• Journal of Trauma and Injury
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• v.34 no.4
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• pp.233-241
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• 2021

Purpose: The medical community has been heavily impacted by the coronavirus disease 2019 pandemic. The management of facial trauma patients has been affected by the patient capacity of emergency rooms. In this study, we share our experiences of facial trauma management during the social lockdown period and investigate the epidemiological changes in facial bone fractures. Methods: A total of 997 patients who presented to Ajou University Hospital Emergency Center and were evaluated by plastic or maxillofacial surgeons for facial trauma were included in this retrospective study. Our study design was a comparative study of two groups: the 2019 group (control) and the 2020 group (the experimental group that experienced social lockdown). Results: The total number of emergency room inpatients reflected the national pandemic trends with three peaks in patient numbers. According to these trends, facial bone fractures had two different low points in August 2020 and December 2020. A comparison of the 2019 and 2020 facial bone fractures did not show a statistically significant difference in the total number of patients. An analysis of the causes of trauma showed that domestic accidents increased in 2020 (30.92%; p<0.001). Among the anatomical sites of facial injury in surgical patients, the frontozygomatic complex fracture increased the most in 2020 (p=0.018). Facial injuries with two separate sites of injury or with three or more involved sites also showed a significant increase in 2020 (p<0.001). Conclusions: We demonstrated that the incidence of facial trauma patients correlated with the incidence of patients presenting to the emergency department and that facial trauma is inextricably related to multi-trauma cases. Domestic accidents and facial trauma with multiple anatomically involved sites are increasing trends that need more attention.

• Journal of Preventive Medicine and Public Health
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• v.57 no.2
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• pp.108-119
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• 2024

Objectives: Abrupt changes in air pollution levels associated with the coronavirus disease 2019 (COVID-19) outbreak present a unique opportunity to evaluate the effects of air pollution on influenza risk, at a time when emission sources were less active and personal hygiene practices were more rigorous. Methods: This time-series study examined the relationship between influenza cases (n=22 874) and air pollutant concentrations from 2018 to 2021, comparing the timeframes before and during the COVID-19 pandemic in and around Thailand's Khon Kaen province. Poisson generalized additive modeling was employed to estimate the relative risk of hospitalization for influenza associated with air pollutant levels. Results: Before the COVID-19 outbreak, both the average daily number of influenza hospitalizations and particulate matter with an aerodynamic diameter of 2.5 ㎛ or less (PM_2.5) concentration exceeded those later observed during the pandemic (p<0.001). In single-pollutant models, a 10 ㎍/m³ increase in PM_2.5 before COVID-19 was significantly associated with increased influenza risk upon exposure to cumulative-day lags, specifically lags 0-5 and 0-6 (p<0.01). After adjustment for co-pollutants, PM_2.5 demonstrated the strongest effects at lags 0 and 4, with elevated risk found across all cumulative-day lags (0-1, 0-2, 0-3, 0-4, 0-5, and 0-6) and significantly greater risk in the winter and summer at lag 0-5 (p<0.01). However, the PM_2.5 level was not significantly associated with influenza risk during the COVID-19 outbreak. Conclusions: Lockdown measures implemented during the COVID-19 pandemic could mitigate the risk of PM_2.5-induced influenza. Effective regulatory actions in the context of COVID-19 may decrease PM_2.5 emissions and improve hygiene practices, thereby reducing influenza hospitalizations.

• Journal of the Korean earth science society
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• v.43 no.2
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• pp.283-302
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• 2022

Despite the nationwide COVID-19 lockdown in China since January 23, 2020, haze days with high PM₁₀ levels of 88-98 ㎍ m^-3 occurred on February 1 and 2, 2020. During these haze days, the East Asian region was affected by a warm and stagnant air mass with positive air temperature anomalies and negative zonal wind anomalies at 850 hPa. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was used to analyze the variation of regional PM₁₀ aerosol transport in Korea due to decreased anthropogenic emissions in East Asia. The base experiment (BASE), which applies the basic anthropogenic emissions in the WRF-Chem model, and the control experiment (CTL) applied by reducing the anthropogenic emission to 50%, were used to assess uncertainty with ground-based PM₁₀ measurements in Korea. The index of agreement (IOA) for the CTL simulation was 0.71, which was higher than that of BASE (0.67). A statistical analysis of the results suggests that anthropogenic emissions were reduced during the COVID-19 lockdown period in China. Furthermore, BASE and CTL applied to zero-out anthropogenic emissions outside Korea (BASE_ZEOK and CTL_ZEOK) were used to analyze the variations of regional PM₁₀ aerosol transport in Korea. Regional PM₁₀ transport in CTL was reduced by only 10-20% compared to BASE. Synthetic weather variables may be another reason for the non-linear response to changes in the contribution of regional transport to PM₁₀ in Korea with the reduction of anthropogenic emissions in East Asia. Although the regional transport contribution of other inorganic aerosols was high in CTL (80-90%), sulfate-nitrate-ammonium (SNA) aerosols showed lower contributions of 0-20%, 30-60%, and 30-60%, respectively. The SNA secondary aerosols, particularly nitrates, presumably declined as the Chinese lockdown induced traffic.

