Toward an E-learning adoption: Sustainable technology used

The phenomenon that occurs in universities today is the increase in the use of e-learning during the Covid-19 pandemic. However, the readiness of students and universities is seen as too short. The purpose of this research is to examine the relationship between expected benefits, e-learning curriculum, and educational partners in supporting student e-learning adoption. This study supports the sustainability of technology used in e-learning concepts. This research method is a quantitative survey of students in the city of Bandung (Indonesia) who implement e-learning as a learning medium. Data from students were taken through a questionnaire and processed using SmartPLS. The analysis was carried out using regression analysis with research hypothesis testing. The results of the study found that the expected benefits, e-learning curriculum, and educational partners have a positive relationship with the e-learning adoption of students in online learning. The E-learning curriculum is an antecedent variable that has better support for e-learning adoption. The research findings explain that e-learning adoption in universities can be built by three aspects starting from the e-learning curriculum, expected benefits, to educational partners. There is important information from this research that can be used as information support on the implementation and sustainability of online learning. E-learning organizers are expected to be able to improve the concept of e-learning, especially in the curriculum, because it has an important role to increase student e-learning adoption. © 2023 Author(s).

The Role of IoT Technologies in Malaysia During the Covid-19 Pandemic: A Mini- Review

The Covid-19 global infection has significantly influenced people's health, resulting in sudden changes in lifestyle through social exclusion and isolation. To break the transmission and terrifying health threat of Covid-19, the Malaysian Government imposed a Movement Control Order (MCO) starting March 18, 2020, by restricting movement and contact. The Covid-19 pandemic emphasized the importance of the digital inclusion agenda, and the application of Internet of Things (IoT) services has given tremendous benefits in various disciplines, as it helps maintain physical distance during the pandemic. Modern lifestyles are being transformed by the IoT revolution by embracing technological, economic, and social prospects. In fact, many sectors in Malaysia would be transformed through the application of IoT, particularly in productivity, and services. Thus, this review paper discusses IoT's most recent breakthroughs and applications that are used in Malaysia during the Covid-19 crisis. Furthermore, it investigates current IoT implementation and discusses the potential impact of the pandemic on the application of IoT in terms of technology trends and economic impact. IoT is worth mentioning as one of the technologies demonstrating its importance and capabilities in mitigating the severity of the pandemic within the country. This article delves into the applications, social and economic impact, and barriers to the widespread adoption of IoT in the Covid-19 pandemic. This review paper will be useful to academic researchers, business professionals, organizations in various sectors, and anyone interested in determining IoT services' impact on pandemics.

Gamification in Online Learning: A Case Study among University Students in Malaysia

Online learning has become compulsory when the world was facing the Covid 19 outbreak. Accordingly, students' engagement and participation during online learning have been a major concern among teachers. By adapting the Technology Acceptance Model (TAM), the present study is carried out to examine influential factors towards the intention to use gamification during online classes. With the use of judgmental sampling, 283 usable responses have been gathered from undergraduate students in Malaysia. Results revealed that ‘authentic' positively affects three mediating variables of perceived value (PEU), perceived usefulness (PU) and perceived enjoyment (PE). Additionally, PEU, PU and PE posit positive responses towards the intention to use gamification in online learning. Furthermore, all three mediators also present positive effects in the relationship between authentic and intention to use. Thus, this study affirms the usability of TAM in the online learning context with the extension of authenticity as the external factor and perceived enjoyment as the mediating factor. The results give implications for educators and higher learning institutions to modify their learning outcomes and course content to be more interesting with the usage of online gamification tools. Perhaps, this study gives further insight for future research to apply other external factors, such as knowledge and trust to enrich the study in gamification context © 2023, Asian Journal of University Education.All Rights Reserved.

