ABSTRACT
Owing to the continuous variant of the COVID-19 virus, the present epidemic may persist for a long time, and each breakout displays strongly region/time-dependent characteristics. Predicting each specific burst is the basic task for the corresponding strategies. However, the refinement of prevention and control measures usually means the limitation of the existing records of the evolution of the spread, which leads to a special difficulty in making predictions. Taking into account the interdependence of people' s travel behaviors and the epidemic spreading, we propose a modified logistic model to mimic the COVID-19 epidemic spreading, in order to predict the evolutionary behaviors for a specific bursting in a megacity with limited epidemic related records. It continuously reproduced the COVID-19 infected records in Shanghai, China in the period from March 1 to June 28, 2022. From December 7, 2022 when Mainland China adopted new detailed prevention and control measures, the COVID-19 epidemic broke out nationwide, and the infected people themselves took "ibuprofen” widely to relieve the symptoms of fever. A reasonable assumption is that the total number of searches for the word "ibuprofen” is a good representation of the number of infected people. By using the number of searching for the word "ibuprofen” provided on Baidu, a famous searching platform in Mainland China, we estimate the parameters in the modified logistic model and predict subsequently the epidemic spreading behavior in Shanghai, China starting from December 1, 2022. This situation lasted for 72 days. The number of the infected people increased exponentially in the period from the beginning to the 24th day, reached a summit on the 31st day, and decreased exponentially in the period from the 38th day to the end. Within the two weeks centered at the summit, the increasing and decreasing speeds are both significantly small, but the increased number of infected people each day was significantly large. The characteristic for this prediction matches very well with that for the number of metro passengers in Shanghai. It is suggested that the relevant departments should establish a monitoring system composed of some communities, hospitals, etc. according to the sampling principle in statistics to provide reliable prediction records for researchers. © 2023 Chinese Physical Society.
ABSTRACT
Contemporarily, COVID-19 shows a sign of recurrence in Mainland China. To better understand the situation, this paper investigates the growth pattern of COVID-19 based on the research of past data through regression models. The proposed work collects the data on COVID-19 in Mainland China from January 21st, 2020, to April 30th, 2020, including confirmed, recovered, and death cases. Based on polynomial regression and support vector machine regressor, it predicts the further trend of COVID-19. The paper uses root mean squared error to evaluate the performance of both models and concludes that there is no best model due to the high frequency of daily changes. According to the analysis, support vector machine regressors fit the growth of COVID-19 confirmed case better than polynomial regression does. The best solution is to utilize different types of models to generate a range of prediction result. These results shed light on guiding further exploration of the growth of COVID-19. © 2023 SPIE.
ABSTRACT
The 2022 IEEE Microwave Theory and Technology Society (MTT-S) International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP 2022) was held in Guangzhou, China, 12-14 December 2022 (see Figure 1). Due to the continuous impact of COVID-19 pandemic, small-size, on-site opening and closing ceremonies were organized in Guangzhou, while all the conference sessions were held online. The special Women in Microwaves (WiM) and Wireless session sponsored by the WiM subcommittee under the IEEE Membership and Geographical Activities of the MTT-S AdCom, was held in the afternoon of 13 December. More than 60 people attended this event, including three invited speakers from Austria, Japan, and Mainland China;six panelists from Mainland China, and some other professionals and graduate students from industries and universities (see Figure 2). © 2000-2012 IEEE.
ABSTRACT
Based on a systematical discussion of the logical relationship between social mentality as a psychological basis of social actions and institutions and social governance, and the online emotion as the core element of the dynamic tendency of internet-based social mentality to form emotional energy to promote the operation of the internet society, this paper conducts an empirical study on the online social mentality and public sentiment guidance during the COVID-19 epidemic in mainland China. We use more than 1 million Weibo dynamic data of 104 accounts of three different types including official media, self-media, and big V media and conduct emotional calculation and judgment to address our objectives. The results show that the public sentiment presented by Weibo as the carrier is mainly positive, among which the official media play a positive role in guiding emotions, while the role played by big Vs' is limited during the COVID-19 epidemic. There exists different public sentiment stemmed from the regional differences brought by the heterogeneity of social governance, economic and social development beyond the media guidance. The study provides valuable internet governance experience on how the government can guide the public to respond to and deal with the crisis with a positive attitude when major public health emergencies occur in the future. © 2022 IEEE.
