• Journal of Digital Convergence
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• v.20 no.5
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• pp.179-185
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• 2022

The purpose of this study is to provide new implications for the development and operation of programs and comparative studies in university policy by examining how core competencies of university students participating in tutoring programs affect learning satisfaction. For this purpose, 33 university students participated in the tutoring program before COVID-19 and 72 university students participated in the tutoring program after COVID-19 were surveyed and statistically processed. As a result, first, there was a positive correlation between self-innovation, challenge, communication, harmony, sincerity, problem solving and learning satisfaction among the components of core competencies of H university before COVID-19. There was a positive correlation between self-innovation, challenge, communication, harmony, sincerity, problem solving and learning satisfaction of core competencies after COVID-19. Second, in the pre-COVID-19 period, core competence had a high explanatory power on learning satisfaction, but there was no statistically significant factor in each of the remaining components except for the challenge. After COVID-19, core competence was secured with a high rate of explanatory power, self-innovation and harmony among the components of core competence were found to have a positive effect on learning satisfaction, and challenge was found to have a negative effect on learning satisfaction. The implications of this study are that when students participate in the tutoring program, it is necessary to emphasize the challenge factors and when they proceed in non-face-to-face, it is necessary to emphasize the self-innovation factors or the harmony factors rather than the challenge factors.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.11-17
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• 2022

In this paper, a model that can increase the efficiency of work in arranging interior furniture by applying augmented reality technology was studied. In the existing system to which augmented reality is currently applied, there is a problem in that information is limitedly provided depending on the size and nature of the company's product when outputting the image of furniture. To solve this problem, this paper presents an AR labeling algorithm. The AR labeling algorithm extracts feature points from the captured images and builds a database including indoor location information. A method of detecting and learning the location data of furniture in an indoor space was adopted using the CNN technique. Through the learned result, it is confirmed that the error between the indoor location and the location shown by learning can be significantly reduced. In addition, a study was conducted to allow users to easily place desired furniture through augmented reality by receiving detailed information about furniture along with accurate image extraction of furniture. As a result of the study, the accuracy and loss rate of the model were found to be 99% and 0.026, indicating the significance of this study by securing reliability. The results of this study are expected to satisfy consumers' satisfaction and purchase desires by accurately arranging desired furniture indoors through the design and implementation of AR labels.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.541-546
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• 2022

This study is to analyze the effect of rapid rise in the rescue activity of suffering on the increase of reactive oxygen species. There is no study that tested the change rate of reactive oxygen species according to the rapid rise in 119 rescue workers, so we want to check the symptoms that appear in rescue workers' bodies. There were 5 subjects, and B, C, and E showed similar values before and after diving: 0.41µmol/L, 0.11µmol/L, and 0.87µmol/L, respectively. However, in subject D, the level of active oxygen rise before and after diving was significantly higher at 1.41µmol/L, which is believed to be due to increased anxiety caused by poor underwater visibility and increased fatigue during rapid ascent after underwater rescue activities. Subject A showed a significantly low increase in active oxygen before and after diving at 0.07µmol/L. The reason seems to be that A is 54 years old and has the most diving experience among the test subjects, and it seems that it is the result of receiving less stress from the poor watch due to the abundant experience of rescue activities as a 119 rescue worker and the skillful underwater activities. Fatigue and anxiety were both high at 4. It is thought that the psychological tension during underwater activities increased fatigue, and the turbidity of the underwater vision raised anxiet.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.159-165
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• 2023

While the frequency of seismic occurrence has been increasing recently, the domestic seismic response system is weak, the objective of this research is to compare and analyze the seismic vulnerability of buildings using statistical analysis and machine learning techniques. As the result of using statistical technique, the prediction accuracy of the developed model through the optimal scaling method showed about 87%. As the result of using machine learning technique, because the accuracy of Random Forest method is 94% in case of Train Set, 76.7% in case of Test Set, which is the highest accuracy among the 4 analyzed methods, Random Forest method was finally chosen. Therefore, Random Forest method was derived as the final machine learning technique. Accordingly, the statistical analysis technique showed higher accuracy of about 87%, whereas the machine learning technique showed the accuracy of about 76.7%. As the final result, among the 22,296 analyzed building data, the seismic vulnerabilities of 1,627(0.1%) buildings are expected as more dangerous when the statistical analysis technique is used, 10,146(49%) buildings showed the same rate, and the remaining 10,523(50%) buildings are expected as more dangerous when the machine learning technique is used. As the comparison of the results of using advanced machine learning techniques in addition to the existing statistical analysis techniques, in spatial analysis decisions, it is hoped that this research results help to prepare more reliable seismic countermeasures.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.23-37
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• 2022

