• Research in Plant Disease
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• v.28 no.3
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• pp.113-121
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• 2022

Rice blast is a major plant disease that occurs worldwide and significantly reduces rice yields. Rice blast disease occurs periodically in Korea, causing significant socio-economic damage due to the unique status of rice as a major staple crop. A disease outbreak prediction system is required for preventing rice blast disease. Epidemiological investigations of disease outbreaks can aid in decision-making for plant disease management. Currently, plant disease prediction and epidemiological investigations are mainly based on quantitatively measurable, structured data such as crop growth and damage, weather, and other environmental factors. On the other hand, text data related to the occurrence of plant diseases are accumulated along with the structured data. However, epidemiological investigations using these unstructured data have not been conducted. The useful information extracted using unstructured data can be used for more effective plant disease management. This study analyzed news articles related to the rice blast disease through text mining to investigate the years and provinces where rice blast disease occurred most in Korea. Moreover, the average temperature, total precipitation, sunshine hours, and supplied rice varieties in the regions were also analyzed. Through these data, it was estimated that the primary causes of the nationwide outbreak in 2020 and the major outbreak in Jeonbuk region in 2021 were meteorological factors. These results obtained through text mining can be combined with deep learning technology to be used as a tool to investigate the epidemiology of rice blast disease in the future.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.

• Journal of Korean Home Economics Education Association
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• v.33 no.1
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• pp.169-185
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• 2021

The purpose of this study is to apply the clothing teaching-learning plan from a critical science perspective developed to improve teenager's empowerment, and to examine it's effects. A total of 12 plans of 5 modules(Module A to E) developed from critical science perspective were implemented for four weeks. Second-year students (N 42) of K Middle School located in Y-si, Gyeonggi-do participated in the study in the study, and the survey results were analyzed quantitatively using t-tests. For the quality analysis, The student interview data, action reports and etc. were collected, and qualitative analysis was conducted using empowerment model as the analysis framework. The findings of study are follows. First, two hours each for modules A to D, and four hours for module E were assigned, because module E included an action project. In the action projects by for groups, students were expected to take the lead in conducting the activities such as developing promotional posters, posting opinions online, promoting videos, informing how to make recyclables, and donating to the community. Second, as a result of analyzing the pre-implementation vs post-implementation empowerment scores, a significant difference was found in social-political empowerment (t=-2.06, p<0.05). According to the analysis of student interviews and students project's reports, students were found to become aware of empowerment through the instruction. On the intrapersonal level, positive self-awareness and self-efficacy, and on the interpersonal level, smooth communication and democratic decision-making were confirmed. This study is meaningful in that regular a home economics instruction class from a critical science perspective have made a quantitative and qualitative impact on teenagers' improvement empowerment, providing opportunities to find their roles in the soceity, cooperate with others, and behave responsibly as members of society.

• Journal of Korean Elementary Science Education
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• v.41 no.4
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• pp.658-672
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• 2022

The unique teaching and learning difficulties of speed-related units in elementary school science are mainly due to the student's lack of mathematical thinking ability and procedural knowledge on speed measurement, and curriculums and textbooks must be constructed with these in mind. To identify the implications of composing a new science curriculum and relevant textbooks, this study reviewed the structure and contents of the speed-related units of three curriculums from the 2007 revised curriculum to the 2015 revised curriculum and the resulting textbooks and examined their relevance in light of the literature. Results showed that the current content carries the risk of making students calculate only the speed of an object through a mechanical algorithm by memorization rather than grasp the multifaceted relation between traveled distance, duration time, and speed. Findings also highlighted the need to reorganize the curriculum and textbooks to offer students the opportunity to learn the meaning of speed step-by-step by visualizing materials such as double number lines and dealing with simple numbers that are easy to calculate and understand intuitively. In addition, this paper discussed the urgency of improving inquiry performance such as process skills by observing and measuring an actual object's movement, displaying it as a graph, and interpreting it rather than conducting data interpretation through investigation. Lastly, although the current curriculum and textbooks emphasize the connection with daily life in their application aspects, they also deal with dynamics-related content somewhat differently from kinematics, which is the main learning content of the unit. Hence, it is necessary to reorganize the contents focusing on cases related to speed so that students can grasp the concept of speed and use it in their everyday lives. With regard to the new curriculum and textbooks, this study proposes that students be provided the opportunity to systematically and deeply study core topics rather than exclude content that is difficult to learn and challenging to teach so that students realize the value of science and enjoy learning it.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.393-404
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• 2022

