ABSTRACT
Introduction: Since the start of pandemic new variants have been evolving and moving from one country to another either by air travel or ground crossings. Objective: To find out factors associated with noncompliance of recommended guidelines by international passengers so that we can improve the arrangements at airports where required, improve future preparedness, and give recommendations to concerned authorities for improvement in enforcing guidelines. Methodology: A cross-sectional study was carried out at Islamabad International Airport during the months of June and July 2021. The study population included international arriving passengers aged 12 years and above. Questions were asked about following guidelines before boarding, on board, and after disembarkation. Twenty questions were asked to assess compliance level. A median cut off value was set for assessment of noncompliance. Results: The male to female ratio was 1:1. The age range was 12 – 75 years. The odds of noncompliance to guidelines were higher in females compared to males. The results revealed a significant association between region of arrival of respondents and noncompliance. Passengers arriving from Afghanistan, the UK and the USA were more likely to be noncompliant to guidelines (p-value = 0.00). There was a significant association between occupation of participants and noncompliance. Housewives and retired were more likely to be noncompliant (p-value = 0.00). A significant association was observed between vaccinated people and noncompliance. Conclusion: Travelers arriving from some specific countries were noncompliant to guidelines. Vaccinated were most noncompliant which indicates still we need to work on awareness and need legislations, fines, or travel restrictions for noncompliant travellers. © 2022 The Author(s).
ABSTRACT
With the development of ICT and its adoption in various domains, it gained remarkable intention in the healthcare sector which introduce the telemedicine term. The coronavirus pandemic has created several challenges for researchers to develop an accurate and fast detection system. In this paper, we present a new telemedicine application to predict Covid-19 using CNN and Fuzzy set techniques. The evaluation of the system indicates high performance with a 98% F1 score, 99% of recall, 98% for precision, and 97% of accuracy. © 2022 IEEE.
ABSTRACT
Like many different and relevant sectors, the leather industry is currently facing a major environmental issue that may affect the competitiveness of all the stakeholders across the value chain. Drawing the conceptual model on the natural resource-based view (NRBV), this study seeks to examine the mediating role of individual green values (IGV) between green transformational leadership (GFTL) and environmental performance (EP). Furthermore, government regulations are used as a moderator concerning the relationship between GTFL and EP. An online survey was randomly distributed to Pakistan's leather industry employees to test the hypothesis by collecting data from 205 respondents. Partial Least Square Structural Equation Modeling (PLS-SEM) has been used to analyze data. The results demonstrate that green transformational leadership (GTFL) positively affects EP. Moreover, this study also reveals that GTFL significantly contributes to developing the IGV that consequently affects EP. Thus, the current study provides a significant sequential GTFL, IGV and EP path. However, surprisingly, the results show that government regulations do not moderate the relationship between GTFL and IGV. This study significantly contributes to the theory and stakeholders and leaders in a vast variety of manufacturing industries. It suggests that all organizations should adopt GTFL principles that encourage employees to engage in environmentally friendly activities by developing green values at the individual level to enhance EP. With this regard, GTLF, IGV, and government regulations may thus play a vital role for organizations and industry for better EP and competitiveness.
ABSTRACT
The present study examines the nexus between exploration, exploitation, quality ambidexterity, and innovation ambidexterity in the Covid-19 pandemic through moderating role of IT Ambidexterity. The data were collected from the faculty and admin staff of universities of Pakistan through an online survey due to the Covid-19 situation. A total number of 280 valid questionnaires were received and utilized for the final analysis. The PLE-SEM technique was employed to analyze the current model. The empirical findings of the study reveal that exploration, quality ambidexterity, exploitation, and IT ambidexterity are significantly and positively associated with innovation ambidexterity. Moreover, the moderating role of IT ambidexterity was also significant between exploitation and innovation ambidexterity. Hence, this study's findings confirm that technology presence and advancement are integral for universities to conduct academic and admin functions. © 2021 IEEE.
ABSTRACT
COVID-19 is among the dangerous illness in the world due to its quickly spreading, posing a new challenge for researchers to discover it early. In last few months, new covid19 virus strains have been found in South Africa, India, and United Kingdom (UK) due to the mutation of the virus. Owing this critical situation of the world health and with increased number of the cases with the absence of efficient a cure vaccine, timely quarantine and medical treatment, as well as reliable identification of COVID-19, are required to prevent and contain this pandemic. Radiology images and Artificial Intelligence techniques are the most used techniques in computer-aided medical diagnosis for Covid-19 detection. The present paper shows a Convolution Neural Network based novel metaheuristic techniques called Marine Predator Algorithm for detecting Covid-19 and well differentiate between Covid-19 and Pneumonia disease. Our proposed system achieves good results in term of classification such as 93% of accuracy, 95% of precision, 97% of recall and F1-score 95%. © 2021 IEEE.