• Journal of Korea Entertainment Industry Association
• /
• v.14 no.6
• /
• pp.289-299
• /
• 2020

The purpose of this study was to confirm the effect of mindfulness education on perceived stress, mindfulness, psychological well-being, and brain waves. The study used a repeated-measures design to examine 42 female university students currently enrolled in mindfulness courses. Subjects participated in the mindfulness course once a week for eight weeks, 50 minutes per session. The main outcome variables, such as perceived stress, mindfulness, and psychological well-being, were measured with a structured questionnaire and brain waves were measured with an electroencephalograph. The same variables were then measured after the completion of the eight-week course. The results demonstrate that perceived stress significantly decreased from 1.85±0.39 to 1.66±0.39 points (t=3.44, p=.001), while, on the other hand, mindfulness increased from 3.10±0.26 points to 3.19±0.32 points (t =-2.78, p=.008). There was also a significant difference in the level of autonomy, a subcategory of psychological well-being (t=-2.70, p=.010). In addition, EEG indicated significant changes in the frequencies of Theta channel 19 and Rapid Alpha channels 7 and 10. These results suggest that further studies are needed to elucidate the effects of mindfulness education through the modification of mindfulness course plans, diversification of teaching methods, and improvement in the educational environment.

• Journal of Cadastre & Land InformatiX
• /
• v.52 no.1
• /
• pp.105-118
• /
• 2022

The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.

• Journal of Space Technology and Applications
• /
• v.2 no.1
• /
• pp.41-51
• /
• 2022

CubeSat is a satellite platform that is widely used not only for earth observation but also for space exploration. CubeSat is also used in magnetic field investigation missions to observe space physics phenomena with various shape configurations of magnetometer instrument unit. In case of magnetic field measurement, the magnetometer instrument should be far away from the satellite body to minimize the magnetic disturbances from satellites. But the accommodation setting of the magnetometer instrument is limited due to the volume constraint of small satellites like a CubeSat. In this paper, we investigated that the magnetic field interference generated by the cube satellite was analyzed how much it can affect the reliability of magnetic field measurement. For this analysis, we used a reaction wheel and Torque rods which have relatively high-power consumption as major noise sources. The magnetic dipole moment of these parts was derived by the data sheet of the manufacturer. We have been confirmed that the effect of the residual moment of the magnetic torque located in the middle of the 3U cube satellite can reach 36,000 nT from the outermost end of the body of the CubeSat in a space without an external magnetic field. In the case of accurate magnetic field measurements of less than 1 nT, we found that the magnetometer should be at least 0.6 m away from the CubeSat body. We expect that this analysis method will be an important role of a magnetic cleanliness analysis when designing a CubeSat to carry out a magnetic field measurement.

• Journal of Life Science
• /
• v.32 no.4
• /
• pp.298-302
• /
• 2022

Sulforaphane is a sulfur-containing substance found in large amounts in cruciferous plants and has been reported in several studies to have anticancer effects. Kale is a representative cruciferous plant known as a superfood and is widely used as an ingredient in various dishes. In this study, in order to investigate a cultivation method for increasing kale's content of sulforaphane, kale was treated with geraniol or methyl jasmonate and water stressed during cultivation using a aeroponic culture system in a fully enclosed plant factory. Geraniol or methyl jasmonate were sprayed on the kale's leaf surface once a day for 2 days, and water deprivation stress was conducted for 3 days after 7 days from first treatment day. No difference in growth between control, geraniol, methyl jasmonate treated groups were observed during cultivation. The study results showed that the kale sulforaphane content increased by 60% in the group treated with geraniol compared to the control group and that the group treated with water deprivation stress in addition to geraniol showed a significant increase of 414%. These results show that kale with an increased content of sulforaphane can be grown and that geraniol can be a good research material for increasing the content of functional substances in plants.

• Korean Journal of Heritage: History & Science
• /
• v.55 no.3
• /
• pp.60-72
• /
• 2022

A number of wooden built heritage remain in Korea, and most have been damaged by various biological factors including termite. Owing to the irreversible damage caused by termites, wooden built heritage are losing their authenticity and structural stability. In this study, Area-Wide Integrated Termite Management(AW-ITM) was proposed to prevent termite damage. First, to understand the locational characteristics of these sites, the distance from adjacent forests and surrounding forest areas was analyzed for 182 national designated wooden built heritage(national treasures, treasures) using the Geographic Information System(GIS). By analyzing existing pest control projects(2003-2020) and the components of the ITM, the characteristics of termite control for cultural heritages were determined. Based on these results, the cultural heritage sites and their surrounding spaces were divided into three areas, and the types of cultural properties were divided into six types according to the location and number of buildings. Along with this, termite control measures were proposed for each area and type. The concept of AW-ITM has been partially applied to the "Comprehensive Control of Termites in wooden built heritages Sites" by the Cultural Heritage Administration. Caution must be taken with regard to the establishment of a cultural heritage management policy; AW-ITM should be applied on a trial basis with the results then being carefully analyzed and reflected in the establishment of policies pertaining to the conservation management of cultural heritage.

• Journal of the Korean Electrochemical Society
• /
• v.25 no.4
• /
• pp.154-161
• /
• 2022

The carbon-neutrality induced by the global warming is important for the modern society. Hydrogen has been received the attention as a new energy source to replace the fossil fuels. Polymer electrolyte membrane fuel cells, which convert the chemical reaction energy of hydrogen into electric power directly, are a type of eco-friendly power for future vehicles. Due to the sluggish oxygen reduction reaction and costly Pt catalyst in the cathode, the research related to the replacement of Pt-based catalysts has been vitally carried out. In this case, however, the performance is significantly different from each other and a variety of factors have existed. In this review paper, we rearrange and summarize relevant papers published within 5 years approximately. The selection of precursors, synthesis method, and co-catalyst are represented as a core factor, while the necessity of research for the further enhancement of activity may be raised. It can be anticipated to contribute to the replacement of precious metal catalysts in the various fields of study. The final objective of the future research is depicted in detail.

