ABSTRACT
The increased demand for this form of food delivery has been expected to drastically alter restaurant patrons' dining habits. As people have been forced to stay indoors to prevent the virus from spreading, food delivery services over the internet are in high demand. As established in this study, the planned ideal is a good executive implementation for online meal delivery services. Food delivery services are rapidly growing in India, opening up several opportunities for a wide range of online food delivery (OFD) platforms while also generating a competitive commercial sector. Following that, the fuzzy technique for order performance by similarity to ideal solution method (FTOPSIS) is used to rank online food delivery (OFD) enterprises based on the characteristics chosen. In this paper, we study the present multi-criteria decision-analysis (MCDA) paradigm based on the fuzzy analytic hierarchy process (FAHP) and the fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) method to achieve the goal. After that, a hierarchy multiple criteria decision-analysis (MCDA) model based on fuzzy sets theory is introduced to deal with the online food delivery Service in the chain system. The fuzzy analytic hierarchy process (FAHP) is a fuzzy set theory technique for generating criteria weights, which are then used to interpret expert phonological evaluation statements.
ABSTRACT
In light of current trends in virology, we performed social media analysis of 13 main topics in the area of virology and ranked these topics with metrics such as users, posts, engagement, and influence. These metrics were monitored against the 13 keywords on Twitter for the same period (i.e., from 27 November to 6 December 2021) for benchmarking purposes. The 13 main topics were "virological Science", " preventive vaccines", "therapeutic vaccines", "viral pathogenesis", "viral immunology", "antiviral strategies", "virus structure", "virus expression", "viral resistance", "emerging viruses", "interspecies transmission", "viruses and cancer" and " viral diseases". "viral diseases" recorded the highest number of users (i.e., 905 users) and the highest number of post (i.e., about 1K posts). The second-highest number of posts were monitored to be on "therapeutic vaccines" with 729 posts from 691 users. In terms of engagement, "viral diseases" (3.4 K) were found to be on the top followed by "viruses and cancer" (3.1K). Lastly, in terms of influence, "viral diseases" recorded 9.0 million influences followed by 6.6 million influences on "emerging viruses". In summary, "viral diseases" was found to be the most engaging and influential topic highest with the highest number of posts from most of the tweet users. In relation to trending hashtags in virology, #COVID19 recorded the highest number of hashtags, followed by # omicron, #sarscov2, #publichealth, #omicronvarient, #wuhan, #originofcovid, #fauci and #epidemiology. Word clouds showing the main area of discussion were also generated for these 13 main topics.
ABSTRACT
Wearing proper personal protective equipment (PPE) such as N95 mask and goggles is mandatory for healthcare workers who deal with suspected or infected patients. Since the recent COVID19 pandemic, these measures have become mandatory practiced. We aimed to investigate the association between exposure to PPE and the occurrence of new-onset headaches, and its impact on pre-existing headaches. Cross-sectional study was done among healthcare workers who worked in some hospitals in Saudi Arabia during the COVID-19 outbreak.378 healthcare workers participated in the survey. Around 79% of them were aged between 21-30 years old. 47.9% of them were residents, followed by family physicians (14.8%) and nurses (14.3%). Approximately, 24% of the participants had pre-existing headaches, with migraine being the most common (54.5%). N95 face mask was used by 31.7% of the participants an while 43.7% used goggles. Nurses had a higher mean daily exposure time of 9.78 +/- 3.07 compared others (p-value < 0.001). Around 16% of our respondents developed a new onset headache, longer duration of exposure was significantly associated with this type of headache (p-value <0.001), and it occurred more frequently in residents (43.1%). Of those who had prior headaches, 43.2% reported an increase in the frequency, and 36.4% attributed this change to the use of the face mask. 37.5% had an increased need for acute analgesic medication. PPE is associated with the occurrence of new-onset headaches and exacerbation of pre-existing headaches in healthcare workers. Shorter duration of exposure may reduce incidence and severity.
ABSTRACT
In this paper, we discuss the statistical processing of COVID-19 data. COVID-19 was initially recognized in Wuhan, China, on December 31, 2019. It then spread to other parts of the world, so it became known as a pandemic. It has received interest due to its sudden emergence as a deadly human pathogen. The effect is not only confined to morbidity and mortality but also extends to social and economic consequences. Statistical analysis is required to measure the damage done to humans and take the necessary measures to limit this damage. The objective of the work was to examine the effects of various factors on the deaths due to COVID-19. To achieve this goal, we applied a logistic regression (LR) model, as a statistical method, and a decision tree model, as a machine learning method, to model the deaths due to COVID-19 in France, Germany, Italy, and Spain. The predictive abilities of these two models were compared. The overall accuracies of the decision tree and LR were 94.1% and 93.9%, respectively. It was also observed that countries with high population densities tended to have more cases than those with smaller population densities. There were more female deaths than male deaths in the United Kingdom, and more deaths occurred for those aged 65 years and older. The data were collected from the World Health Organization’s official website from January 11, 2020, to May 29, 2020. The results obtained were in agreement with the previous results obtained by others.
ABSTRACT
Automated test generation is an important component in the digital transformation of education. Assessing knowledge using tests is an objective, fast and effective. Electronic tests are effective in verifying knowledge but they also can be used for self-learning. Generating tests by teachers is a laborious and time-consuming process. The development of an automatic test generation system is a key component for adapting education to the ever-changing digital environment. This paper presents a logical approach to assessing student success in the testing process. The approach satisfies the two goals of testing: knowledge testing and self-learning. A process for intelligent transition from one level of complexity of the testing system to another has been developed. This is a new and innovative approach to developing an intelligent automatic test generation system. None of our known training management systems has a self-test module with self-generated questions. The system we developed generates questions independently using templates. The system also navigates students through the different levels of complexity of the content, using the puzzle method and the curiosity function. Adding intelligence to an automated e-test generation system can be a milestone of digital transformation in education and can increase the efficiency of the teaching and learning process during a crisis. Today we are facing the crisis with COVID-19, which affects all areas of work, study and life. Our intelligent approach helps educational institutions to overcome atypical situations like the one we face now. It can also support the universities for a smooth digital transformation and better handling with future atypical situations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The Kingdom of Saudi Arabia (KSA) consists of 26 agencies. Each agency is composed of branches that are spread across the KSA. Some have the authority to strategically attract and hire people. Most agencies and branches do not interchange data with each other. People who want to apply to a university for study or to the public government for work have to enter all of their personal data each time. A government services bus (GSB) is a platform that enables agencies and the associated branches to integrate and interlink in order to share data. Most agencies are unaware of the advantages of GSB. COVID-19 has locked down the world in many aspects. This study aims to identify the purpose of GSB and its advantages in order to raise awareness in the agencies, branches, and communities. A questionnaire was conducted to measure the awareness of GSB. Awareness is an essential factor that allows a government agency to understand why it should interlink with GSB. There are numerous advantages to sharing and interchanging data among agencies and providing e-services to other agencies and citizens. © 2021, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.