Towards for Designing Educational System Using Role-Based Access Control

During the COVID-19 pandemic, online electronic educational systems have been used in most schools and universities as they were forced to move their operations from classrooms to online settings. However, these systems face a serious security issue. Access control considers the core of data security for any implemented system. This paper presents the well-known role-based access control (RBAC) approach to enhance system security and improve user role and system privilege. This study also addresses the issues faced by extant schemes, such as security risk tolerance, by proposing a privacy-preserving educational system that utilizes RBAC and smart multifactor authentication. This approach uses an asymmetric cryptosystem based on the Elgamal digital signature operation to provide multi-factor authentication while relying on low-complexity cryptographic hash functions. RBAC manages system security via the "user classification, role authorization, and unified management” approach. By limiting the amount of data that users can access, RBAC is particularly suited for multi-level applications. This approach also uses informal analysis and the Scyther tool to conduct extensive formal security proofs. RBAC offers many benefits, including mutual authentication, identity anonymity, forward secrecy, key management, and high resistance to well-known attacks, such as phishing, replay, Man-In-The-Middle (MITM), and insider attacks. Compared with other schemes, RBAC offers more security features and boasts higher cost effectiveness in processing and communication. Furthermore, our work achieves a good balance between performance and security complexity when compared to the state-of-the-art. So, we get good results at a cost of 0.253 ms for computing and 1326 bits for communication © 2023, International Journal of Intelligent Engineering and Systems.All Rights Reserved.

Subacute Rhinovirus Myocarditis Complicating Nonischemic Alcohol-Induced Dilated Cardiomyopathy: Unusual Mixed Etiologies of Biventricular Heart Failure

Background Dilated cardiomyopathy (DCM) is caused by many conditions, including ischemia, genetics, infection, chemotherapy, or idiopathic. Clinical suspicion is needed to identify reversible etiologies. Case A middle-aged truck-driver presents with exertional dyspnea, cough, lower extremity edema, and low-grade fever for 2 weeks. He had 20-pack-year smoking history and 3-4 alcoholic drinks weekly. Chest x-ray showed pulmonary congestion. BNP was elevated. ECHO showed severely dilated ventricles with LVEF < 10% and no wall abnormalities. Decision-making Perfusion stress test showed no inducible ischemia. Coronary angiogram showed no epicardial disease. Cardiac MRI (CMR) showed severely dilated biventricular failure, pericardial thickening, circumferential pericardial effusion, epicardial involvement suggestive of subacute myopericardial inflammation and scarring with delayed gadolinium-enhancement and RVEF < 5%. Liver ultrasound showed no cirrhosis. Viral PCR was positive for rhinovirus, negative COVID-19. He was treated medically requiring inotropes then transferred to heart failure center for assist device evaluation. Conclusion Our patient reported moderate alcohol use, which alone would not explain the myopericardial changes seen on CMR. Given the findings, his DCM was attributed to alcohol complicated by possible subacute rhinovirus myocarditis. Our association is further supported by recent respiratory viral prodrome along with exclusion of other etiologies. [Formula presented]Copyright © 2023 American College of Cardiology Foundation

Secure two-factor mutual authentication scheme using shared image in medical healthcare environment

The cloud healthcare system has become the essential online service during the COVID-19 pandemic. In this type of system, the authorized user may login to a distant server to acquire the service and resources they demand, we need full security procedures that cover criteria such as authentication, privacy, integrity, and availability. The journey of security for any healthcare system starts with the authentication of users based on their privileges. Traditional user authentication mechanisms, such as password and personal identification number (PIN) typing, are vulnerable to malicious attacks like on/offline, insider, replay, guessing, and shoulder surfing. To address these issues, we proposed a secure authentication scheme that uses the authenticated delegating mechanism based on two factors: a one-time password and generating a secure variable vector from a legible user's digital image to enable the permission of a user through the back-end database of a cloud server. The proposed mutual authentication can protect the information against well-known attacks, ensure the user's privacy, and key management. Moreover, comparisons with existing schemes show that the proposed scheme supplies more privacy, security metrics, and resistance to attacks than the others while being more efficient in computation and communication costs. © 2023, Institute of Advanced Engineering and Science. All rights reserved.

Description of a COVID-19 Beta Variant Outbreak, Joint Base Lewis-McChord, WA, February–March 2021

An outbreak of SARS CoV-2 infection occurred in an infantry battalion from Joint Base Lewis-McChord following participation in a field training exercise in the vicinity of Yakima, WA in February of 2021. Extreme weather during the exercise disrupted planned COVID-19 mitigation measures and caused 110 soldiers to be sheltered in a small aircraft hangar for several nights. The probable index case reported to sick call with symptoms compatible with COVID-19, but the soldier was not diagnosed with COVID-19, was returned to duty, and was allowed to remain in the enclosed hangar for 3 additional days. In total, 143 individuals with epidemiologic ties to the field training exercise tested positive for SARS-CoV-2 during the outbreak. Nine samples sent for sequencing were determined to be the SARS-CoV-2 Beta variant. This report illustrates important lessons learned whose implementation in the future will enable better protection of service members from COVID-19 and similar health risks associated with training. © 2022, Armed Forces Health Surveillance Center. All rights reserved.

