• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.83-88
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• 2022

The purpose of this study is to present an analysis and implications for the metaverse-based virtual real estate transaction service. Through blockchain-based technology and metaverse, the world we live in is expanding naturally. Therefore, changes in the environment and perceptions of market participants are also very important factors. The concept and thinking about the existing asset value change and investment are also changing. This means that you can generate profits through value and investment in intangible assets. The service user aspect is a case of investing in the future value of virtual real estate that if more users participate rather than the present value, the principle of supply and demand will be applied to increase the number of consumers and the price will naturally rise according to the principle of scarcity. The service provider provides a technical platform for the service to directly transact the portion of the virtual area considered of interest directly through the virtual real estate purchase business. As the number of participants increases as well as funds and transaction fees, various revenue models such as advertisements can be discovered and provided. It plays the role of providing jobs and information through new services. As a stakeholder, governments can exploit the emergence of new technologies and products to create people and services and secure economic benefits. Of course, various institutional supports should be provided so that new services can settle in the market while mitigating risk factors. This study is meaningful in that it contributes to the establishment of a domestic metaverse-based environment and related research and is utilized in the study of virtual space real estate services.

• Animal Bioscience
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• v.35 no.2
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• pp.224-235
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• 2022

Objective: Cage rearing has critical implications for the laying duck industry because it is convenient for feeding and management. However, caging stress is a type of chronic stress that induces maladaptation. Environmental stress responses have been extensively studied, but no detailed information is available about the comprehensive changes in plasma metabolites at different stages of caging stress in ducks. We designed this experiment to analyze the effects of caging stress on performance parameters and oxidative stress indexes in ducks. Methods: Liquid chromatography tandem mass spectrometry (LC/MS-MS) was used to determine the changes in metabolites in duck plasma at 5 (CR5), 10 (CR10), and 15 (CR15) days after cage rearing and traditional breeding (TB). The associated pathways of differentially altered metabolites were analyzed using Kyoto encyclopedia of genes and genomes (KEGG) database. Results: The results of this study indicate that caging stress decreased performance parameters, and the plasma total superoxide dismutase levels were increased in the CR10 group compared with the other groups. In addition, 1,431 metabolites were detected. Compared with the TB group, 134, 381, and 190 differentially produced metabolites were identified in the CR5, CR10, and CR15 groups, respectively. The results of principal component analysis (PCA) show that the selected components sufficiently distinguish the TB group and CR10 group. KEGG analysis results revealed that the differentially altered metabolites in duck plasma from the CR5 and TB groups were mainly associated with ovarian steroidogenesis, biosynthesis of unsaturated fatty acids, and phenylalanine metabolism. Conclusion: In this study, the production performance, blood indexes, number of metabolites and PCA were compared to determine effect of the caging stress stage on ducks. We inferred from the experimental results that caging-stressed ducks were in the sensitive phase in the first 5 days after caging, caging for approximately 10 days was an important transition phase, and then the duck continually adapted.

• Journal of Space Technology and Applications
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• v.1 no.1
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• pp.23-32
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• 2021

The high-level Space Situational Awareness (SSA) objective is to provide to the users dependable, accurate and timely information in order to support risk management on orbit and during re-entry and support safe and secure operation of space assets and related services. Therefore the risk assessment for the re-entry of space objects should be managed nationally. In this research, the Software for Re-Entry Prediction of space objects (SREP) was developed for national SSA system. In particular, the rate of change of the drag coefficient is estimated through a newly proposed Drag Scale Factor Estimation (DSFE), and is used for high-precision orbit propagator (HPOP) up to an altitude of 100 km to predict the re-entry time and position of the space object. The effectiveness of this re-entry prediction is shown through the re-entry time window and ground track of space objects falling in real events, Grace-1, Grace-2, Tiangong-1, and Chang Zheng-5B Rocket body. As a result, through analysis 12 hours before the final re-entry time, it is shown that the re-entry time window and crash time can be accurately predicted with an error of less than 20 minutes.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.193-202
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• 2022

The purpose of this study is to propose an effective informatization policy by categorizing consumer groups according to the level of digital divide and identifying the characteristics of each type. For this end, a total of 402 data were collected through an online and on-site surveys targeting consumers with internet experience, and the data were analyzed using the SPSS 26.0 program. As a result of conducting a K-means cluster analysis based on access to, capability, and utilization of digital devices, four consumer groups were categorized: 'device lover', 'proficient user', 'general user', and 'digital alienated'. By consumer type, significant differences were found in demographic characteristics, social capital, perception of the future information society, attitude toward technology as innovativeness, discomfort and familiarity, which are the antecedent variables of the digital divide. Significant differences in digital device satisfaction and intention to use, which are outcome variables of the digital divide, were also confirmed by consumer type. This study is academically and practically valuable in that it proposes customized informatization policies for each consumer group according to the level of digitization.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.377-388
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• 2022

Metaverse, realistic virtual space technology has become a hot topic. However, due to the lack of an institutional system to the metaverse environment, concerns are rising over the leakage of industrial confidentiality, including digital assets produced, stored, processed, and transferred within the metaverse. Digital forensics, a technology to defend against hacking attacks in cyberspace, cannot be used in metaverse space, and there is no basis for calculating the extent of damage and tracking responsibility, making it difficult to respond to human resources leakage and cyberhacking effectively. In this paper, we define the scope of industrial confidentiality information and leakage scenario and propose policy and institutional measures based on problems in each metaverse scenario. As a result of the study, it was necessary to prepare a standardized law on Extra-territorial search and seizure issues and a system for collecting cryptocurrency evidence to respond to industrial confidentiality leaks in the metaverse. The study expects to contribute to industrial technology development by preparing in advance for problems that may arise in metaverse technology.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.209-215
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• 2022

