• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.193-201
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• 2023

With the end of global COVID-19 epidemic, hospital staff are likely to be "physically and mentally exhausted" after three years of grueling work in the fight against the epidemic. At this point, it is especially important to enable them to continue to maintain their previous proactive work behavior. This study focuses on 400 employees of various types in three-A grade hospitals in Zhanjiang, Guangdong Province, through the proactive motivation model. Statistical software SPSS 25.0 and AOMS 22.0 were used to analyze the survey data to test whether role modeling in hospital management can have an impact on employees' proactive behaviors, in addition to verifying the mediating role of transactional psychological contract. The results of this study show that: First, role modeling of hospital leaders has a positive effect on employees' proactive behavior and a negative effect on their transactional psychological contract; Second, transactional psychological contract has a negative effect on employees' proactive behavior; Third, the transactional psychological contract mediates the effect between role modeling of leaders and employees' proactive behavior. The results of this research add to the F-path of proactive motivation model, and provide enlightenments and implications for hospital management.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.25 no.5
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• pp.422-431
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• 2022

Purpose: At the beginning of the Coronavirus disease (COVID-19) epidemic, physicians paid close attention to children with chronic diseases to prevent transmission or a severe course of infection. We aimed to measure the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody levels in children with chronic gastrointestinal and liver diseases to analyze the risk factors for infection and its interaction with their primary disease. Methods: This cross-sectional study analyzed SARS-CoV-2 antibody levels in patients with gastrointestinal and liver diseases (n=141) and in healthy children (n=48) between January and February 2021. Results: During the pandemic, 10 patients (7%) and 1 child (2%) had confirmed COVID-19 infection (p=0.2). The SARS-CoV-2 antibody test was positive in 36 patients (25.5%) and 11 children (22.9%) (p=0.7). SARS-CoV-2 antibody positivity was found in 20.4%, 26.6%, 33.3%, and 33.3% of patients with chronic liver diseases, chronic gastrointestinal tract diseases, cystic fibrosis, and liver transplantation recipients, respectively (p>0.05, patients vs. healthy children). Risk factors for SARS-CoV-2 antibody positivity were COVID-19-related symptoms (47.2% vs. 14.2%, p=0.00004) and close contact with SARS-CoV-2 polymerase chain reaction-positive patients (69.4% vs. 9%, p<0.00001). The use, number, and type of immunosuppressants and primary diagnosis were not associated with SARS-CoV-2 antibody positivity. The frequency of disease activation/flare was not significant in patients with (8.3%) or without (14.2%) antibody positivity (p=0.35). Conclusion: SARS-CoV-2 antibodies in children with chronic gastrointestinal and liver diseases are similar to that in healthy children. Close follow-up is important to understand the long-term effects of past COVID-19 infection in these children.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1377-1393
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• 2023

Social media is used for various purposes including entertainment, communication, information search, and voicing their thoughts and concerns about a service, product, or issue. The social media data can be used for information mining and getting insights from it. The World Health Organization has listed COVID-19 as a global epidemic since 2020. People from every aspect of life as well as the entire health system have been severely impacted by this pandemic. Even now, after almost three years of the pandemic declaration, the fear caused by the COVID-19 virus leading to higher depression, stress, and anxiety levels has not been fully overcome. This has also triggered numerous kinds of discussions covering various aspects of the pandemic on the social media platforms. Among these aspects is the part focused on vaccines developed by different countries, their features and the advantages and disadvantages associated with each vaccine. Social media users often share their thoughts about vaccinations and vaccines. This data can be used to determine the popularity levels of vaccines, which can provide the producers with some insight for future decision making about their product. In this article, we used Twitter data for the vaccine popularity detection. We gathered data by scraping tweets about various vaccines from different countries. After that, various machine learning and deep learning models, i.e., naive bayes, decision tree, support vector machines, k-nearest neighbor, and deep neural network are used for sentiment analysis to determine the popularity of each vaccine. The results of experiments show that the proposed deep neural network model outperforms the other models by achieving 97.87% accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1478-1499
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• 2024

Coronavirus disease (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. COVID-19 become an active epidemic disease due to its spread around the globe. The main causes of the spread are through interaction and transmission of the droplets through coughing and sneezing. The spread can be minimized by isolating the susceptible patients. However, it necessitates remote monitoring to check the breathing issues of the patient remotely to minimize the interactions for spread minimization. Thus, in this article, we offer a wearable-IoTs-centered framework for remote monitoring and recognition of the breathing pattern and abnormal breath detection for timely providing the proper oxygen level required. We propose wearable sensors accelerometer and gyroscope-based breathing time-series data acquisition, temporal features extraction, and machine learning algorithms for pattern detection and abnormality identification. The sensors provide the data through Bluetooth and receive it at the server for further processing and recognition. We collect the six breathing patterns from the twenty subjects and each pattern is recorded for about five minutes. We match prediction accuracies of all machine learning models under study (i.e. Random forest, Gradient boosting tree, Decision tree, and K-nearest neighbor. Our results show that normal breathing and Bradypnea are the most correctly recognized breathing patterns. However, in some cases, algorithm recognizes kussmaul well also. Collectively, the classification outcomes of Random Forest and Gradient Boost Trees are better than the other two algorithms.

• Journal of Internet of Things and Convergence
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• v.7 no.2
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• pp.13-19
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• 2021

It is analyzed that the energy pattern is affected by the social matters of the disease trend where the energy consumption has been reduced following the depression of the national economy. The campaign of social distance for the people has been done by voluntary or legally due to the epidemic of the Coronavirus Disease 2019 (COVID-19). Some economic stimulus policies have been done in some countries including the United States, South Korea, and some others. It is shown the susceptible, infectious, and recovered (SIR) modeling applied by system dynamics (SD) where the logical modeling is constructed with S, I, and R. Especially, the I is connected with Society including Population, Race, and Maturity. In addition, Economy and Politics are connected to Income, GDP, Resources, President, Popularity, Ruling Government, and Leadership. The graph shows the big jump on 2020 April when is the starting month of the S value multiplication. This shows the effect of the COVID-19 and its related post-pandemic trend. The trends of OECD and non-OECD are very similar and the effect of the virus hazards causes significantly to the economic depressions.