Reliable terrestrial rainfall observations from satellites at finer spatial resolution are essential for urban hydrological and microscale agricultural demands. Although various traditional "top-down" approach-based satellite rainfall products were widely used, they are limited in spatial resolution. This study aims to assess the potential of a novel "bottom-up" approach for rainfall estimation, the parameterized SM2RAIN model, applied to the C-band SAR Sentinel-1 satellite data (SM2RAIN-S1), to generate high-spatial-resolution terrestrial rainfall estimates (0.01° grid/6-day) over Central South Korea. Its performance was evaluated for both spatial and temporal variability using the respective rainfall data from a conventional reanalysis product and rain gauge network for a 1-year period over two different sub-regions in Central South Korea-the mixed forest-dominated, middle sub-region and cropland-dominated, west coast sub-region. Evaluation results indicated that the SM2RAIN-S1 product can capture general rainfall patterns in Central South Korea, and hold potential for high-spatial-resolution rainfall measurement over the local scale with different land covers, while less biased rainfall estimates against rain gauge observations were provided. Moreover, the SM2RAIN-S1 rainfall product was better in mixed forests considering the Pearson's correlation coefficient (R = 0.69), implying the suitability of 6-day SM2RAIN-S1 data in capturing the temporal dynamics of soil moisture and rainfall in mixed forests. However, in terms of RMSE and Bias, better performance was obtained with the SM2RAIN-S1 rainfall product over croplands rather than mixed forests, indicating that larger errors induced by high evapotranspiration losses (especially in mixed forests) need to be included in further improvement of the SM2RAIN.

• Journal of Nutrition and Health
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• v.56 no.1
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• pp.97-111
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• 2023

Purpose: Childhood obesity has become a social problem due to the social distancing necessitated by the coronavirus disease 2019 pandemic. This study aimed to identify the dietary problems of obese children through various dietary assessment methods and to confirm the usefulness of each method. Methods: The subjects were 88 students in the 4th to 6th grade of elementary school who participated in the nutrition camp organised by the Busan Metropolitan Office of Education, 2020. To evaluate dietary problems and assess diet quality, 24-hour meal records, monthly food intake frequency, and Dietary Screening Test (DST) data were analyzed. Results: Of the subjects, 15.7%, 30.3%, and 53.9% were normal weight, overweight, and obese, respectively. The average age was 11.77 ± 0.77 years and the average body mass index was 23.96 ± 3.01 kg/m². It was observed from the 24-hour meal record method that the overweight and obese subject groups consumed fewer green vegetables (p < 0.001) and white vegetables (p < 0.01) than the normal weight group. In the monthly food intake frequency method, the consumption of ramen (p < 0.01), snacks (p < 0.05), and sausages (p < 0.05) were high in the obese group, and that of anchovies, broccoli, and sweet pumpkin was high in the normal group (p < 0.05). The comparative data from the DST revealed that the overweight and obese groups had less vegetable intake than the normal weight group (p < 0.01) and had higher intakes of dairy products, fast food, and sweet snacks (p < 0.05). Conclusion: The usefulness of each method in the dietary evaluation of obese children was confirmed. To address the problem of obesity, it is necessary to evaluate the dietary problem and approach it with a customized solution tailor-made for the individual subject.

