ABSTRACT
[This retracts the article DOI: 10.1007/s00500-021-05643-2.].
ABSTRACT
The entire globe is going through a severe health crisis due to the rapid spread of Covid-19 Disease, which in turn creating a deep impact on the human lives and their day-to-day livelihood. Only hope of preventing it from further spread of disease is by following all the precautionary measures provided by the WHO. One of the most important safety measures is to wear face mask and maintain social distancing. Hence, we have proposed to develop a system can monitor whether a person is wearing a facemask correctly/not in real time. This will help to reduce the rapid spread of the disease in public places and various other organizations. We have proposed a solution that uses Artificial Intelligence and has a capability to detect the violation of wearing a face mask in real-time using Image Recognition and Video Techniques. The main intention of the proposed work is to provide the front-end software (Web or mobile application) for administrators to monitor the violation. The system will capture the violated instance and store the data. Our system will also include a User registration form where the users have to register their information along with their face images. This will be an input to the face recognition model, which will train and alert the user whenever violation occurs. © 2021 IEEE.
ABSTRACT
The World Health Organization (WHO) on December 31, 2019, was informed of several cases of respiratory diseases of unknown origin in the city of Wuhan in the Chinese Province of Hubei, the clinical manifestations of which were similar to those of viral pneumonia and manifested as fever, cough, and shortness of breath. And, the disease caused by the virus is named the new coronavirus disease 2019 and it will be abbreviated as 2019-nCoV and COVID-19. As of January 30, 2020, the WHO classified this epidemic as a global health emergency (Chung et al. in Radiology 295(1):202-207, 2020). It is an international real-life problem. Due to deaths, globally everyone is under fear. Now, it is the responsibility of researchers to give hope to the people. In this article, we aim to better protect people and general pandemic preparedness by predicting the lifetime of the disease-causing virus using three mathematical models. This article deals with a complex real-life problem people face all over the world, an international real-life problem. The main focus is on the USA due to large infection and death due to coronavirus and thereby the life of every individual is uncertain. The death counts of the USA from February 29 to April 22, 2020, are used in this article as a data set. The death counts of the USA are fitted by the solutions of three mathematical models and a solution to an international problem is achieved. Based on the death rate, the lifetime of the coronavirus COVID-19 is predicted as 1464.76 days from February 29, 2020. That is, after March 2024 there will be no death in the USA due to COVID-19 if everyone follows the guidelines of WHO and the advice of healthcare workers. People and government can get prepared for this situation and many lives can be saved. It is the contribution of soft computing. Finally, this article suggests several steps to control the spread and severity of the disease. The research work, the lifetime prediction presented in this article is entirely new and differs from all other articles in the literature.
ABSTRACT
The existing pandemic of COVID-19 has developed an unimaginable, socially hostile climate for citizens. Against the context of this exogenous shock, we analysed the relationship between risk-taking, trait resilience and state anxiety, under which the relationship between trait resilience and risk-taking moderates with state anxiety during the pandemic, and using the principle of combined prospects. In a survey of 515 people in the U.S. we test risk taking by means of a comportment assessed and evaluate trait anxiety, five main characteristics and other demographics. Study of a regression showed that age moderates the correlation between risk and anxiety and that highly resilient, risk-tolerant people have lower anxiety than less resilient people. In the other hand, older people with a higher longevity, are less prone to threats than their younger and least resilient opposites. Studies are minimal and further research is proposed.