• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.192-202
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• 2017

This study analyzed the influence relations of the subjectivity of satisfaction with curriculum in food cooking area based on NCS by applying Q methodology, targeting graduates of hotel cooking department in college. This paper largely suggests two research questions like following. Research Question 1: What are the acceptance types of satisfaction with curriculum in food cooking area based on NCS? Research Question 2: What are the homogeneous characteristics and implications of each type? In the results of typological analysis based on such research questions, total four types were drawn like following: Type1(N=7): Basic Practical Classes Pursuit-type, Type2(N=5): Domestic Employment Preference-type, Type3(N=5): Famous Chef Inviting Class Pursuit-type, and Type4(N=3): Tailor-Made Lessons Pursuit-type. Each type showed its own distinctive characteristics. In this study, the graduates' perception in a specific cooking department would be used as a basis for follow-up researches. In the future, it would be necessary to have researches to establish the customized-curriculum system such as planning/operating student-centered teaching/learning guidelines and also conducting mentoring programs. Also, it is expected to have continuous follow-up researches to complement the limitations of this study.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.52-67
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• 2020

Recently, the Arctic has been exposed to snow-covered land due to melting permafrost every year, and the Korea Geographic Information Institute(NGII) provides polar spatial information service by establishing spatial information of the polar region. However, there is a lack of spatial information on vegetation sensitive to climate change. This research used a multi-temporal Sentinel-2 image to perform land cover classification of the Ny-Ålesund in Arctic Svalbard. In the pre-processing step, 10 bands and 6 vegetation spectral index were generated from multi-temporal Sentinel-2 images. In image-classification step is consisted of extracting the vegetation area through 8-class land cover classification and performing the vegetation species classification. The image classification algorithm used Random Forest to evaluate the accuracy and calculate feature importance through Out-Of-Bag(OOB). To identify the advantages of multi- temporary Sentinel-2 for vegetation classification, the overall accuracy was compared according to the number of images stacked and vegetation spectral index. Overall accuracy was 77% when using single-time Sentinel-2 images, but improved to 81% when using multi-time Sentinel-2 images. In addition, the overall accuracy improved to about 83% in learning when the vegetation index was used additionally. The most important spectral variables to distinguish between vegetation classes are located in the Red, Green, and short wave infrared-1(SWIR1). This research can be used as a basic study that optimizes input characteristics in performing the classification of vegetation in the polar regions.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.118-129
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• 2022

The purpose of this report is to study a strategic model of promotion activities through various analysis and sales forecasting by selecting wearable products for domestic online companies and collecting sales data. For data analysis, various algorithms are used for analysis and the results are selected as the optimal model. The gradation boosting model, which is selected as the best result, will allow nine independent variables to be entered, including promotion type, price, amount, gender, model, company, grade, sales date, and region, when predicting dependent variables through supervised learning. In this study, the review values set as dependent variables for each type of sales promotion were studied in more detail through the ensemble analysis technique, and the main purpose is to analyze and predict them. The purpose of this study is to study the grades. As a result of the analysis, the evaluation result is 95% of AUC, and F1 is about 93%. In the end, it was confirmed that among the types of sales promotion activities, value-added benefits affected the number of reviews and review grades, and that major variables affected the review and review grades.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.29-35
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• 2022

UV rays have beneficial or harmful effects on the human body depending on the degree of exposure. An accurate UV information is required for proper exposure to UV rays per individual. The UV rays' information is provided by the Korea Meteorological Administration as one component of daily weather information in Korea. However, it does not provide an accurate UVI at the user's location based on the region's Ultraviolet index. Some operate measuring instrument to obtain an accurate UVI, but it would be costly and inconvenient. Studies which assumed the UVI through environmental factors such as solar radiation and amount of cloud have been introduced, but those studies also could not provide service to individual. Therefore, this paper proposes a deep learning model to calculate UVI using solar object information and sunlight characteristics to provide an accurate UVI at individual location. After selecting the factors, which were considered as highly correlated with UVI such as location and size and illuminance of sun and which were obtained through the analysis of sky images and solar characteristics data, a data set for DNN model was constructed. A DNN model that calculates the UVI was finally realized by entering the solar object information and sunlight characteristics extracted through Mask R-CNN. In consideration of the domestic UVI recommendation standards, it was possible to accurately calculate UVI within the range of MAE 0.26 compared to the standard equipment in the performance evaluation for days with UVI above and below 8.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.2
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• pp.310-321
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• 2022

This study aimed to find out how creative education programs using AR/VR affect student's creative problem-solving skills and class satisfaction. For this purpose, a total of 179 students in 7 classes of the first grade of J High school located in the chungbuk region were the subjects of this study. The data were analyzed by performing two-dependent samples (t-test) based on the difference between the pre- and post-scores of creative problem-solving ability test, and the value of class satisfaction was analyzed and interpret using descriptive statistics and interview. The results of this study are as follows. First, except for 'execution', 'problem discovery and analysis', 'idea generation', 'execution plan', 'conviction and communication', and 'innovation tendency' showed statistically significant results. Second, in terms of class satisfaction of the creative education program, it was an average of 3.75 and it was difficult for learners to derive creative ideas, outputs, and results through groups within a given time in regular class, but generally showed a positive response. Therefore, it was confirmed that the creative education program using AR/VR increased student's learning motivation and interest in the process of generation or expanding ideas to solve problems like educational effect of STEAM.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.210-223
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• 2023