A New UAV-Based Social Distance Detector for COVID-19 Outbreaks Reduction, Using IoT, Computer Vision and Deep Learning Technologies

Nowadays, we are living in a dangerous environment and our health system is under the threatened causes of Covid19 and other diseases. The people who are close together are more threatened by different viruses, especially Covid19. In addition, limiting the physical distance between people helps minimize the risk of the virus spreading. For this reason, we created a smart system to detect violated social distance in public areas as markets and streets. In the proposed system, the algorithm for people detection uses a pre-existing deep learning model and computer vision techniques to determine the distances between humans. The detection model uses bounding box information to identify persons. The identified bounding box centroid's pairwise distances of people are calculated using the Euclidean distance. Also, we used jetson nano platform to implement a low-cost embedded system and IoT techniques to send the images and notifications to the nearest police station to apply forfeit when it detects people's congestion in a specific area. Lastly, the suggested system has the capability to assist decrease the intensity of the spread of COVID-19 and other diseases by identifying violated social distance measures and notifying the owner of the system. Using the transformation matrix and accurate pedestrian detection, the process of detecting social distances between individuals may be achieved great confidence. Experiments show that CNN-based object detectors with our suggested social distancing algorithm provide reasonable accuracy for monitoring social distancing in public places, as well. © 2022 Lavoisier. All rights reserved.

Data stories and dashboard development: a case study of an aviation schedule and delay causes

In this case study, five key processes in modelling a data story of aviation data patterns during COVID-19 have been executed. It started with the collection of secondary data from relevant sources. Data inspection, transformation, and preparation activities, including data cleaning, filtering, and sampling, are all included in this work. Iterative exploratory data analysis (EDA) has been conducted to determine the pattern of each independent attribute, followed by an assessment after the data story is modelled and integrated on a dashboard. The questionnaire has been distributed and the visuals were assessed by giving respondents a few tasks to interpret stories based on their comprehension. The result shows that the data stories have been interpreted in a similar narrative by all the respondents. The overall mean score is 4.71, and this significantly shows that the respondents agree and strongly agree that the visual objects help in communicating patterns and stories. The overall process gives researchers experience and guidelines for future work. Overall, the objectives of the study have been met. Nevertheless, it gives researchers a lot of experience in interpreting data, cleansing and transformation, analysis, modelling the visualisation by selecting suitable charts, and integrating the objects together into a dashboard.

Malaysian Enhanced Movement Control Order (EMCO): a unique and impactful approach to combating pandemic COVID-19

Purpose - The paper highlights the process-handling during the Enhanced Movement Control Order (EMCO) in combating pandemic COVID-19 in Malaysia. Design/methodology/approach - Malaysia first issued an EMCO following a cluster that involved a religious gathering. The EMCO was issued to lockdown the area, undertake screening, treat positive cases and quarantine their close contacts. Active case detection and mass sampling were the main activities involving the population in both zones. Findings - One hundred ninety-three confirmed COVID-19 cases were identified from the total population of 2,599. Of these cases, 99.5% were Malaysians, 31.7% were aged >60 years and all four deaths (Case Fatality Rate, 2.1%) were elderly people with comorbidities. One hundred and one cases (52.3%) were asymptomatic, of which 77 (77%) were detected during mass sampling. The risk factors contributing to the outbreak were contacts that had attended the religious gathering, regular mosque congregants, wedding ceremony attendees and close household contacts. Malaysia implemented an effective measure in the form of the EMCO to contain the COVID-19 outbreak, where the last cases were reported 16 days before the EMCO was lifted. Originality/value - The residents' compliance and inter-agency cooperation were essential elements to the success of the EMCO. A targeted approach using an EMCO should be implemented in a future pandemic.

