Background Uncertainties surrounding the 2019 novel coronavirus (COVID-19) remain a major global health challenge and requires attention. Researchers and medical experts have made remarkable efforts to reduce the number of cases and prevent future outbreaks through vaccines and other measures. However, there is little evidence on how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection entropy can be applied in predicting the possible number of infections and deaths. In addition, more studies on how the COVID-19 infection density contributes to the rise in infections are needed. This study demonstrates how the SARS-COV-2 daily infection entropy can be applied in predicting the number of infections within a given period. In addition, the infection density within a given population attributes to an increase in the number of COVID-19 cases and, consequently, the new variants. Results Using the COVID-19 initial data reported by Johns Hopkins University, World Health Organization (WHO) and Global Initiative on Sharing All Influenza Data (GISAID), the result shows that the original SAR-COV-2 strain has R0<1 with an initial infection growth rate entropy of 9.11 bits for the United States (U.S.). At close proximity, the average infection time for an infected individual to infect others within a susceptible population is approximately 7 minutes. Assuming no vaccines were available, in the U.S., the number of infections could range between 41,220,199 and 82,440,398 in late March 2022 with approximately, 1,211,036 deaths. However, with the available vaccines, nearly 48 Million COVID-19 cases and 706, 437 deaths have been prevented. Conclusion The proposed technique will contribute to the ongoing investigation of the COVID-19 pandemic and a blueprint to address the uncertainties surrounding the pandemic.
Network insecurity has become an increasing problem in the world of computer networks. Technical experts have tried to combat this by improving the technical awareness of the threats and technical solutions involved in Wireless Local Networks (WLAN) through technical reports and policy enforcement. The average users' knowledge and awareness of network security, how they react to the warnings and implement security measures is also very important. Current studies on users' awareness of security policies, whether it has been communicated well enough and how aware WLAN users are to the threats and issues involved are still not fully ascertained. To fill this gap it is important to find out the users basic knowledge of the security measures and policies. In this paper, statistical methods were developed and adopted in other to compare the knowledge of Information Technology (IT) related employees and that of non-technical employees on how aware they are of WLAN security threats and security measures. The techniques the paper has adopted revealed the knowledge gap between non-technical and technical users. This revelation is significant and therefore requiring more efficient methods for creating awareness on WLAN threats and countermeasures among average users.
Over a decade since transparency was introduced as a first-class concept in computing, transparency is still an emerging concept that is quite poorly understood. Also, despite existing research contributions, transparency is yet to be incorporated into the software engineering practice, and the promise it holds remains unfulfilled. Although there is evidence of increasing stakeholders' demand for software and process transparency, the realization of such demand is yet to be fully witnessed within the software engineering practice. There is a need to uncover transparency and how it has so far been conceptualized, operationalized, and challenges faced. We applied a systematic literature review method in search of articles published between January 2006 and March 2022. This study reports a systematic review of the explicit conceptualization and application of transparency in 18 articles out of a total of 162 selected for review. Our study found that transparency remains an under-researched non-functional quality requirement concept, especially as it impacts information and software systems development. Of the 18 articles reviewed, only three studies representing 16.67% conceptualized transparency in software development and focused on the transparency of software artifacts. The remaining 83.33% of studies conceptualized transparency in information systems, focusing on general information and fully functional information systems. Transparency is yet to be fully explored from a theoretical gathering point of view and as a non-functional indicator of software quality hence its slow adoption and incorporation into mainstream software practice. Apart from providing a catalog of transparency factors that stakeholders can use to evaluate transparency achievement, the paper proposed a roadmap to enhance transparency implementation and also provides future research directions.
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