This study developed elementary and middle school career education programs linked to science subjects and local natural resources, and explored learning effects and implications for developing and operating career programs. In order to achieve the research purpose, a 10-hour career education program using local natural and social resources was developed and applied to 25 elementary and middle school students in rural areas. As a result of the study, most of the elementary and middle school students who participated in this study were not well aware of the natural and social resource value of the area where they lived. Therefore, when developing and operating a regional-based career education program for elementary and middle school students in rural areas, it is necessary to operate a separate teaching/learning activity time so that students can fully know the natural and social information and resource values of the region. In addition, in order to enhance students' participation and interest in career education programs, it is necessary to organize the operation of the program in groups, not individuals, and to guide students in detail by dividing the program's performance process into several sub-steps. Finally, the core material of regional-linked career education-related programs focused more on their own content, that is, agricultural products grown by parents, and future job settings were higher in start-ups that directly operate companies such as travel agencies and manufacturing companies. Given the recent emphasis on career education in the curriculum, it is suggested that local students should pay more attention to finding materials with local resource value in the field of geoscience, which is closely related to natural resources, and developing and operating them as career education programs linked to local resources.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.311-323
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• 2023

In order to reduce disaster damage by localized heavy rains, floods, and urban inundation, it is important to know in advance whether natural disasters occur. Currently, heavy rain watch and heavy rain warning by the criteria of the Korea Meteorological Administration are being issued in Korea. However, since this one criterion is applied to the whole country, we can not clearly recognize heavy rain damage for a specific region in advance. Therefore, in this paper, we tried to reset the current criteria for a special weather report which considers the regional characteristics and to predict the damage caused by rainfall after 1 hour. The study area was selected as Gyeonggi-province, where has more frequent heavy rain damage than other regions. Then, the rainfall inducing disaster or hazard-triggering rainfall was set by utilizing hourly rainfall and heavy rain damage data, considering the local characteristics. The heavy rain damage prediction model was developed by a decision tree model and a random forest model, which are machine learning technique and by rainfall inducing disaster and rainfall data. In addition, long short-term memory and deep neural network models were used for predicting rainfall after 1 hour. The predicted rainfall by a developed prediction model was applied to the trained classification model and we predicted whether the rain damage after 1 hour will be occurred or not and we called this as 1ST-Model. The 1ST-Model can be used for preventing and preparing heavy rain disaster and it is judged to be of great contribution in reducing damage caused by heavy rain.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1101-1118
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• 2017

Temperatures in urban areas are steadily rising due to rapid urbanization and on-going climate change. Since the spatial distribution of heat in a city varies by region, it is crucial to investigate detailed thermal characteristics of urban areas. Recently, many studies have been conducted to identify thermal characteristics of urban areas using satellite data. However,satellite data are not sufficient for precise analysis due to the trade-off of temporal and spatial resolutions.In this study, in order to examine the thermal characteristics of Daegu Metropolitan City during the summers between 2012 and 2016, Moderate Resolution Imaging Spectroradiometer (MODIS) daytime and nighttime land surface temperature (LST) data at 1 km spatial resolution were downscaled to a spatial resolution of 250 m using a machine learning method called random forest. Compared to the original 1 km LST, the downscaled 250 m LST showed a higher correlation between the proportion of impervious areas and mean land surface temperatures in Daegu by the administrative neighborhood unit. Hot spot analysis was then conducted using downscaled daytime and nighttime 250 m LST. The clustered hot spot areas for daytime and nighttime were compared and examined based on the land cover data provided by the Ministry of Environment. The high-value hot spots were relatively more clustered in industrial and commercial areas during the daytime and in residential areas at night. The thermal characterization of urban areas using the method proposed in this study is expected to contribute to the establishment of city and national security policies.

• Journal of Korean Home Economics Education Association
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• v.18 no.2 s.40
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• pp.63-77
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• 2006

The Purpose of this study is to provide the basic data for the improvement or the contents or clothing curriculum in the 7th technology home economics of middle school. The standard of satisfaction of students' according to the detail domains and the standard of necessity and practical use and learners' patterns of activity task suggested in textbooks were evaluated. The ninth grade 169 boy students and 336 girl students in the national capital region were participated in this survey. According to the survey results, firstly, a dress domain got the highest relative importance(28.56%) while a clothes material domain took the lowest relative importance(8.07%) among various detail domains. Secondly, the standard of satisfaction according to each detail domain fell below the average. Generally girls' satisfaction for teaching was higher than boys'. Thirdly, a clothes material domain showed the lowest necessity for textbook contents according to detail domain and other domains showed above the average. The necessity for textbook contents appeared high for boy students rather than girl students. In addition, boy and girl students did not have interest in content relevance in textbook. Especially, they could not do well and understand experiments and practices in clothing section. Finally, The degree of utilization of the activity task ill textbooks was very low. Among various activity tasks, the learning by discovering and exploring were more utilized than cooperating learning.

• Journal of the Korean earth science society
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• v.34 no.3
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• pp.274-285
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• 2013

The purpose of this study was to develop geological field study sites for learning topography and geology of the area with igneous rocks, specifically in Duibaejae volcanic edifice and Seonang-bawi that were distributed in Goseong-gun, Gangwon-do area. As a follow up, we conducted a study to examine the effect of the study sites when applied to high school freshmen Earth science course. The study proceeded based on the Orion's model in the order of preparatory unit, field trip, and summary unit. The geological field study sites were developed based on the geological study elements presented in the Korean Earth science curriculum. Before the field trip, students simply memorized factual knowledge on minerals, rocks and etc., and showed very low level of understanding on the formation process of the region that was distributed with granite and basalt. Especially, their understanding showed that granite and basalt were formed from the same magma at the same time. After the field trip, they increased in-depth level of understanding about minerals, rocks, and geological structures, but were not able to explain the topographical characteristics of the two rocks because they did not recognize the times of the creation of granite and basalt. The reason is that they have learned the simple concept of the process of forming granite and basalt in their middle school, but that they have not learned the meaning of the difference between two the geological eras when each of the two rocks, granite and basalt, were formed.