Social media platforms in promoting effectiveness campaign during Covid-19

Today, social media plays a vital role in providing information to the public through various platforms including traditional and digital media. In March 2020, the government had announced the Movement Control Order (MCO) due to the outbreak of COVID-19 in.Malaysia. As a result of globalization, COVID-19 shows that pandemic breakouts pose a significant threat to the world. However, using social media to promote campaigns during COVID-19 has its own drawbacks, such as the difficulty of recognizing promoted content. Social media sites have evolved into one of the most important sources of information as well as a platform for spreading dangerous rumors. Thus, it is also under severe pressure to regulate disease misinformation that is pushing people in the wrong direction. Therefore, the purpose of this research is to identify which social media platforms are more effective towards effectiveness campaigns during COVID-19. Researchers employed quantitative surveys, which were distributed across all social media platforms from various people. In sampling, researchers have referred to Roasoft Sample Size Calculator [11]. A total of 162 respondents responded to the survey. The findings of this research prove that Malaysians are using social media for promoting the effectiveness campaign during COVID-19, with M=3.44 being the highest. Furthermore, males are the most effective in promoting the COVID-19 campaigns, with a score of 0.262. © 2022 Author(s).

Online shopping acceptance between gender amid Covid-19 pandemic

Internet advancements and technological sophistication play integral parts in driving online shopping. This method is widely used globally and has become the latest trend among people regardless of age. It was brought to the forefront so that people would no longer need to go to a physical store to make purchases or sales as the world is moving fast and forward nowadays. Even though the world is still recuperating from the COVID-19 pandemic where the number of cases rise every day, online shopping remains the public choice method of monthly shopping. Regardless of how great a revolution it is, online shopping is not all roses. There have been concerns with security and guarantees, quality, and logistics. The aim of this study is to identify the level of online shopping acceptance between male and female during the COVID-19 pandemic. The study involved 335 respondents from various demographic backgrounds. The quantitative research method was used in this research where questionnaires were distributed via a purposive sample technique. The data were analysed through the Statistical Package of Social Science (SPSS) version 23. In general, this research proved that Malaysians' acceptance towards online shopping during COVID-19 pandemic is high (M=3.14). Female respondents are more likely to accept online shopping. However, there is no significant difference between males and females. © 2022 Author(s).

The level of stress among different household income during Covid-19

Coronavirus disease (COVID-19) is a contagious disease caused by a new virus. The majority of patients infected with the COVID-19 virus will usually experience light to medium respiratory illness and will recover without getting any special treatment. Since the case became more serious, the Malaysian government has issued a Movement Control Order to beat the coronavirus and protect the country's health systems. However, there are unintended consequences caused by the coronavirus. Besides, it brings different kinds of stress, including physical and mental health risks. The main objective of this study is to examine the level of stress experienced by people from diverse socioeconomic backgrounds during COVID-19. Researchers used a quantitative method and distributed a Google Form survey to all social media platforms. A total of 191 people responded to the survey. From the findings, Malaysians are extremely stressed during this pandemic (M=3.58). Furthermore, the results show that people in the B40 income category are more stressed than those in the M40 and T20 household income categories. The government should take this issue more seriously and assist individuals who are affected by the pandemic of COVID-19. © 2022 Author(s).

Impact of the COVID-19 pandemic on essential workers in Europe: Subset analysis of a global online survey

Introduction: This study aims to explore how essential workers in Europe differed from the rest of the population in terms of their experiences of social life, access to services, mental well-being, and perceived benefits of the lockdown. Methods: This study used a descriptive analysis to evaluate the overall experiences of the essential workers in Europe. Data analyzed in this study is part of a larger global online cross-sectional survey conducted during April to November 2020 involving post-secondary staff, students and the general population (remote workers). Data of 19,794 participants are included in the current study, and analysis is based on a comparison of participants who self-identified as essential workers, with those who did not using the chi-square test. Results: Mean age was 34.5 years (SD =13.0) for essential workers and 30.2 years (SD =12.4) for the general population (remote workers). While 13.6% of all respondents were essential workers, the proportion was more among older ages (30 and above), females, and those who lived in suburbs. Overall, 46.8% of participants reported increased levels of stress during week 1-2 (51% of essential workers and 46.1% of the other participants, p<0.001). More essential workers reported their social life being great than the rest of the population (25.3% vs. 16.4%, p<0.001), and COVID-19 symptoms (13.6 vs 10.5%, p<0.001). In addition, fewer reported having troubled relationships (16.3% vs. 18.6%, p<0.001) or being able to do sufficient exercise (35.7% vs. 40.5%, p<0.001) than the general population (remote workers). Take-home message: The important role of essential workers during the pandemic cannot be overstated, yet their contributions, especially non-healthcare essential workers, have not been fully appreciated. © 2022 Parvin EFTEKHAR et al.