Design a sturdy and secure authentication scheme capable of early detection of COVID-19 patients using WBANs

COVID-19 was first reported in China Wuhan and rapidly grown up to more than 58 countries based on the World Health Organization (WHO). Well ahead of any health emergency, the health care server has the ability to access these data via authorization and then s/he performs necessary actions. In order to protect medical data from malicious activities, authentication is the starting point for this. Authentication systems represent a network support factor to reduce ineffective users and radically eliminate phishing because authentication determines the identity of the real user. Many schemes and technologies have been suggested for authentication in wireless body area networks (WBANs). In this paper, we suggest a strong dynamic password authentication system for WBANs. We adopt a (different/new) way to calculate a password and make it coherent and dynamic for each login session. Our work also provides additional security properties to get rid of hub node impersonation attacks and resolve key escrow issues. Our scheme resist fishing attach which keep patient from any illegal change of drugs. By comparison, the proposed scheme is considered active and has strong security based on formal security analysis tools such as AVISPA. © 2022 Institute of Advanced Engineering and Science. All rights reserved.

Sentiment analysis system for COVID-19 vaccinations using data of Twitter

COVID-19 vaccination topic has been a hot topic of discussions on social media platforms wondering its effectiveness against the SARS-COV-2 virus. Twitter is one of the social media platforms that people widely lunched to express and share their thoughts about different issues touching their daily life. Though many studies have been undertaken for COVID-19 vaccine sentiment analysis, they are still limited and need to be updated constantly. This paper conducts a system for COVID-19 vaccine sentiment analysis based on data extracted from Twitter platform for the time interval from 1st of January till the 3rd of Sep. 2021, and by using deep learning techniques. The introduced system proposes to develop a model architecture based on a deep bidirectional long short-term memory (LSTM) neural network, to analyze tweets data in the form of positive, neutral, and negative. As a result, the overall accuracy of the developed model based on validation data is 74.92%. The obtained outcomes from the sentiment analysis system on collected tweets-data of COVID-19 vaccine revealed that neutral is the prominent sentiment with a rate of 69.5%, and negative sentiment has less rate of tweets reached 20.75% while the positive sentiment has a lesser rate of tweets reached of 9.67%. © 2022 Institute of Advanced Engineering and Science. All rights reserved.

CT Patterns Among Covid-19 Patients During the Second Wave: A Single Institute Study

Background: The COVID-19 pandemic caused a worldwide dramatic loss of human life. The second wave of coronavirus showed a very rapid spread. Objective: This study aimed to retrospectively analyze the laboratory findings and chest computed tomography (CT) features in patients with suspected coronavirus disease (COVID-19) pneumonia during the second wave. Patients and methods: From November 2020 to February 2021, a total of 295 patients were admitted to our hospital with suspected COVID-19 pneumonia. They underwent multiple laboratory tests including (s. ferritin, CBC) as well as non–contrast CT. Only 144 patients had PCR results available. The CT findings were reported as regards the presence of ground glassing, consolidation and pleural effusion. Results: 198 (67.1%) showed ground glassing and 36.9% (109 cases) had consolidation in their CT. These lesions were bilateral in 181 cases about 63.3% being single in in 71 cases (25.3 %). Pleural effusion was found in 202 cases (68.7%). Significant correlation was found between CRP, s. ferritin and d-dimer with presence of consolidation. Significant decreased neutrophil count and decreased DD among positive in comparison with negative ground glassing. PCR results were available in only 144 out of 295 patients (48.8%). It was positive in 100 out of 144 patients (69.4%) and negative in 44 patients (30.6%). Highly significant relation between COVID-19 Reporting and Data System (CO-RADS) categories & PCR among all studied cases. Conclusion: During the second wave, the CT findings were similar to wave one with PCR proved COVID-19 cases more frequent with higher CO-RADS and RSNA categories. © 2022, Ain Shams University Faculty of Medicine. All rights reserved.