Based on the service scenario proposed by the existing Kim Tae-wan (2018) who can safely evacuate inmates with the help of a mobile application linked to a fire detection system in the event of a fire, the final purpose of this study is to develop the scenario by incorporating more realistic scenarios with mobile stimuli that can help them escape or act through the Delph In addition, to make the scenarios produced more realistic considering the structure and copper lines of a typical building, expert scenario verification and Delphi technique were applied to exclude unnecessary or impractical aspects of the existing scenarios. The results of the second Delphi survey showed that the primary psychology that could be seen at the time of the fire alarm were doubts, safety concerns and alarm, and the results of the second Delphi survey were analyzed, and the satisfaction of the content adequacy (CVR), convergence, and consensus was derived. Finally, this was applied to create a scenario in which a mobile application was assisted to evacuate the fire response phase. This study will allow the use of methods to increase the evacuation rate of those who are in the event of a fire.

• Food Science of Animal Resources
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• v.43 no.3
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• pp.402-411
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• 2023

This study was conducted to investigate the bactericidal effect of nisin (Nisin) only, atmospheric pressure plasma (APP) only, and a combination of APP and nisin (APP+Nisin)(APP+Nisin) on beef jerky and sliced ham inoculated with Escherichia coli O157:H7, gram-negative bacteria. The bactericidal effect against E. coli O157:H7 and Listeria monocytogenes was confirmed using a nisin solution at a concentration of 0-100 ppm, and APP+Nisin was tested on beef jerky and sliced ham using 100 ppm nisin. Beef jerky and sliced ham were treated with APP for 5 min and 9 min, respectively. In the bacterial solution, 100 ppm nisin out of 0-100 ppm nisin exhibited the highest bactericidal activity against L. monocytogenes (gram-positive bacteria; p<0.05); however, it did not exhibit bactericidal effects against E. coli O157:H7 (gram-negative bacteria). The APP+Nisin APP+Nisin exhibited a 100% reduction rate in both E. coli O157:H7 and L. monocytogenes compared to the control group, and was more effective than the Nisin. The APP+Nisin decreased the number of colonies formed by 0.80 and 1.96 Log CFU/g for beef jerky and sliced ham, respectively, compared to the control, and exhibited a higher bactericidal effect compared to the Nisin (p<0.05). These results demonstrate the synergistic bactericidal effect of APP and nisin, providing a possible method to improve the limitations of nisin against gram-negative bacteria. In addition, this technology has the potential to be applied to various meats and meat products to control surface microorganisms.

• Korean Journal of Community Nutrition
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• v.27 no.6
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• pp.492-502
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• 2022

Objectives: This study examines the foodservice status of kindergartens attached to elementary schools in Seoul. We further determine the perception of elementary school principals and kindergarten assistant principals on the foodservice management for kindergartens. Methods: This survey was conducted from July 17 to 23, 2019, enrolling 207 kindergartens attached to elementary schools in Seoul. Questionnaires were sent to principals of elementary schools and assistant principals of kindergartens, and the data obtained from 89 kindergartens were included in the analysis. The questionnaire consisted of four parts: general information on subjects, foodservice management status, foodservice management status during elementary school vacations, and the perception of principals of elementary schools and assistant principals of kindergartens on foodservice management. Data are presented as frequency and percentage or mean and standard deviation. Statistical comparison between principals of elementary schools and assistant principals of kindergartens was conducted by paired t-test, chi-square test, and Pearson's correlation analysis. Results: A separate menu (10.1%) or recipe (20.2%) that considers preschooler characteristics was rarely used for foodservice at kindergartens attached to elementary schools. Most kindergartens did not have a separate dining space (3.4%) or a dedicated cook (93.3%). Although most kindergartens (92.1%) had operational foodservice during elementary school vacations, non-professional staff and non-nutrition teacher were mainly in charge of organizing the menu and purchasing ingredients (34.1% and 41.5%, respectively). The rate of using a contract catering company (28.0%, 23.2%) was also high. Both elementary school principals and assistant principals of kindergartens showed a high perception of the necessity for providing responsibility allowances for nutrition teachers and improving the cooking environment for kindergartens during elementary school vacations. Conclusions: There is a need for policies and administrative support measures to improve the quality of foodservices for kindergartens attached to elementary schools.