IT Infrastructure and Perceived Ease of Use to Increase E-Learning Adoption

The pandemic in 2020 known as Covid-19 had an impact on independent learning at home. Learning in university ultimately needs to be done online because of face-to-face restrictions. However, online learning activities ultimately affect the level of student motivation in learning. Examining the implementation of learning system on the university, the purpose of this study is to evaluate e-Iearning adoption on student psychological motivation through IT infrastructure support and perceived ease of use. This research examines a model with the goal of student psychological motivation, so that a study was carried out on students with a total of 149 respondents. The research method was carried out by quantitative surveys and research data obtained from questionnaires. Research with path analysis was conducted to evaluate the research model. In testing the research model, a study was carried out through the evaluation of research hypotheses. The findings in the model test results it is known that IT infrastructure and perceived ease of use are important for student regarding adoption to online learning. Another finding was conveyed that e-Iearning adoption can increase students' psychological motivation. The research findings focus on the mediation model of e-Iearning adoption;furthermore for universities, this model can be used as input on the implementation of online learning. Model adaptation aims to increase student motivation in dealing with online learning. © 2022 IEEE.

Sudden sensorineural hearing loss in coronavirus disease-2019: Our experience

Coronavirus disease-2019 (COVID-19) is an ongoing global pandemic exerting considerable strain on the health-care system. Sudden-onset sensorineural hearing loss (SSNHL) among patients with COVID-19 had been reported sparingly in the literature. Hearing loss can be easily overlooked in intensive care settings and establishing diagnosis can also be challenging. Proposed causes include injury to inner ear structures, cochlear nerve, or auditory brainstem. Prompt diagnosis and treatment is recommended to avoid long-term morbidity. All patients presenting with sudden-onset hearing loss should be screened for COVID-19. Here, we report a case of COVID-19 patient with SSNHL and how the hearing level is determined. Copyright © 2022 Indian Journal of Otology Published by Wolters Kluwer-Medknow.

A literature review of dual disaster challenges for resilient office building toward reducing disaster risks

Flood is acknowledged as the most common natural disaster in several parts of the globe. For Malaysia, flood is considered as the most frequent natural disaster, with the frequency of at least once a year. The risks of flood can be seen through property loss and damages, infrastructure casualties, and disruption to socio-economic activities. Adding to that, Malaysia also faced the flood during the pandemic when it hit several states, namely Pahang, Johor, and Kelantan, during the monsoon season in 2020 and 2021, amid the rising cases of Covid-19. The ongoing COVID-19 pandemic has posed significant challenges for disaster response, calling for the “new norms” to be quickly established for better disaster risk reduction. Several mitigation strategies have been taken by the government to reduce the risks of floods in Malaysia. As office buildings possess important roles in delivering effective services to the public while maintaining their critical documents, this paper focuses on providing related literature on building resilience. Having an early understanding of the core elements of office building resilience in dual disaster challenges will provide the basis for further investigation in the later stage of data collection.

The molecular basis of the severe acute respiratory syndrome coronavirus 2 (sars-cov-2)

