had an income and suffered from fewer diseases. And a lower quality of life was found among the senior citizens who faced difficulties in emotional response handling, who had difficulties in emotional control and who lagged behind in terms of emotional coping. Accordingly, the emotional regulation difficulties of the senior citizens could be said to be closely linked to their quality of life. Given the findings of the study, in which way elderly people could be helped to improve their emotional regulation in consideration of their own personal characteristics was discussed, and how to classify their emotional regulation difficulties from various angles to relieve them of the troubles was suggested.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.6
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• pp.109-120
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• 2023

The High-Frequency Radar (HFR) is an equipment designed to measure real-time surface ocean currents in broad maritime areas.It emits radio waves at a specific frequency (HF) towards the sea surface and analyzes the backscattered waves to measure surface current vectors (Crombie, 1955; Barrick, 1972).The Seasonde HF Radar from Codar, utilized in this study, determines the speed and location of radial currents by analyzing the Bragg peak intensity of transmitted and received waves from an omnidirectional antenna and employing the Multiple Signal Classification (MUSIC) algorithm. The generated currents are initially considered ideal patterns without taking into account the characteristics of the observed electromagnetic wave propagation environment. To correct this, Antenna Pattern Measurement (APM) is performed, measuring the strength of signals at various positions received by the antenna and calculating the corrected measured vector to radial currents.The APM principle involves modifying the position and phase information of the currents based on the measured signal strength at each location. Typically, experiments are conducted by installing an antenna on a ship (Kim et al., 2022). However, using a ship introduces various environmental constraints, such as weather conditions and maritime situations. To reduce dependence on maritime conditions and enhance economic efficiency, this study explores the possibility of using unmanned aerial vehicles (drones) for APM. The research conducted APM experiments using a high-frequency radar installed at Dangsa Lighthouse in Dangsa-ri, Wando County, Jeollanam-do. The study compared and analyzed the results of APM experiments using ships and drones, utilizing the calculated radial currents and surface current fields obtained from each experiment.