• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.508-510
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• 2021

In this study, the difference in resilience was analyzed based on the results of a study of classes that practiced using Raspberry Pi, which had to cross school due to temporarily conducting online classes due to the COVID-19 pandemic. As a result of the study, in online classes, 14 people had resilience less than 150, 32 people who had 150 or more and less than 180, and 9 people who had 180 or more. On the other hand, in the school attendance class, there were 7 people with resilience less than 150, 29 people with resilience less than 150 and less than 180, and 20 people with more than 180. Therefore, in subjects where programming using Raspberry Pi and circuit manufacturing are taught at the same time, the laboratory and practice environment should be able to proceed properly as much as possible. should proceed mainly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.511-513
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• 2021

In this study, digital twin technology and block chain technology are used to provide. A learning method was suggested. The medium used in this study is a 6-axis robot released by Denso, and the operating coordinates of the equipment can be converted into data through the data displayed on each axis. In addition, the results of the practice can be stored in the blockchain to ensure the confidentiality and integrity of the evaluation. The method proposed in this study is expected to be of great help to practical classes in specialized high schools even in the COVID-19 pandemic.

• Journal of the Korean Society of Radiology
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• v.82 no.6
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• pp.1505-1523
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• 2021

Purpose Although chest CT has been discussed as a first-line test for coronavirus disease 2019 (COVID-19), little research has explored the implications of CT exposure in the population. To review chest CT protocols and radiation doses in COVID-19 publications and explore the number needed to diagnose (NND) and the number needed to predict (NNP) if CT is used as a first-line test. Materials and Methods We searched nine highly cited radiology journals to identify studies discussing the CT-based diagnosis of COVID-19 pneumonia. Study-level information on the CT protocol and radiation dose was collected, and the doses were compared with each national diagnostic reference level (DRL). The NND and NNP, which depends on the test positive rate (TPR), were calculated, given a CT sensitivity of 94% (95% confidence interval [CI]: 91%-96%) and specificity of 37% (95% CI: 26%-50%), and applied to the early outbreak in Wuhan, New York, and Italy. Results From 86 studies, the CT protocol and radiation dose were reported in 81 (94.2%) and 17 studies (19.8%), respectively. Low-dose chest CT was used more than twice as often as standard-dose chest CT (39.5% vs.18.6%), while the remaining studies (44.2%) did not provide relevant information. The radiation doses were lower than the national DRLs in 15 of the 17 studies (88.2%) that reported doses. The NND was 3.2 scans (95% CI: 2.2-6.0). The NNPs at TPRs of 50%, 25%, 10%, and 5% were 2.2, 3.6, 8.0, 15.5 scans, respectively. In Wuhan, 35418 (TPR, 58%; 95% CI: 27710-56755) to 44840 (TPR, 38%; 95% CI: 35161-68164) individuals were estimated to have undergone CT examinations to diagnose 17365 patients. During the early surge in New York and Italy, daily NNDs changed up to 5.4 and 10.9 times, respectively, within 10 weeks. Conclusion Low-dose CT protocols were described in less than half of COVID-19 publications, and radiation doses were frequently lacking. The number of populations involved in a first-line diagnostic CT test could vary dynamically according to daily TPR; therefore, caution is required in future planning.

• Journal of Korean Academy of Nursing
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• v.51 no.6
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• pp.703-719
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• 2021

Purpose: We aimed to identify collaborative disaster governance through the demand and supply analysis of resources recognized by nurses during the COVID-19 pandemic. Methods: We used a descriptive study design with an online survey technique for data collection. The survey questions were developed based on focus group interviews with nurses responding to COVID-19 and expert validity testing. A 42-question online survey focusing on disaster governance was sent to nurses working in COVID-19 designated hospitals, public health offices, and schools. A total of 630 nurses participated in the survey. Demand and supply analysis was used to identify the specific components of disaster governance during a pandemic situation and analyze priority areas in disaster governance, as reported by nurses. Results: Demand and supply analysis showed that supplies procurement, cooperation, education, and environment factors clustered in the high demand and supply quadrant while labor condition, advocacy, emotional support, and workload adjustment factors clustered in the high demand but low supply quadrant, indicating a strong need in those areas of disaster governance among nurses. The nurses practicing at the public health offices and schools showed major components of disaster governance plotted in the second quadrant, indicating weak collaborative disaster governance. Conclusion: These findings show that there is an unbalanced distribution among nurses, resulting in major challenges in collaborative disaster governance during COVID-19. In the future and current pandemic, collaborative disaster governance, through improved distribution, will be useful for helping nurses to access more required resources and achieve effective pandemic response.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.183-193
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• 2021

In this paper, the author found and analyzed the problems caused by the change of traditional teaching methods to online in classrooms and laboratories. Looking at the analysis of major problems, first, there were various technical problems, including not all environments and facilities being connected to the Internet. Second, the effectiveness of virtual classes, which were suddenly switched online, could also be questioned. Finally, in the face of a new environment, the stress of teachers to adapt rapidly to the new teaching methodology was a problem. The author proposed digital transformation as a way to address these problems. The author analyzed educational changes, learning modalities and various technical tools, and various tasks to enable digital transformation. First, the author investigated, analyzed, and presented the factors necessary to efficiently operate the classroom environment that will change to online. Next, the author analyzed the factors and problems needed to make the students' classes reliable and efficient, and proposed solutions. Finally, the author pointed out the problem that during online lectures, the responsibility of learning is excessively transferred from teachers to students, and proposed a solution to this problem. Subsequently, the author proposed future studies.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1039-1046
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• 2022

After the COVID-19 pandemic, the spread of the untact culture and the Fourth Industrial Revolution, which generates various types of data, generated so much data that it was not compared to before. This led to higher data throughput, revealing little by little the limitations of the existing network system centered on vendors and hardware. Recently, SDN technology centered on users and software that can overcome these limitations is attracting attention. In addition, SDN-based load balancing techniques are expected to increase efficiency in the load balancing area of the server cluster in the data center, which generates and processes vast and diverse data. Unlike existing SDN load distribution studies, this paper proposes a load distribution technique in which a controller checks the state of a server according to the occurrence of an event rather than periodic confirmation through a monitoring technique and allocates a user's request by weighting it according to a load ratio. As a result of the desired experiment, the proposed technique showed a better equal load balancing effect than the comparison technique, so it is expected to be more effective in a server cluster in a large and packet-flowing data center.