Quantifying the effects of frequently prescribed antimicrobials with perceived potential for qt interval prolongation during the COVID-19 ERA

Background. Countless diseases and medications have been implicated in the past as causing prolongation of the QT interval. Their unique role through the means of quantifying the definite magnitude of relative risk they contribute during hospitalization still requires further investigation. The aim of this study was to describe the impact of commonly used anti-infectives on the QT interval in hospitalized patients during the COVID-19 era. Methods. Demographic information, medical history, laboratory data, medication administration history and ECG recording data was collected from the electronic records of adult patients admitted to two urban hospitals. A mixed effects approach with four sub-models for the QT interval comprised of: heart rate, circadian rhythm, gender, and the drug (regressed as the cumulative mg dose administered over time) and disease effects was used. Fixed and random effects with between occasion variability were estimated for the parameters with a Bayesian approach using the STAN software. Results. Data from 2180 patients were used with baseline characteristics shown in Table 1. Observed vs. predicted plots based on the training (Figure 1.A) and validation data set (Figure 1.B) showed excellent fit. The parameters for QTc0, α, gender, and circadian rhythm were identified within the range previously described (Table 2.). Similarly, the model correctly identified the impact of acute or chronic diseases on the QT interval. Model coefficient estimates [mean (95% CI) of 0.010 (0.006, 0.15) and 0.0045 (0.0013, 0.01100) msec/mg cumulative dose, respectively] suggest that patients treated with conventional regimens of fluconazole and levofloxacin are most likely to present with a QT interval increase > 5 msec, the cutoff threshold of regulatory concern. Figure 1. A-B Table 1. Table 2. Conclusion: The model developed accurately identified the impact baseline risk factors and concomitant medications have on the QT interval. When adjusted for these confounding variables, estimates of QT interval prolongation show that treatment with fluconazole and levofloxacin pose a considerable risk;while treatment with azithromycin or hydroxychloroquine is of moderate risk for QT interval prolongation.

Towards design strong emergency and COVID-19 authentication scheme in VANET

The wide use of vehicular ad hoc networks (VANETs) in the last decade has led many researchers to find efficient and reliable methods to obtain the desired benefits and offer services, such as healthcare and traffic management. However, VANETs suffer from security issues represented by authentication and data integrity. In this paper, we propose a robust mutual authentication scheme based on elliptic curve cryptography (ECC), cryptography Hash Function, and a pseudonym. The proposed work was twofold in focus: First, on healthcare in emergency cars which use VANETs, and second, on overcoming security issues, such as resisting familiar attacks (e.g. insider attacks and reply attacks). Because of the serious situation generated by the worldwide outbreak of the Covid-19 epidemic, we also found this research valuable in supporting global efforts to combat the rapid spread of this virus, by finding the safest and fastest routes to epidemic treatment centres for medical staff, assistance teams in medical operations, fumigation control, and all work teams associated with disease control. This research attempts to contribute by proposing a special signal used to define epidemic teams. The best route, fast route can be chosen by using VANETs infrastructure. This scheme also deals with metric security features, such as key management, data integrity, and data privacy. In the communication and computation cost, we noticed that our proposed scheme achieved good results compared with the related works. © 2021 Institute of Advanced Engineering and Science. All rights reserved.

Psychological impact of the COVID-19 pandemic on local and international students in Malaysian universities

Purpose: This paper aims to investigate the psychological impact of the COVID-19 pandemic on university students in Malaysian universities as well as its effect on their learning. Design/methodology/approach: The study employed a quantitative design, as the data were collected through a survey. The participants were 219 students, divided as follows: 102 local students and 117 international students in Malaysian universities. Findings: The findings showed no significant difference in terms of the psychological impact of COVID-19 among students according to the variables, nationality (local and international), gender and level of study. The descriptive analysis showed that the outbreak of COVID-19 made the students anxious, worried and restless. Besides, the outbreak of COVID-19 made the students unable to focus on their study, feel anxious about studying, have less confidence on their leaning and commit more mistakes than normal days. The psychological stress made online learning during the isolation period less effective and less helpful for students, which made them more worried about their academic achievement and future study plans. Originality/value: COVID-19 is a current issue, and the psychological effect of COVID-19 on local and international students and their learning has not been covered in previous literature. © 2020, Emerald Publishing Limited.

COVID-19 pandemic and the changing paradigms of higher education: A gulf university perspective

With the outbreak of COVID-19 in the month of February 2020, Bahrain government had to enforce distance learning amidst the school and university students and the faculty were directed to work from home. With no formal and intense training, it was completely a fire fighting scenario be it for students or for the faculty members. Thanks to digital tools, supportive IT staff, tech-savvy students, and easy availability of high-speed internet - without which the coping with could have been impossible for the faculty. With this backdrop, this paper intends to spell out the changing paradigms of Gulf University with respect to teaching and learning process during COVID-19 phase and how the faculty members and students have been managing to achieve the objectives of the teaching and learning. © 2020 Asian E F L Journal Press. All rights reserved.

