• Journal of Wetlands Research
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• v.25 no.4
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• pp.297-305
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• 2023

The recycled irrigation is a type of irrigation that uses downstream water to fulfill irrigation demand in the upstream agricultural areas; the used irrigation water returns back to the downstream. The recycled irrigation is advantageous for securing irrigation water for plant growth, but the returned water typically contains high levels of nutrients due to excess nutrients inputs during the agricultural activities, potentially deteriorating stream water quality. Therefore, quantitative assessment on the effect of the recycled irrigation on the stream water quality is required to establish strategies for effective irrigation water supply and water quality management. For this purpose, a watershed model is generally used; however no functions to simulate the effects of the recycled irrigation are provided in the existing watershed models. In this study, we used multi-reservoir model coupled with the Hydrological Simulation Program-Fortran (HSPF) to estimate the effect of the recycled irrigation on the stream water quality. The study area was the Gwangok stream watershed, a subwatershed of Gyeseong stream watershed in Changnyeong county, Gyeongsangnam-do. The HSPF model was built, calibrated, and used to produce time series data of flow and water quality, which were used as hypothetical observation data to calibrate the multi-reservoir model. The calibrated multi-reservoir model was used for simulating the recycled irrigation. In the multi-reservoir model, the Gwangok watershed consisted of two subsystems, irrigation and the Gwangok stream, and the reactions (plant uptake, adsorption, desorption, and decay) within each subsystem, and fluxes of water and materials between the subsystems, were modeled. Using the developed model, three scenarios with different combinations of the operating conditions of the recycled irrigation were evaluated for their effects on the stream water quality.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.715-728
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• 2023

Tracksite of pterosaurs, birds, and dinosaurs in Chungmugong-dong in Jinju was designated as a natural monument in 2011 and is known as the world's largest in terms of the number and density of pterosaur footprints. This site has been managed by installing protection buildings to conserve in 2018. About 17% of the footprints of pterosaur, theropod, and ornithopod in this site under management in the 2nd protection building are of great academic value, but observation of footprints has difficulties due to continuous physical and chemical damage. In particular, the accumulation of milk-white contaminants is formed by the gypsum and air pollutant complex. Gypsum remains evaporated with a plate or columnar shape in the process of water circulation around the 2nd protection building, and the dust is from through the inflow of the gallery windows. The aqueous solution of gypsum, consisting of calcium from the lower bed and sulfur from grass growth, is catchmented into the groundwater from the area behind the protection building. Pollen and a few minerals other constituents of contaminants, go through the gallery window, which makes it difficult to expel dust. To conserve the fossil-bearing beds from two contaminants of different origins, controlling the water and atmospheric circulation of the 2nd protection building and removing the contaminants continuously is necessary. When cleaning contaminants, the steam cleaning method is sufficiently effective for powder-shaped milk-white contaminants. The fossil-bearing bed consists of dark gray shale with high laser absorption power; the laser cleaning method accompanies physical loss to fossils and sedimentary structures; therefore, avoiding it as much as possible is desirable.

• 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.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.997-1008
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• 2023

Ship detection at sea can be performed in various ways. In particular, satellites can provide wide-area surveillance, and Synthetic Aperture Radar (SAR) imagery can be utilized day and night and in all weather conditions. To propose an efficient ship detection method from SAR images, this study aimed to apply the You Only Look Once Version 5 (YOLOv5) model to Sentinel-1 images and to analyze the difference between individual vs. integrated models and the accuracy characteristics by polarization. YOLOv5s, which has fewer and lighter parameters, and YOLOv5x, which has more parameters but higher accuracy, were used for the performance tests (1) by dividing each polarization into HH, HV, VH, and VV, and (2) by using images from all polarizations. All four experiments showed very similar and high accuracy of 0.977 ≤ AP@0.5 ≤ 0.998. This result suggests that the polarization integration model using lightweight YOLO models can be the most effective in terms of real-time system deployment. 19,582 images were used in this experiment. However, if other SAR images,such as Capella and ICEYE, are included in addition to Sentinel-1 images, a more flexible and accurate model for ship detection can be built.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Journal of Korean Dental Hygiene Science
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• v.6 no.2
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• pp.13-23
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• 2023

Background: The purpose of this study was to examine the differences in the formation of dental hygienist images based on the pathways of obtaining occupational information and to establish a foundation for the correct perception and positive promotion of the dental hygienist profession. Methods: A survey was distributed to 305 college preparatory students in the metropolitan area. The questionnaire consisted of 34 items, including general characteristics(3 items), pathway-related questions(3 items), dental hygienist image-related question(2 1items), application-related questions(2 items), and admission-related questions(5 items). The images of dental hygienists based on general characteristics, perception pathways, and admission were analyzed using the Mann-Whitney U test and Kruskal-Wallis test. Results: The survey results from all participants showed that the overall image of dental hygienists was 3.75 points. Personal image scored the highest at 4.18 points, while social image was the lowest at 3.20 points(p<0.05). The overall image of dental hygienists was higher for the 'online' group (3.88) compared to the 'offline' group, and statistically significant differences were observed among groups in overall, personal, and professional images(p<0.05). The overall image of dental hygienists was higher for those who learned offline (3.87), and the only significant difference between groups was seen in the personal image. When it came to admission, the 'admitted' students gave a higher overall score (4.00) compared to 'non-admitted' students (3.64), with significance found in all areas except for social image (p<0.05). Conclusion: It is believed that effective utilization of online pathways can inform more people about the importance and expertise of dental hygienists, thereby contributing to promoting oral health and enhancing the perception of the profession. Properly valuing and educating about the role of dental hygienists through promotion and education can help improve the image of the profession.