On the Jeju coast, international cruise ships, passenger ships, and other ships pass frequently, as well as many fishing boats. Thus, there is a high risk of marine accidents and frequent ship collisions. Accordingly, it is urgent to establish a coastal VTS for systematic safety management of ships passing through the coastal waters of Jeju. The purpose of this study was to set the area of the VTS to be newly established. In this study, to calculate the workload of the VTS operators, a formula was proposed that reflects the monitoring workload considering the monitoring frequency and required time for target as well as non-target ships and the workload for ship collision situations. The proposed formula was applied to the newly established VTS area in Jeju. Three control sectors were set up in each VTS center. The average number of workstations per hour was approximately 1, so the division between sectors was appropriate. Thus, it was deduced that there would be no workload for the VTS operators. It is expected that the method proposed in this study can be used as primary data for calculating the appropriate number of workstations for the current VTS, and setting the VTS area for a new coastal VTS in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.217-226
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• 2022

In the view of the application of high-precision spatial information production, UAV (Umanned Aerial Vehicle)-Photogrammetry has a problem in that it lacks specific procedures and detailed regulations for quantitative quality verification methods or certification of captured images. In addition, test tools for UAV image quality assessment use only the GSD (Ground Sample Distance), not MTF (Modulation Transfer Function), which reflects image resolution and contrast at the same time. This fact makes often the quality of UAV image inferior to that of manned aerial image. We performed MTF and GSD analysis simultaneously using a siemens star to confirm the necessity of MTF analysis in UAV image quality assessment. The analyzing results of UAV images taken with different payload and sensors show that there is a big difference in σ_MTF values, representing image resolution and the degree of contrast, but slightly different in GSD. It concluded that the MTF analysis is a more objective and reliable analysis method than just the GSD analysis method, and high-quality drone images can only be obtained when the operator make images after judging the proper selection the sensor performance, image overlaps, and payload type. However, the results of this study are derived from analyzing only images acquired by limited sensors and imaging conditions. It is therefore expected that more objective and reliable results will be obtained if continuous research is conducted by accumulating various experimental data in related fields in the future.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.27-35
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• 2022

The purpose of this study is to analyze the metaverse-related issues in the news big data from an educational perspective, explore their characteristics, and provide implications for the educational applicability of the metaverse and future education. To this end, 41,366 cases of metaverse-related data searched on portal sites were collected, and weight values of all extracted keywords were calculated and ranked using TF-IDF, a representative term weight model, and then word cloud visualization analysis was performed. In addition, major topics were analyzed using topic modeling(LDA), a sophisticated probability-based text mining technique. As a result of the study, topics such as platform industry, future talent, and extension in technology were derived as core issues of the metaverse from an educational perspective. In addition, as a result of performing secondary data analysis under three key themes of technology, job, and education, it was found that metaverse has issues related to education platform innovation, future job innovation, and future competency innovation in future education. This study is meaningful in that it analyzes a vast amount of news big data in stages to draw issues from an education perspective and provide implications for future education.

• Korean Journal of Community Nutrition
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• v.27 no.3
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• pp.223-244
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• 2022

Objectives: This study was designed to investigate the relationship between metabolic risk factors, Index of Nutrition Quality, and the dietary quality index score of Korean adults. Methods: The subjects were 18,652 Korean adults aged 19 years or older (7,899 males, 10,753 females) who participated in the 2016-2019 Korea National Health and Nutrition Examination Survey. Subjects were divided into normal, pre-metabolic syndrome, and metabolic syndrome (MetS) groups according to the number of their metabolic risk factors. Data were analyzed using the SPSS program. Results: About 44.7% of men in the MetS group were at least college graduates (P < 0.001), whereas 52.0% of women in the MetS group were middle school graduates or lower (P < 0.001). The frequency of fruit and dairy products intake tended to decrease as the number of metabolic risk factors increased in both men and women (P for trend < 0.001). As the number of metabolic risk factors decreased, the frequency of grain intake tended to decrease in men (P for trend < 0.001) while the frequency of intake of red meat (P for trend = 0.001), poultry (P for trend < 0.001), and eggs (P for trend < 0.001) decreased in women. The total scores of Diet Quality Index-International (DQI-I) (men P < 0.001, women P < 0.01) and Korean Healthy Eating Index (KHEI) (men and women P < 0.001) were significantly lower in the MetS group compared to the other groups, and the total score of DQI-I and KHEI tended to decrease as the number of metabolic risk factors increased. Conclusions: Dietary quality evaluation using various indices can provide more information on the dietary problems related to metabolic risk factors. Nutrients and foods that have been confirmed to be related to metabolic risk factors can be used to develop dietary guidelines for the nutritional management of metabolic diseases.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.457-468
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• 2022

In aged society, it is important to prevent older people from being disability needing long-term care. The purpose of this study is to develop a prediction model to discover high-risk groups who are likely to be beneficiaries of Long-Term Care Insurance. This study is a retrospective study using database of National Health Insurance Service (NHIS) collected in the past of the study subjects. The study subjects are 7,724,101, the population over 65 years of age registered for medical insurance. To develop the prediction model, we used logistic regression, decision tree, random forest, and multi-layer perceptron neural network. Finally, random forest was selected as the prediction model based on the performances of models obtained through internal and external validation. Random forest could predict about 90% of the older people in need of long-term care using DB without any information from the assessment of eligibility for long-term care. The findings might be useful in evidencebased health management for prevention services and can contribute to preemptively discovering those who need preventive services in older people.