Korean Journal of Agricultural and Forest Meteorology
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v.23
no.3
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pp.156-162
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2021
The number of smart farms has increased to save labor in agricultural production as the subsidy become available from central and local governments. The number of illegal greenhouses has also increased, which causes serious issues for the local governments. In the present study, we developed Mask-RCNN model to detect greenhouses based on satellite images. Greenhouses in the satellite images were labeled for training and validation of the model. The Mask-RC NN model had the average precision (AP) of 75.6%. The average precision values for 50% and 75% of overlapping area were 91.1% and 81.8%, respectively. This results indicated that the Mask-RC NN model would be useful to detect the greenhouses recently built without proper permission using a periodical screening procedure based on satellite images. Furthermore, the model can be connected with GIS to establish unified management system for greenhouses. It can also be applied to the statistical analysis of the number and total area of greenhouses.
After the COVID-19 pandemic, hand hygiene has become more important to prevent and reduce infection. To manage and provide water to ensure safe handwashing, water governance and the role of public servants are also getting critical. Many organizations have given their priority to capacity building of public servants. In the Strategic Plan for the ninth phase of the Intergovernmental Hydrological Programme (2022-2029), 'Water education in the Fourth Industrial Revolution' is included as a priority. In Korea, ODA in the field of water and sanitation is emphasized in Korea's 3rd Mid-term Strategy for Development Cooperation (2021-2025). Also, KOICA and various water-related organizations have been organizing water education programs for developing countries. This study presents the direction for water education for public servants in developing countries in the post COVID-19 through the education program cases of the International Centre for Water Security and Sustainable Management established by the agreement between the Korean government and UNESCO in 2017. The study suggests that water-related organizations should cooperate with each other to prevent duplication of water education contents. It also suggests that blended learning should be actively utilized for the improvement of education program effectiveness. Lastly, the study emphasizes that education demand for the water technologies related to the fourth industrial revolution and smart water management is increasing, which should be considered when water-related organizations create online content or design education programs.
Background and objective: This study was conducted to identify the components of kindergartener horticultural education by deriving objective components of horticultural education using the Delphi survey method, and then to provide basic data that can be used when creating horticultural programs in the regular curriculum. Methods: A total of 32 experts including professors of early childhood education, kindergarten directors, horticultural therapy professors, and horticultural therapists were selected as the Delphi panel. Of the 32 selected, only 29 answered all three rounds of the surveys. For the first round of the survey, an open-ended questionnaire, was used, and in the second and third rounds closed-ended questionnaires were used. Results: Results indicated that under the category of the goals of horticultural education, there were 7 items related to the current problems of horticultural education, 16 items related to the need for horticultural education in the smart age, 18 items related to the direction of horticultural education, and 5 items related to the areas most suitable for horticulture education for young children in the Nuri Curriculum. Results in the category of the implementation of horticultural education indicated that 2 items related to horticultural education hours, 3 items related to the venue for horticultural education, 2 items related to the activity types applicable to the Nuri Curriculum, and 4 items related to the objects of horticultural activities were derived. As the current problems of horticultural education, the following items were identified: event-oriented activity (M = 4.24) and lack of kindergarten teachers' opportunities for systematic gardening education (M = 4.21). The results related to the necessity of horticultural education indicated the following items: education on respect for life through caring (M = 4.59), emotional intelligence and stability (M = 4.55), directly experience of the growth process of plants (M = 4.55), and development of the five senses (M = 4.55). Finally, within the direction of horticultural education: nurturing the desire to live with nature (M = 4.50), and learning about life (M = 4.44) was identified, which had higher averages. Within the areas of the Nuri Curriculum, which is most consistent with horticultural education, nature exploration (M = 4.69) and the integration of all areas (M = 4.59) were derived as priorities. Also, regarding the implementation of horticultural education, the following items were derived as the priority from the expert group: 30-40 minutes (M = 4.14) and 40-50 minutes (M = 4.14) for class periods, outdoor garden in a kindergarten(M = 4.66) for the venue of gardening education, outside play (M = 4.59) for the activity type, and vegetable crops (M = 4.55) for the objects of gardening activities. Conclusion: It is significant that the goal and implementation of kindergartner horticultural education were objectively derived through collecting opinions of expert panels. Based on the results of this study, a horticultural education program for kindergarten teachers should be implemented.
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.