• Communications of Mathematical Education
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• v.38 no.2
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• pp.167-186
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• 2024

Since the 5th mathematics curriculum, the goals of mathematics education have been presented in three categories: cognitive, process, and affective goals. In the 2022 revised mathematics curriculum, the content system was also presented as knowledge-understanding, process-skill, and value-attitude. Therefore, in order to present lesson goals to students, it is necessary to present all three aspects that are the goals of mathematics education. Currently, the lesson titles presented in mathematics textbooks are directly linked to lesson goals and are the first source of information for students during class. Accordingly, this study analyzed how the three categories of lesson titles and content system presented in the 2015 revised 1st and 2nd grade mathematics textbook are connected. As a result, most lesson titles presented two of the three categories, but the reflected elements showed a tendency to focus on the categories of knowledge-understanding and process-skill. Some cases of lesson titles reflected content elements of the value-attitude category, but this showed significant differences depending on the mathematics content area. Considering the goals of mathematics lessons, it will be necessary to look at ways to present lesson titles that reflect the content elements of the value-attitude categories and also explore ways to present them in a balanced way. In particular, considering the fact that students can accurately understand the goals of the knowledge-understanding categories even without presenting them, descriptions that specifically reflect the content elements of the process-skill and value-attitude categories seem necessary. Through this, we attempted to suggest the method of presenting the lesson titles needed when developing the 2022 revised mathematics textbook and help present effective lesson goals using this.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.387-396
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• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

• Journal of the Korean Wood Science and Technology
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• v.2 no.2
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• pp.32-34
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• 1974

The important results which have been obtained in the investigation can be recapitulated as follows. 1. As demonstrated by the experimental results and analyses concerning their effects in the on-ground type mushroom house, the constructions in relation to the side wall and ceiling of the experimental house showed a sufficient heat insulation on effect to protect insides of the house from outside climatic conditions. 2. As the effect on the solar type experimental mushroom house which was constructed in a half basement has been shown by the experimental results and analyses, it has been proved to be effective for making use of solar heat. However there were found two problems to be improved for putting solar house to practical use in the farm mushroom growing: (1) the construction of the roof and ceiling should be the same as for the on ground type house, and (2) the solar heat generating system should be reconstructed properly. 3. Among several ventilation systems which have been studied in the experiments, the underground earthen pipe and ceiling ventilation, and vertical side wall and ceiling ventilation systems have been proved to be most effective for natural ventilation. 4. The experimental results have shown that ventilation systems such as the vertical side wall and underground ventilation systems are suitable to put to practical use as natural ventilation systems for farm mushroom house. These ventilation systems can remarkably improve the temperature of fresh air which is introduced into the house by heat transfers within the ventilation passages, so as to approach to the desired temperature of the house without any cooling or heating operation. For example, if it is assuming that X is the outside temperature and Y is the amount of temperature adjustment made by the influence of the ventilation system, the relationships that exist between X and Y can be expressed by the following regression lines. Underground iron pipe ventilation system. Y=0.9X-12.8 Underground earthen pipe ventilation system. Y=0.96X-15.11 Vertical side wall ventilation system. Y=0.94X-17.57 5. The experimental results have 8hown that the relationships existing between the admitted and expelled air and the $CO_2$ concentration can be described with experimental regression lines or an exponent equation as follows: 5.1 If it is assumed that X is an air speed cm/sec. and Y is an expelled air speed in cm/sec. in a natural ventilation system, since the Y is a function of the X, the relationships that exist between X and Y can be expressed by the regression lines shown below: 5.2 If it IS assumed that X is an admitted volume of air in $m^3$/hr. and Y is an expelled volume of air in $m^3$/hr. in a natural ventilation system, since the Y is a function of the X, the relationships that exist between X and Y can be expressed by the regression lines shown below. 5.3 If it is assumed that expelled air speed in emisec. and replacement air speed in cm/sec. at the bed surface in a natural ventilation system are shown as X and Y. respectively, since the Y is a function of the X. the relationships that exist between X and Y can be expressed by the following regression line: GE(100%)-CV (50%) ventilation system. Y=-0.54X+0.84 5.4 If it is assumed that the replacement air speed in cm/sec. at the bed surface is shown as X, and $CO_2$ concentration which is expressed by multiplying 1000 times the actual value of $CO_2$ % is shown as Y, in a natural ventilation system, since the Y is a function of the X, the relationships that exist between X and Y can be expressed by the following regression line: GE(100%)-CV(50%) ventilation system. Y=114.53-6.42X 5.5 If it is assumed that the expelled volume of air is shown as X and the $CO_2$ concencration which is expressed by multiplying 1000 times the actual of $CO_2$% is shown as Y in a natural ventilation system, since the Y is a function of the X, the relationships that exist between X and Y can be expressed by the following exponent equation: GE(100%)-CV(50%) ventilation system. Y=$127.18{\times}1.0093^{-x}$ 5.6 The experimental results have shown that the ratios of the cross sectional area of the GE and CV vent to the total cubic capacity of the house, required for providing an adequate amount of air in a natural ventilation system, can be estimated as follows: GE(admitting vent of the underground ventilation) 0.3-0.5% (controllable) CV(expelling vent of the ceiling ventilation) 0.8-1.0% (controllable) 6. Among several heating devices which were studied in the experiments, the hot-water boilor which wasmodified to be fitted both as hot-water boiler and as a pressureless steam-water was found most suitable for farm mushroom growing.