ABSTRACT
COVID-19 is the seventh member of the Coronaviridae family and this virus will spread quickly in humans, birds and other animals. Human infections are the major source of spreading this virus, it causes mainly respiratory and neurological diseases. In the month of December 2019 there were an increased number of patients reported to hospitals in Wuhan, China. They identified this virus as a novel Corona virus, named as COVID-19. Due to this uncontrollable virus two major challenges are faced by mankind. First, abnormal growth of COVID-19 cases is leading to insufficient medical resources and second, emergency protocols (such as lockdowns) are imposed as preventive measures. we provide a preliminary evolutionary graph theory based mathematical model was designed for control and prevention of COVID-19. In the proposed model, well known technique of social distancing with different variations are implemented. Lockdown by many countries leads to the decrease of Gross Domestic Product (GDP) and increase in mental problems in citizens. These two problems can be solved by the administration of anti virus in some form to the public as a counterpart to the virus. This model works more effectively with high percolation of antiviral nodes in a population and over a period of time. © 2022 Scrivener Publishing LLC.
ABSTRACT
Background: COVID 19 created a challenging situation for many of the industries across the globe. Our primary focus is on the most affected airline industry. In this paper, the connectivity and profits of an airline company were analyzed with the theoretical approach and by proposing a novel model to increase the performance of the above parameters. In our previous work, two airlines were investigated, and it was observed that adding trips to a non-profit airline concerning profit Airlines is one of the optimal techniques to improve the performance. In this paper, multi-airlines have been considered. Methods: In the first step, identify the appropriate data sets for three airline companies and the collected data set in image format, to convert them into graph format consisting of nodes and edges. In the next step, an analysis has been conducted on data set graphs by considering the parameters like diameter, density, average degree, clustering coefficient and the shortest path generated to identify the profitable airlines. The proposed algorithms will apply either trimming or adding operations on low-profit airline operators with respective profitable airlines. In the last step, the proposed algorithm will generate an output with better connectivity and profits. Results: In this research, other interesting findings, which are relatively contrasted to the previous findings, were observed. In the present research findings, trimming of trips to non-profit airlines concerning the profit airlines can also be an optimal solution for better performance. Discussion: In this research, complex multigraph airlines were analyzed by using the graph analytics technique for the optimum solution. Standard parameters like edges, nodes, degree, clustering, and shortest path on indigo, spice jet, and AirAsia airline systems were also compared. Conclusion: The proposed algorithm analyzes the connectivity of airline systems and applies either trimming or enhancing techniques. Indigo airlines have the best-connected network as compared to the other two models. Trimming operations will be performed on Indigo, whereas on Air Asia and spice jet, both cutting and enhancing will be served. © 2021 Bentham Science Publishers.