• Journal of Food Hygiene and Safety
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• v.36 no.5
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• pp.363-375
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• 2021

Trends in the developing era to discover and design peptide-based treatments throughout an epidemic infection scenario such as COVID-19 could progress into a more efficient and low-cost therapeutic environment. However, the weakening of proteolysis is one downside of natural peptide drugs. But, peptidomimetics may help resolve this issue. In this review, peptide and peptide-based drug discovery were summarized to target one key entry mechanism of severe coronavirus pulmonary emboli syndrome (SARS-CoV-2), which encompasses the association of the host angiotensin-converting enzyme-2 (ACE2) receptor and viral spike (S) protein. Furthermore, the benefits of proteins, peptides and other possible actions that have been studied for COVID-19 through new peptide-based treatments are discussed in the review. Lastly, an overview of the peptide-based drug therapy environment is comprised of an evolutionary viewpoint, structural properties, operational thresholds, and an explanation of the therapeutic area.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.1
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• pp.79-91
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• 2022

In this study, the effects of self-efficacy, perceived usefulness, perceived ease of use, and depression on college students' academic persistence in the COVID-19 epidemic and the resulting non-face-to-face education situation were identified as mediating effects on learning satisfaction. In the second semester of 2020, a survey was conducted on students enrolled in a four-year university in Daegu and the data were statistically analyzed. The path coefficient was estimated by the Smart PLS bootstrap method and the significance of the path coefficient was verified. The Sobel Test was conducted to verify the mediating effect of academic continuity intention as a parameter. The research results can be summarized as follows. First, it was found that self-efficacy and perceived usefulness had a significant influence in the relationship with learning satisfaction. Second, the relationship between learning satisfaction and academic continuity intention was found to have a significant influence. Third, depression and ease of use did not show any significant influence in the relationship between learning satisfaction. Finally, a Sobel Test was conducted to verify the mediating effect of academic continuity intention with self-efficacy, usefulness, ease of use, and depression as independent variables and learning satisfaction as parameters. As a result of both regression analyses, it was found that β values decreased, and learning satisfaction had a mediating effect. As a result of this study, it is suggested that research to increase learner satisfaction and develop various contents to increase the effectiveness of education that can increase self-efficacy and perceived usefulness should be conducted in parallel. I think this study can be used as basic data in establishing measures to continue studying for college students in natural disaster situations or psychological crisis situations called COVID-19.

• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.15-21
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• 2021

This paper conducted a feasibility study by applying an Internet of Things and Artificial intelligence-based management system for the elderly living alone in an aging society. The number of single-person families over the age of 50 is expected to increase, and problems such as health, safety, and loneliness may occur due to aging. Therefore, by establishing an IoT-based care system for the elderly living alone, a stable service was developed through securing a rapid response system for the elderly living alone and automatically reporting 119. The participants of the demonstration test were subjects under the jurisdiction of the "Seongnam Senior Complex," and the data collection rate between the IoT sensor and the emergency safety gateway was high. During the demonstration period, as a result of evaluating the satisfaction of the IoT-based care system for the elderly living alone, 90 points were achieved. We are currently in the COVID-19 situation. Therefore, the number of elderly living alone is continuously increasing, and the number of people who cannot benefit from care services will continue to occur. Also, even if the COVID-19 situation is over, the epidemic will happen again. So the care system is essential. The elderly care system developed in this way will provide safety management services based on artificial intelligence-based activity pattern analysis, improving the quality of in-house safety services.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.553-561
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• 2021

Health services in developing countries are increasingly focused on satisfying the needs of customers. During the COVID-19 pandemic, many patients have anxiety when going to hospitals for medical treatment. The pressures brought by the pandemic have overwhelmed the hospital system in Vietnam. This has caused the quality of service at these hospitals to decrease because they have focused on the goal of preventing the spread of the virus. Therefore, hospitals, especially private hospitals, need many solutions to improve the quality of their services. This study evaluated the impact of these factors on hospital service quality, as well as the influence of customer service quality on patient satisfaction. The survey was conducted from January 2021 to September 2021 and data was collected directly from 539 patients at Van Phuc Hospital 1. The results show that 4 factors affect the service quality of the hospital, as well as the service quality affecting patient satisfaction, in which, the strongest impact on the service quality of the hospital is the service attitude and professional capacity of the medical team. In the context of the COVID-19 epidemic, this study implies that if the hospital service is good, the customers' peace of mind and satisfaction will be enhanced.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.149-160
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• 2022

The article considers the peculiarities of developing a marketing strategy for the adaptation of small businesses to quarantine restrictions in the field of commercial entrepreneurship. The importance of reformatting the existing marketing strategy in connection with the change of key conditions of trade activity with the introduction of quarantine restrictions due to the covid19 virus epidemic is substantiated. Quarantine restrictions and the temporary introduction of lockdown in various countries around the world, including Ukraine, have not only caused a crisis for small businesses. But they became a shock therapy and accelerated the digitalization of retail. Trends in digitalization and development of digital infrastructure allow both to adapt the structures of commercial entrepreneurship to the current conditions, and set directions for development in the long run. Particular attention in the article is paid to changing the business model and automation of sales processes based on the introduction of vending. The preconditions and existing experience of vending in Ukraine are analyzed. An outline of the business model of the project for the sale of goods through vending machines has been developed.