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive singlestranded ribonucleic acid (ssRNA) virus in the Coronavridae family that was first identified in December 2019. The virus causes a disease named COVID-19, which is associated with various respiratory symptoms ranging from mild to life-threatening complications. The pandemic state was announced by the World Health Organization (WHO) in March 2020. Since then, the viral genome and structure have been extensively studied. This review aims to present the most recent advances in the SARS-CoV-2. The viral genome encodes 16 non-structural proteins involved in viral replication and transcription, four structural proteins assembled to form the virions, and at least six accessory proteins involved in viral pathogenicity and virions assembly. Being an RNA virus, the SARS-CoV-2 genome undergoes rapid mutations. Several thousand mutations in the submitted genomes compared with the first strain have been reported since the pandemic's beginning. Some mutations such as the ''Cluster 5'' variant, VOC 202012/01, and the N501Y mutation raised public health concerns globally because they could affect the virus transmissibility, disease severity, diagnostic methods, and vaccine development. The virus infects humans by recognizing the ACE2 receptor on the human cells and the TMPRSS2 proteolytic effect. The gold standard diagnostic method based on the WHO is nucleic acid amplification testing;however, several other non-molecular and radiological testing could also be beneficial. Several trials have been initiated to produce an effective vaccine, more than 60 have reached clinical trials, and some have recently been approved. The leading vaccines are the RNA-based ones;BNT162b2 and Moderna. Further studies are required to evaluate the vaccines' effectiveness, diagnostic efficacy, and disease management to keep pace with the ongoing viral evolution. © 2022, An-Najah National University. All rights reserved.

Sudden hearing loss and COVID-19 vaccine: A potential signal?

Introduction: Vaccination against COVID-19 appears to be a promising approach to mitigate this pandemic. The French agency of medicinal products (ANSM) issued a signal concerning cases of sudden hearing loss (SHL) following vaccination with elasomeran (Spikevax® Moderna) [1] and AZD1222 (Vaxzevria® AstraZeneca) [2]. SHL is defined as a sensorineural hearing loss ≥30 dB within 72 hours [3]. We aimed to investigate the potential signal of SHL associated with COVID-19 vaccines. Material and methods: We queried VigiBase® (World Health Organization pharmacovigilance database), for all reports of "Sudden Hearing Loss" (MedDRA Preferred Term) related to "COVID-19 vaccine" (Active Ingredient), from 1967 to December 30, 2021 [4]. Disproportionality analysis was based on the Reporting Odds Ratio (ROR) with its 95% Confidence Interval (CI) and the Information Component (IC). A positive IC025 is statistically needed to confirm the detection of a signal [5]. Results: In VigiBase®, 1,602 cases of COVID-19 vaccine-associated SHL were collected. Tozinameran (Pfizer-BioNTech) was mostly notified with 1,053 (65.7%) reports, followed by elasomeran (Moderna, 281, 17.5%), AZD1222 (AstraZeneca, 217, 13.5%), and JNJ 78436735 (Janssen, 43, 2.7%). Most cases concerned women (885, 55.2%), with a median age of 51 years, and 827 (51.6%) were considered serious. The association of COVID-19 vaccines and SHL showed significant disproportionality, with a ROR of 7.4 (95% CI 6.9-7.9) and an IC025>0. Tozinameran reached the strongest ROR (8.2;95% CI 7.6-8.8), followed by elasomeran (4.6;95% CI 4.0-5.2), JNJ-78436735 (3.0;95% CI 2.2-4.0), and AZD1222 (2.7;95% CI 2.3-3.1), all with IC025>0. Discussion/Conclusion: Significant disproportionality was identified for COVID-19 vaccines and SHL. Even though this adverse drug event may rely on an inflammatory mechanism, causality cannot be established by this pharmacovigilance study. However, this finding may strengthen the signals issued by ANSM, concerning elasomeran and AZD1222. SHL following COVID-19 vaccination might be evoked and treated as soon as possible.

COVID-19 vaccine-associated trigeminal neuralgia: Analysis of the WHO safety database