• Journal of Practical Engineering Education
• /
• v.14 no.2
• /
• pp.267-277
• /
• 2022

Achievement at university is recognized in a comprehensive sense as the level of qualitative change and development that students have embodied as a result of their experience in university education. Therefore, the academic achievement of university students will be given meaning in cooperation with the historical and social demands for diverse human resources such as creativity, leadership, and global ability, but it is practically an indicator of the outcome of university education. Measurement of academic achievement by such credits involves many problems, but in particular, standardization of academic achievement by credits based on evaluation methods, contents, and university rankings is a very difficult problem. In this study, we present a model that uses machine learning techniques to predict whether or not academic achievement is excellent for D-University graduates. The variables used were analyzed using up to 96 personal information and bachelor's information such as graduation year, department number, department name, etc., but when establishing a future education course, only the data after enrollment works effectively. Therefore, the items to be analyzed are limited to the recommended ability to improve the academic achievement of the department/student. In this research, we implemented an academic achievement prediction model through analysis of core abilities that reflect the philosophy, goals, human resources image, and utilized machine learning to affect the impact of the introduction of the prediction model on academic achievement. We plan to apply the results of future research to the establishment of curriculum and student guidance conducted in the department to establish a basis for improving academic achievement.

• Journal of the Korean Society of Radiology
• /
• v.16 no.1
• /
• pp.15-23
• /
• 2022

3D printing technology is being used in various fields such as medicine and biotechnology, and materials containing metal powder are being commercialized through recent material development. Therefore, this study intends to analyze the photon spectrum during added filtration using 3D printing material during diagnostic X-ray examination through simulation. Among the Monte Carlo techniques, MCNPX (ver. 2.5.0) was used. First, the appropriateness of the photon spectrum generated in the simulation was evaluated through SRS-78 and SpekCalc, which are X-ray spectrum generation programs in the diagnostic field. Second, photon spectrum the same thickness of Al and Cu filters were obtained for characterization of 3D printing materials containing metal powder. In addition, the total photon fluence and average energy according to changes in tube voltage were compared and analyzed. As a result, it was analyzed that PLA-Al required about 1.2 ~ 1.4 times the thickness of the existing Al filter, and PLA-Cu required about 1.4 ~ 1.7 times the thickness of the Cu filter to show the same degree of filtration. Based on this study in the future, it is judged that it can be utilized as basic data for manufacturing 3D printing additional filters in medical fields.

• Journal of the Korean Society of Radiology
• /
• v.16 no.1
• /
• pp.25-34
• /
• 2022

Brain computed tomography (CT) is useful for brain lesion diagnosis, such as brain hemorrhage, due to non-invasive methodology, 3-dimensional image provision, low radiation dose. However, there has been numerous misdiagnosis owing to a lack of radiologist and heavy workload. Recently, object detection technologies based on artificial intelligence have been developed in order to overcome the limitations of traditional diagnosis. In this study, the applicability of a deep learning-based YOLOv5s model was evaluated for brain hemorrhage detection using brain CT images. Also, the effect of hyperparameters in the trained YOLOv5s model was analyzed. The YOLOv5s model consisted of backbone, neck and output modules. The trained model was able to detect a region of brain hemorrhage and provide the information of the region. The YOLOv5s model was trained with various activation functions, optimizer functions, loss functions and epochs, and the performance of the trained model was evaluated in terms of brain hemorrhage detection accuracy and training time. The results showed that the trained YOLOv5s model is able to provide a bounding box for a region of brain hemorrhage and the accuracy of the corresponding box. The performance of the YOLOv5s model was improved by using the mish activation function, the stochastic gradient descent (SGD) optimizer function and the completed intersection over union (CIoU) loss function. Also, the accuracy and training time of the YOLOv5s model increased with the number of epochs. Therefore, the YOLOv5s model is suitable for brain hemorrhage detection using brain CT images, and the performance of the model can be maximized by using appropriate hyperparameters.

• Journal of Korean Library and Information Science Society
• /
• v.53 no.3
• /
• pp.263-285
• /
• 2022

This study presented the factor analysis on constructing the new factors affecting the middle school students' online learning behaviors from the questionnaires employed among middle school students. A total of 204 students participated and the data were collected in South Korea. The sample of middle school ninth-grade students was selected and used through purposive sampling. Findings from the factor analysis provided evidence for the eight-factor solution for the 35-items accounting for 66.15% of the shared variance. A wide range of factors has been considered to identify students' online learning behaviors. The appropriate experience and use of e-learning in the middle school period is also important as it will be a critical stepstone for future education. This research provides information that has been taken into account for advancing online learning to enhance the quality of e-learning systems for middle school students. The study results provided eight new factors affecting the middle school students' online learning behaviors; that is 1) communication using social media as a learning tool, 2) intention to share information using ICT, 3) addiction of technology, 4) adoption of technology, 5) seeking information using ICT, 6) use of social media learning, 7) information search using ICT, and 8) immersion of technology. This study confirmed that middle school students prefer communication using social media as a learning tool, and value intention to share information using ICT for the most part. The data obtained based on factor analysis can highlight the online learning behaviors towards a mixture of social media learning and ICT to ensure a new educational platform for the future of e-learning. This research expects to be useful for both middle schools of online learning to better understand students' online learning behaviors and design online learning environments and information professionals to better assist students who particularly need digital literacy.