This study was conducted to improve the convenience of design of mobile VR devices use in a way binds smart phones. Research on traditional mobile VR devices is insufficient. So the first survey was conducted on users 100 to understand the current status and status of mobile VR devices. As a result, it was found that the satisfaction with the convenience of use was significantly lowered, and countermeasures were needed. Then, a second survey of 30 Heavy Users was conducted to find out specific usability and problems of mobile VR devices. Through this, problems, ease of use, and other opinions of mobile VR devices were found. The survey results were analyzed through the Descriptive Statistics Act, and it was found that improvement was urgent due to low satisfaction with wearing and network. In-depth interviews were conducted with the same respondents. As with the problems derived first, problems such as wearing satisfaction, excessive head weight for long-term use, and lack of content could be found. Based on the previous studies, the focus group interview consisting of 6 experts derived the ease of use evaluation element. It consists of elements that can satisfy the convenience of use of mobile VR devices for creation, wearing satisfaction, network, morphology, learning, and spatiality, and has a total of 26. Using this evaluation elements, it is intended to provide better ease of use to users who will use the mobile VR device.
In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.
This study investigated the impact of elementary science classes using metaverse on the academic achievement, positive experience in science, and digital literacy of elementary school students. In addition, we examined their perceptions. The respondents were derived from two classes in the sixth grade at an elementary school in Gyeonggi-do, who were selected designated as the experimental (n=29 students) and comparative (n=29) groups, respectively. Across five lessons under the "Plant Structure and Function" unit, the experimental group conducted science classes using the metaverse, whereas the comparative group conducted general textbook-based classes. To investigate instructional effects, the study performed ANCOVA using the pre-test score as a covariate, a survey on the perception of students about science classes using metaverse, and conducted interviews with a number of subjects. The result demonstrated that science classes using metaverse exerted no significant effect on scientific academic achievement and digital literacy. However, the study observed a statistically significant effect on science learning emotion which is a sub-element of positive experiences in science. The students were positively aware of science classes using metaverse in terms of interesting and diverse activities, and free expression of inquiry results and perceived the instability of smart devices and network connections as regrettable. Finally, the study posed the implications of the use of metaverse in science classes.
The Journal of the Korea institute of electronic communication sciences
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v.18
no.6
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pp.1321-1330
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2023
This study attempts to address the problem of 3D pose estimation for multiple human objects through a single image generated during the character development process that can be used in augmented reality. In the existing top-down method, all objects in the image are first detected, and then each is reconstructed independently. The problem is that inconsistent results may occur due to overlap or depth order mismatch between the reconstructed objects. The goal of this study is to solve these problems and develop a single network that provides consistent 3D reconstruction of all humans in a scene. Integrating a human body model based on the SMPL parametric system into a top-down framework became an important choice. Through this, two types of collision loss based on distance field and loss that considers depth order were introduced. The first loss prevents overlap between reconstructed people, and the second loss adjusts the depth ordering of people to render occlusion inference and annotated instance segmentation consistently. This method allows depth information to be provided to the network without explicit 3D annotation of the image. Experimental results show that this study's methodology performs better than existing methods on standard 3D pose benchmarks, and the proposed losses enable more consistent reconstruction from natural images.
The Journal of the Convergence on Culture Technology
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v.10
no.2
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pp.357-363
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2024
As AR display virtual technology enters public learning life extensively, the way in which reality and virtual connection are connected is also changing. The purpose of this paper is to study the expression between the 3D connection sensory information visualization experience and virtual reality enhancement through the visual direction sensory information visualization experience of the plane. It is analyzed by examining the basic setting method compared to the current application of AR display and flat visualization cases. The scope of this paper is to enable users to have a better experience through the relationship with sensory visualization, centering on eye tracking technology in the four categories of AR display connection design: gesture connection, eye tracking, voice connection, and sensor. Focusing on eye tracking technology through AR display interaction and current application and comparative analysis of flat visualization cases, the geometric consistency of visual figures, light and color consistency, combination of multi-sensory interaction methods, rational content display, and smart push presented sensory visualization in virtual reality more realistically and conveniently, providing a simple and convenient sensory visualization experience to the audience.
KIPS Transactions on Software and Data Engineering
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v.13
no.1
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pp.1-16
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2024
Over recent years, 6 Sigma has become a key methodology in manufacturing for quality improvement and cost reduction. However, challenges have arisen due to the difficulty in analyzing large-scale data generated by smart factories and its traditional, formal application. To address these limitations, a big data-based 6 Sigma approach has been developed, integrating the strengths of 6 Sigma and big data analysis, including statistical verification, mathematical optimization, interpretability, and machine learning. Despite its potential, the practical impact of this big data-based 6 Sigma on manufacturing processes and management performance has not been adequately verified, leading to its limited reliability and underutilization in practice. This study investigates the efficiency impact of DX SS, a big data-based 6 Sigma, on manufacturing processes, and identifies key success policies for its effective introduction and implementation in enterprises. The study highlights the importance of involving all executives and employees and researching key success policies, as demonstrated by cases where methodology implementation failed due to incorrect policies. This research aims to assist manufacturing companies in achieving successful outcomes by actively adopting and utilizing the methodologies presented.
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