Introduction: To contain the COVID-19 pandemic, vaccination is deemed as a promising approach. A French pharmacovigilance survey identified five cases of trigeminal neuralgia (TN) following vaccination with AZD1222 (Vaxzevria®, AstraZeneca) [1]. Furthermore, a case report mentioned such an adverse reaction with tozinameran (Comirnaty®, Pfizer-BioNTech) [2]. TN is characterized by recurrent, unilateral, and brief electric shock-like pain in one or more trigeminal divisions [3]. TN is triggered by innocuous stimuli. We aimed to investigate the potential signal of TN related to COVID-19 vaccines. Material and methods: We queried VigiBase® (World Health Organization pharmacovigilance database) for all reports of "Trigeminal Neuralgia" (MedDRA Preferred Term) associated with "COVID-19 vaccine" (Active Ingredient), from 1967 to December 29, 2021 [4]. Disproportionality analysis relied on the Reporting Odds Ratio (ROR) with its 95% Confidence Interval (CI), and the Information Component (IC). A positive IC025 is statistically needed to confirm the detection of a signal [5]. Results: In VigiBase®, we gathered 1,283 cases of COVID-19 vaccine-related TN. Most reports involved women (998, 77.8%), with a median age of 52 years, and 510 (39.8%) were deemed serious. Tozinameran was mostly reported with 782 (61.0%) cases, followed by AZD1222 (264, 20.6%), elasomeran (Spikevax® Moderna, 185, 14.4%), and JNJ-78436735 (Janssen® Johnson & Johnson, 37, 2.9%). The association of COVID-19 vaccines and TN revealed significant disproportionality, with an IC025>0 and a ROR of 3.1 (95% CI 2.9-3.3). Tozinameran showed the strongest ROR (3.6;95% CI 3.3-3.8), followed by AZD1222 (2.3;95% CI 2.0-2.6), elasomeran (2.0;95% CI 1.7-2.3), and JNJ-78436735 (1.8 95% CI 1.3-2.5), each with IC025>0. Discussion/Conclusion: COVID-19 vaccines and TN showed relevant disproportionality. Albeit this reaction may rely on an immune-mediated inflammation, causality can only remain hypothetical in this pharmacovigilance study. Nonetheless, this finding may suggest a signal, strengthening reports mentioned by literature and French pharmacovigilance. A TN occurring after COVID-19 vaccination should alert the clinician.

Is transient global amnesia an adverse event associated with COVID-19 vaccines?

Introduction: Vaccination against COVID-19 appears to be a promising approach to mitigate this pandemic. The French agency of medicinal products (ANSM) issued a signal concerning cases of transient global amnesia (TGA) following vaccination with elasomeran (Spikevax® Moderna) [1]. TGA is characterized by the sudden onset of anterograde amnesia with preservation of other cognitive functions and a spontaneous resolution within 24 h [2]. We aimed to investigate the potential link of TGA with COVID-19 vaccines. Material and methods: We queried the WHO VigiBase® for all reports of "Transient global amnesia" (MedDRA Preferred Term) related to "Covid-19 vaccine"(Active Ingredient), from 1967 to December 6, 2021 [3]. Disproportionality analysis was based on the Reporting Odds Ratio (ROR) with its 95% Confidence Interval [CI] and the Information Component (IC) [4]. A positive IC025 statistically detects a signal [5]. Results: The search yielded 289 COVID-19 vaccine-associated TGAs, 178 of which (61.6%) were deemed serious. Most cases concerned women (187, 64.7%), with a median age of 66 years. Tozinameran (T: Comirnarty® Pfizer-BioNTech) was the most represented with 147 reports (50.8%), followed by AZD1222 (A: Vaxzevria® AstraZeneca) with 69 reports (23,8%), elasomeran (E: Spikevax®, Moderna) with 60 reports (20.8%), and JNJ-78436735 (J: Janssen® Johnson & Johnson) with 12 reports (4.2%). With a IC025 > 0, COVID-19 vaccines proved a significant disproportionality (global ROR 5.1 [4.4-6.0]), with respective RORs at 4.6 [3.9-5.0] for T, E at 4.4 [3.4-6.0], A at 3.8 [3.0-5.0], and J at 3.7 [2.1-6.0]. Discussion/Conclusion: Our analysis of COVID-19 vaccines and TGA shows significant disproportionality. Various mechanisms, such as cerebrovascular, inflammatory, or migrainous, may underlie this association. Yet causality cannot be ascertained solely with this approach, although it strengthens the signal issued by the ANSM. Further studies may help to identify the causality of COVID-19 vaccines in triggering TGAs.