• Health Policy and Management
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• v.30 no.2
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• pp.139-141
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• 2020

Coronavirus disease 2019 (COVID-19) is currently in progress. Although it is difficult to predict the end of currently increasing COVID-19, it is expected to last for a long time. The COVID-19 is making a lot of changes. Due to physical distancing and living distancing, non-contacts such as wearing facial masks, online lectures, online medical services, telecommuting, and telemarketing are becoming common. In the era of post-COVID-19, online and offline will coexist. Many countries following China's lockdown strategy, which is agreed with the World Health Organization, should be changed to Taiwan's facial mask strategy for reducing the economic problems. The prolonging COVID-19 will add to the economic difficulties, and the US-China confrontation will be difficult to rebound the global economy. COVID-19, such as plaque, smallpox, and Spanish influenza, will be a historical momentum. How to respond to the crisis of COVID-19 and post-COVID-19 will determine the future of the world and Korea.

• Journal of Multimedia Information System
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• v.8 no.4
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• pp.251-258
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• 2021

In 2019, a novel coronavirus (COVID-19) outbreak started in China and spread all over the world. The countries went into lockdown and closed their borders to minimize the spread of the virus. Shortage of testing kits and trained clinicians, motivate researchers and computer scientists to look for ways to automatically diagnose the COVID-19 patient using X-ray and ease the burden on the healthcare system. In recent years, multiple frameworks are presented but most of them are trained on a very small dataset which makes clinicians adamant to use it. In this paper, we have presented a lightweight deep learning base automatic COVID-19 detection system. We trained our model on more than 22,000 dataset X-ray samples. The proposed model achieved an overall accuracy of 96.88% with a sensitivity of 91.55%.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.200-206
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• 2021

Fraud in e-commerce transaction increased in the last decade especially with the increasing number of online stores and the lockdown that forced more people to pay for services and groceries online using their credit card. Several machine learning methods were proposed to detect fraudulent transaction. Neural networks showed promising results, but it has some few drawbacks that can be overcome using optimization methods. There are two categories of learning optimization methods, first-order methods which utilizes gradient information to construct the next training iteration whereas, and second-order methods which derivatives use Hessian to calculate the iteration based on the optimization trajectory. There also some training refinements procedures that aims to potentially enhance the original accuracy while possibly reduce the model size. This paper investigate the performance of several NN models in detecting fraud in e-commerce transaction. The backpropagation model which is classified as first learning algorithm achieved the best accuracy 96% among all the models.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.33-38
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• 2022

This study examines the impact of e-learning on the educational level of students with intellectual disabilities from the viewpoint of their teachers. The study sample consisted of seven teachers: two working in primary school, two in middle school, and three in secondary school. The research applied a qualitative approach, using interviews with the participants. The results showed that the following are required for the effective use of e-learning: firstly, appropriate training courses need to be offered to teachers, students, and families and secondly, it is vital students are provided with the appropriate digital devices to maintain contact with their teachers. The study concludes by recommending the development of educational applications and/or programs capable of supporting teachers and students in their use of e-learning.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.319-325
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• 2022

By using the Blackboard (BB) system in the education sector, the educational process for both academics and students is facilitated. Two data resources were used to evaluate the use of the BB system by students of Umm Al-Qura University: statistical reports issued by the university and an online questionnaire. A total of 989 students from all colleges and different programmes provided by the university responded to the questionnaire survey. According to our findings, most students did not use the BB before the pandemic. Therefore, the sudden conversion to the BB system required intensive training courses. After the data analysis, the relationship between the use of the BB system before the pandemic and the problems students faced during the lockdown was revealed. The most critical issues raised by the respondents were: (1) "The voice of the lecturer went on and off during BB collaborate class", (2) "internet connection of the lecturer went on and off during BB collaborate class" and (3) "High possibility of IT problems during exams".

• Electronics and Telecommunications Trends
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• v.38 no.3
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• pp.86-97
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• 2023

The outbreak of the novel coronavirus disease in 2020 caused a global semiconductor supply shortage and disruption in the production of devices such as iPhones owing to China's quarantine lockdown. Thus, Apple is diversifying its production bases from China to countries like India and Vietnam. The company is also accelerating semiconductor development to guarantee a stable supply, reduce design costs, and customize semiconductors with high quality and outstanding specifications for their products to outperform devices that use general-purpose semiconductors. Following the mobile application processor, Apple is releasing world-class semiconductors, such as the M1 and M2 chips that play the role of central processing units.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.413-416
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• 2020

COVID-19(Coronavirus Disease 2019)는 RNA 형 바이러스로써 점막감염(粘膜感染)과 비말전파(飛沫傳播)로 전염되는 급성 호흡기성 질병이다. 2019 년 12 월 중국 후베이 우한에서 처음 감염이 보고된 후 빠르게 글로벌로 확산되었고, 현재 여러 국가와 지역이 Lockdown 상태에 있다. COVID-19 의 치사율은 국가별, 연령별 차이는 있으나 사스(SARS-CoV), 메르스(MERS-CoV) 등과 비교하여 높다고 할 수 없다. 그러나 COVID-19 는 신종 코로나바이러스로써 아직 백신(Vaccine)과 항바이러스제가 개발되지 않았고 다른 질병과 비교하여 빠른 감염 속도때문에 의료 공백, 사회적 혼란, 경제적 손실을 크게 일으키고 있다. 따라서 바이러스의 확산 양상을 데이터 분석을 통하여 예측할 수 있다면 사회·경제적인 폐해를 줄일 수 있어 Bass 모델과 R 패키지를 이용하여 COVID-19 확산 예측 모형을 계량적으로 제시하였다.