ABSTRACT
Since the outbreak of the COVID-19 pandemic early in 2020, it had versed the learning mode of offline into online teaching and learning in many parts of the world, while students from different cultural backgrounds may have different perceptions and responses toward online learning. Students' engagement, particularly the emotional dimension is discussed in this study to evaluate different students' perceptions about online learning to represent how culture impact on students' online learning by using Bamberg (1997)'s narrative analysis. 48 interviews were held and 2 interviews of their participants from Macau and Mainland China were particularly picked out to represent how students from different cultural backgrounds are going to position themselves in the discourse of online learning engagement with the involvement of online technologies. Through this study, it was found that students from the high-context cultural learning background (Macau) would hold a more positive attitude with online learning activities compared to students from the low-context learning context, position themselves as relaxed online capabilities. While students from a relatively low-context cultural background (Mainland China) eager to pursue high-efficiency of learning, with a negative attitude towards online learning, position themselves as positive efficiency seekers, underestimate the high-ambiguity and low-efficiency of online learning. Hence, after the rough understanding of students' different perceptions of online learning from different cultural backgrounds, this study further proved the influence of different cultures on learning engagement and provided some implications from different perspectives for pedagogical implementation and instructors to improve online curriculum design. © 2022 ACM.
ABSTRACT
The coronavirus sickness (COVID-19) is a worldwide pandemic that was detected in December 2019 by a Chinese physician in Wuhan, Hubei Province, mainland China. There is presently no licensed human vaccine to combat it. When individuals are close together, COVID-19 spreads more fast. As a consequence, travel constraints are in place to minimize the disease from spreading, and regular Washing the hands is encouraged so that the infections that occur due to the virus. Other indications and symptoms include chest discomfort, sputum production, and a sore throat. COVID19 could lead to a very dangerous disease which is pneumonia which occurs due to the virus. When employing CT scans or Xrays to identify the symptoms that are occuring due to the cause of covid-19 in the last region of the lungs then the accuracy is better than when utilizing RT-PCR. But as there are very less radiologists as compared to the new residents or the people that have come and aslo there has been seen many re examinations occurring of these patients. To solve this kind of the issues or problems that is limiting the CT scans and the x-rays the speed of this procedure must be boosted. This may be done by adding artificial intelligence (AI) approaches into contemporary diagnostic systems. The main motive of the paper is to provide the best accuracy to detect the disease using CNN along with a comparison with the transfer learning approach. © 2022 IEEE.
ABSTRACT
This study investigates the comments posted in two popular channels on YouTube (February to July 2020) that reveal Macau people’s concerns and feelings under the COVID-19 pandemic in terms of the themes elaborated and sentiments expressed. By themes, Macau people showed their concerns on the epidemic situation, economy, the problems it caused, and how the government reacted to the epidemic. In addition, the theme on Mainland China evolved around whether the Central Government would help Macau carry through this pandemic. Moreover, the sentiment results represent Macau people’s worries and uncertainty towards the pandemic. Our study casts light on understanding the living condition of people being confronted with the epidemic in terms of their linguistic behaviour. © 2022, Springer Nature Switzerland AG.
ABSTRACT
Hosting weddings, graduation dinners, teacher appreciation banquets, family banquets and other activities at hotels are very popular in mainland China, the income of banquets and weddings has been considered as a major revenue generator for the hotels. With the high demand for weddings, Yixing Hotel opened three new banquet halls in 2018 and started to use outsourcing employees to assist in serving wedding banquets. This study collected the history data of hotel internal employee surveys and wedding customer surveys to identify the impact of wedding banquet labor outsourcing on customers and internal employees in terms of happiness and satisfaction. The primary data was conducted monthly from October 2018 to March 2021 through SINOTRUST, a consulting company. From February to April of 2020 were not considered in the analysis because these three months had no wedding banquet due to the COVID-19 pandemic. Therefore, a total amount of 26 cases were sorted out in the sample. To test the hypotheses, this study used the classic linear regression model and empirical model and conducted the factor analysis and the regression analysis. The results of this study identified that outsourcing activities affected the happiness and satisfaction of wedding banquet customers;the outsourcing activity has a negative effect on internal employees' happiness and job satisfaction through three dimensions-colleague relationships, job security, and reasonableness of work assignments. Through the case study, the managerial implications and theoretical implications are provided to Yixing and similar-Type hotels regarding the aforementioned dimensions. © 2021 IEEE.
ABSTRACT
Development in the field of Machine Learning and Artificial Intelligence are greatly simplifying the critical bio-medical engineering applications. The first outbreak of Covid’19 pandemic was observed in Mainland China and soon it spread over to remaining 214 countries. World Health Organization (WHO) came to forefront and named it as Corona Virus Disease 2019. This highly contagious disease causes serious impact due to Severe Acute Respiratory Syndrome (SARS)-COV Virus. In this article, we are about to disclose the detailed literature survey around how Machine Learning and Artificial Intelligence are momentously assisting the biomedical engineering segment to tackle with the situation created due to Covid’19 Pandemic. Subsequently, different classifiers, which are used by the researchers for effective diagnosis of Covid’19 infection, are studied for projecting the research in effective diagnosis of different strains of the Corona Virus. © 2021 IEEE.