The Impact of Fiscal Policy Instruments on Economic Wellness: Evidence From Malaysian Per Capita Income

This study examines the strength of the impact of fiscal policy tools on economic wellbeing as measured by per capita income in Malaysia from 1996 to 2020. The impact of fiscal policy instruments on economic wellness, represented by real income per capita, is measured using the autoregressive distributed lags model. The speed of adjustment from short-run disequilibrium to long-run equilibrium is also measured to assess the strength of the fiscal instruments' impact on per capita income. Empirical results exhibit the existence of co-integration relationships between per capita income, tax revenue, and government spending. The findings provide strong support for the presence of a long-run positive impact on government spending and a long-run negative impact of tax revenue on per capita income. The coefficient of ECTt-1 indicates that deviations from a short-run disequilibrium to a long-run equilibrium from the current to the future period are corrected with a speed of 76% (equivalent to a duration of 1.5-2 years to return to equilibrium). The practical and policy implication of the results is fiscal instruments play a significant role, mainly in alleviating the economic impact of the COVID-19 pandemic in the long run.

A Low-Cost Embedded Security System for UAV-Based Face Mask Detector Using IoT and Deep Learning to Reduce COVID-19

Nowadays, the most effective method against the virus is wearing a mask. Hence, it is fundamental to wear a mask appropriately at open places like general stores and shopping malls. This paper proposes a novel human face mask detection method from UAV-captured frame sequences to solve the aforementioned problem. The proposed approach involves an offline stage and an inference stage. The offline stage generates the mask or no-mask by utilizing a convolutional neural network. We trained our model on a face mask dataset, and this enhancement allows the suggested system to obtain high accuracy in detecting unmasked people. The inference stage uses the already generated model to detect no mask humans and sends the alert to the smartphone-based Internet of Things. At this stage, Jetson nano was used to implement an embedded powerful real-time application for UAV-based face mask detection that runs at high frames per second. The proposed system monitors and detects people who have not worn a mask. Also, we used IoT techniques to send the pictures and notifications to the nearest police station to apply forfeit when it detects unmasked people. The main contributions in this paper lie in adjusting the deep learning, embedded platforms, IoT techniques, and Tello drone, generally dedicated to detecting unmasked people at a low cost. On average, detection accuracy is 99% based on the experimental evaluation of the proposed deep learning model for UAV-based face mask detection on the provided dataset. Overall, the proposed method can help decrease the spread of COVID-19 and other transmissible diseases. © 2022 IEEE.

Analysing Trends and Forecasting of COVID-19 Pandemic in Malaysia using Singular Spectrum Analysis

The Singular Spectrum Analysis (SSA) is a powerful non-parametric time series analysis that has demonstrated its capability in forecasting different time series in various disciplines. SSA falls in the framework of data-driven modelling of dynamical system which does not rely on any underlying assumption except the inherent dynamics which are captured over time. The capabilities of SSA are mainly aff orded by its direct connection to the singular value decomposition (SVD). It is generally accepted that SVDbased methods are very affective for the noise reduction in deterministic time series and consequently for forecasting, as well as for extracting trends and structures. Despite its strength, several shortcomings of SSA in the analysis of COVID-19 time series have been reported in the literature. The aim of this paper is to determine the scope of this limitation and we confine our investigation in the analysis and forecasting of COVID-19 Pandemic in Malaysia. We scrutinize the results fromthe SSA analysis of the number of daily confirmed cases to gain further insight into the intrinsic trends of the pandemic. Groupings of the singular spectra that contributes to different features of the pandemic time series are identified using analysis of the singular value spectrum, periodogram analysis and analysis of the weighted correlation matrix. It was revealed that under stationary conditions, the principal eigentriple is sufficient to produce reliable forecast. However, in non-stationary conditions, for example during a movement control order, it is useful to also study the minor eigentriples which could contain transient dynamics that may persist.