• 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 Internet Computing and Services
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• v.24 no.2
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• pp.19-26
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• 2023

Humans have adapted and evolved to natural light. However, as humans stay in indoor longer in modern times, the problem of biorhythm disturbance has been induced. To solve this problem, research is being conducted on lighting that reproduces the correlated color temperature(CCT) of natural light that varies from sunrise to sunset. In order to reproduce the CCT of natural light, multiple LED light sources with different CCTs are used to produce lighting, and then a control index DB is constructed by measuring and collecting the light characteristics of the combination of input currents for each light source in hundreds to thousands of steps, and then using it to control the lighting through the light characteristic matching method. The problem with this control method is that the more detailed the steps of the combination of input currents, the more time and economic costs are incurred. In this paper, an LED lighting control method that applies interpolation and combination calculation based on the minimum spectral power distribution information for each light source is proposed to reproduce the CCT of natural light. First, five minimum SPD information for each channel was measured and collected for the LED lighting, which consisted of light source channels with different CCTs and implemented input current control function of a 256-steps for each channel. Interpolation calculation was performed to generate SPD of 256 steps for each channel for the minimum SPD information, and SPD for all control combinations of LED lighting was generated through combination calculation of SPD for each channel. Illuminance and CCT were calculated through the generated SPD, a control index DB was constructed, and the CCT of natural light was reproduced through a matching technique. In the performance evaluation, the CCT for natural light was provided within the range of an average error rate of 0.18% while meeting the recommended indoor illumination standard.

• Korean Journal of Environmental Biology
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• v.40 no.4
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• pp.464-476
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• 2022

In recent years, macroalgal bloom occurs frequently in coastal oceans worldwide. It might be attributed to accelerating climate change. "Green tide" events caused by proliferation of green macroalgae (Ulva spp.) not only damage the local economy, but also harm coastal environments. These nuisance events have become common across several coastal regions of continents. In Korea, green tide incidences are readily seen throughout the year along the coastlines of Jeju Island, particularly the northeastern coast, since the 2000s. Ulva species are notorious to be difficult for morphology-based species identification due to their high degrees of phenotypic plasticity. In this study, to investigate temporal variation in Ulva community structure on Jeju Island between 2015 and 2020, chloroplast barcode tufA gene was sequenced and phylogenetically analyzed for 152 specimens from 24 sites. We found that Ulva ohnoi and Ulva pertusa known to be originated from subtropical regions were the most predominant all year round, suggesting that these two species contributed the most to local green tides in this region. While U. pertusa was relatively stable in frequency during 2015 to 2020, U. ohnoi increased 16% in frequency in 2020 (36.84%), which might be associated with rising sea surface temperature from which U. ohnoi could benefit. Two species (Ulva flexuosa, Ulva procera) of origins of Europe should be continuously monitored. The findings of this study provide valuable information and molecular genetic data of genus Ulva occurring in southern coasts of Korea, which will help mitigate negative influences of green tide events on Korea coast.

• Journal of Korean Society of Forest Science
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• v.111 no.1
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• pp.150-164
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• 2022

This study was conducted to provide basic information for the development of silvicultural guidelines and manuals. This was achieved through analysis of tree and stand characteristics according to the first and second thinning in Korean white pine plantations. Data were collected from permanent plots installed at Korean white pine plantations according to thinning intensity, and residual tree and stand variables, including diameter at breast height (DBH), volume, and mortality at age 19-43, were analyzed using data repeatedly collected in 4-5 measurements by experiments. According to one-way variance of analysis, tree DBH and volume were significantly different according to thinning intensity (p<0.05). DBH distribution was skewed to the left side over time as thinning intensity was heavier. Thus, tree DBH values were larger in heavy thinning plots with increased age. The periodic annual increment (PAI) of DBH was higher with heavier thinning intensity and fewer years after thinning. The PAI range by thinning intensity was 0.48-0.95 cm/year at age 19-24. In addition, the PAI increased in heavy thinning plots after the second thinning; The PAI range by thinning intensity was 0.29-0.67 cm/year after the second thinning at age 37-42. The PAI of tree volume differed according to thinning intensity, and the PAI value did not decrease obviously, in contrast to the pattern of the DBH PAI. Stand volume was generally higher in high-density stands, and the PAI of stand volume was high in unthinned and light thinning plots. Mortality was highest in unthinned plots, and the differences in mortality according to thinning intensity increased over time. Consequently, the growth of DBH and tree volume was lower as stand density increased, but this growth was facilitated with appropriate first and second thinning operations.