• Journal of the Korean Electrochemical Society
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• v.26 no.3
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• pp.35-41
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• 2023

The carbon-coated silicon monoxide (c-SiO_x), which is a negative electrode active material for lithium-ion batteries (LIBs), has a limited cycle performance due to severe volume changes during cycles, despite its high specific capacity. In particular, the significant volume change of the active material can deform the electrode structure and easily damage the electron transfer pathway. To improve performance and mitigate electrode damage caused by volume changes, we replaced parts of the carbon black conducting agent with carbon nanotubes (CNTs) having a linear shape. The content of the entire conductive material in the electrode was fixed at 10% by mass, and the relative content of CNTs ranged from 0% to 25% by mass to prepare electrodes and evaluate electrochemical performance. As the CNT content in the electrode increased, both cycle life and rate capability improved. Even a small amount of CNT can significantly improve the electrochemical performance of a c-SiO_x negative electrode with large volume changes. Furthermore, dispersing CNTs effectively can lead to achieving the equivalent performance with a reduced quantity of CNTs.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.665-672
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• 2023

Purpose: Underground utility tunnel is facility that is jointly house infrastructure such as electricity, water and gas in city, causing condensation problems due to lack of airflow. This paper aims to prevent electricity leakage fires caused by condensation by detecting whether the control panel door in the underground utility tunnel is open using a deep learning model. Method: YOLO, a deep learning object recognition model, is trained to recognize the opening and closing of the control panel door using video data taken by a robot patrolling the underground utility tunnel. To improve the recognition rate, image augmentation is used. Result: Among the image enhancement techniques, we compared the performance of the YOLO model trained using mosaic with that of the YOLO model without mosaic, and found that the mosaic technique performed better. The mAP for all classes were 0.994, which is high evaluation result. Conclusion: It was able to detect the control panel even when there were lights off or other objects in the underground cavity. This allows you to effectively manage the underground utility tunnel and prevent disasters.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.8
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• pp.253-262
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• 2023

E-voting is a concept that includes actions such as kiosk voting at a designated place and internet voting at an unspecified place, and has emerged to alleviate the problem of consuming a lot of resources and costs when conducting offline voting. Using E-voting has many advantages over existing voting systems, such as increased efficiency in voting and ballot counting, reduced costs, increased voting rate, and reduced errors. However, centralized E-voting has not received attention in public elections and voting on corporate agendas because the results of voting cannot be trusted due to concerns about data forgery and modulation and hacking by others. In order to solve this problem, recently, by designing an E-voting system using blockchain, research has been actively conducted to supplement concepts lacking in existing E-voting, such as increasing the reliability of voting information and securing transparency. In this paper, we proposed an electronic voting system that introduced hybrid blockchain that uses public and private blockchains in convergence. A hybrid blockchain can solve the problem of slow transaction processing speed, expensive fee by using a private blockchain, and can supplement for the lack of transparency and data integrity of transactions through a public blockchain. In addition, the proposed system is implemented as BaaS to ensure the ease of type conversion and scalability of blockchain and to provide powerful computing power. BaaS is an abbreviation of Blockchain as a Service, which is one of the cloud computing technologies and means a service that provides a blockchain platform ans software through the internet. In this paper, in order to evaluate the feasibility, the proposed system and domestic and foreign electronic voting-related studies are compared and analyzed in terms of blockchain type, anonymity, verification process, smart contract, performance, and scalability.