The Effects of Internet Addiction on the Academic Performance of Medical Students at Omdurman Islamic University: An Online Cross-sectional Study (preprint)

Background:In general, the emergence of new technologies such as the internet, social networks and providing opportunities to facilitate and improve global communications quality have created some threats, as Internet Addiction Disorder (IAD), which is an emerging psychological problem across the globe. Young defined it as “an individual’s inability to control his or her use of the internet, which eventually causes psychological, social, school, and/or work difficulties in a person’s life”. Students are among the most critical internet and social networks, particularly during the coronavirus recent pandemic. The prevalence of internet addiction and its association with academic performance among Sudanese medical students has not been discussed yet. Therefore, this study aimed to assess the effects of internet addiction on medical students’ academic performance. Methods:This study was an observational descriptive cross-sectional study conducted on medical students at Omdurman Islamic University in Sudan from 321 sample size by stratified random technique. Data were collected using a questionnaire that contains four sections; the last one is the Internet Addiction Test (IAT), a 20-item scale that measures the presence and severity of internet addiction, developed by Young. Data were analyzed using the statistical package for social science (SPSS) version 24. A P-value < 0.05 was considered statistically significant.Results:Out of 321 medical students, 186 (57.9%) were females, and 135 (42.1%) were males, with no general differences regarding the addiction score. Social media was the leading platform for internet use purposes (88%), mean internet addiction score was 47.7; most of the respondents (55.8%) fit into the moderate-level addiction. There is an association between the duration of internet time consumption and the IAT score, with 5-6 hour/day scoring the highest (mean 50.1 ± 14.3) (P-value 0.001). There is a significant association between platforms that consume most of the participant time and IAT score, with games scoring the highest (IAT mean 56.4 ± 15) (P-value 0.001). There is an insignificant negative correlation between Internet Addiction Test (IAT) grade and CGPA (p-value 0.07).Conclusion:The mean internet addiction score is 47.7, and most of the respondents (55.8%) show moderate-level addiction. The Internet Addiction Test’s application to medical students’ sample concerning the academic performance found no significant association between Internet Addiction Test score and CGPA score.

CT pulmonary angiography in COVID-19 pneumonia: relationship between pulmonary embolism and disease severity

Background: Pulmonary embolism (PE) is one of the known sequels of COVID-19 infection. We aimed to assess the incidence of PE in patients with COVID-19 infection and to evaluate the relationship between the CT severity of the disease and the laboratory indicators. This was a retrospective study conducted on 96 patients with COVID-19 infection proved by positive PCR who underwent CT pulmonary angiography (CTPA) with a calculation of the CT severity of COVID-19 infection. Available patients’ complaint and laboratory data at the time of CTPA were correlated with PE presence and disease severity. Results: Forty patients (41.7%) showed positive PE with the median time for the incidence of PE which was 12 days after onset of the disease. No significant correlation was found between the incidence of PE and the patients’ age, sex, laboratory results, and the CT severity of COVID-19. A statistically significant relation was found between the incidence of PE and the patients’ desaturation, hemoptysis, and chest pain. A highly significant correlation was found between the incidence of PE and the rising in the D-dimer level as well as the progressive CT findings when compared to the previous one. Conclusion: CT progression and the rising in D-dimer level are considered the most important parameters suggesting underlying PE in patients with positive COVID-19 infection which is commonly seen during the second week of infection and alert the use of CT pulmonary angiography to exclude or confirm PE. This is may help in improving the management of COVID-19 infection. © 2020, The Author(s).

Sneezing and asymptomatic virus transmission.

The novel coronavirus disease (COVID-19) spread pattern continues to show that geographical barriers alone cannot contain a virus. Asymptomatic carriers play a critical role in the nature of this virus quickly escalating into a global pandemic. Asymptomatic carriers may transmit the virus unintentionally through sporadic sneezing. A novel Computational Fluid Dynamics (CFD) approach has been proposed with a realistic modeling of a human sneeze achieved by the combination of state-of-the-art experimental and numerical methods. This modeling approach may be suitable for future engineering analyses aimed at reshaping public spaces and common areas, with the main objective to accurately predict the spread of aerosol and droplets that may contain pathogens. This study shows that the biomechanics of a human sneeze, including complex muscle contractions and relaxations, can be accurately modeled by the angular head motion and the dynamic pressure response during sneezing. These have been considered as the human factors and were implemented in the CFD simulation by imposing a momentum source term to the coupled Eulerian-Lagrangian momentum equations. The momentum source was modeled by the measured dynamic pressure response in conjunction with the angular head motion. This approach eliminated the need to create an ad hoc set of inlet boundary conditions. With this proposed technique, it is easier to add multiple fixed and/or moving sources of sneezes in complex computational domains. Additionally, extensive sensitivity analyses based on different environmental conditions were performed, and their impact was described in terms of potential virus spread.