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1.
Journal of Pure and Applied Microbiology ; JOUR
Article in English | Web of Science | ID: covidwho-2100697

ABSTRACT

Saliva samples could be used as a non-invasive method to diagnose COVID-19. We aimed to assess the results of the reverse transcriptase-polymerase chain reaction (RT-PCR) of saliva specimens in the detection of COVID-19. We collected saliva and nasopharyngeal (NP) samples from consecutive COVID-19 suspects in Al-Fallujah Teaching Hospital, Anbar, Iraq from November 29, 2021 to February 15, 2022. The results of the two specimens were compared using RT-PCR. For the positive saliva tests, repetition of the test was undertaken at weekly intervals for four weeks from the time of the presentation. There were 55% men and 60% people <= 35 years. The majority of cases presented within 2-5 days (92%) and were of mild severity (89%). A hundred pairs of samples were taken. COVID-19 was diagnosed by NP swab RT-PCR in 56% and 31% of the saliva samples. The saliva samples had 100% sensitivity (95% confidence interval ICI] 60.4% e96.6%), 63.8% specificity (95% CI 96.1% e99.9%), and mild coefficient agreement (kappa coefficient = 0.522). The positive test for the saliva samples remained as such in all examined cases in the first and second weeks after the first test, 31/31 and 30/30, respectively. While half of them were positive in the third week (15/30). All cases became negative in the fourth week (0/15). We recommend not using the saliva swab as an alternative to the NP swab in the detection of the SARS-CoV-2 by RT-PCR. However, saliva sample can be used for the follow-up of the COVID-19 subjects, in children, elderly, and handicapped patients.

2.
Asian Journal of University Education ; 18(3):818-829, 2022.
Article in English | Scopus | ID: covidwho-2040609

ABSTRACT

The Covid-19 pandemic has brought about a true challenge to students and educators in the teaching, learning and assessment (TLA) of the psychomotor domain integral in laboratory experiment and design work. The pandemic has opened venues for open distance learning (ODL) with a completely new outlook for educators. The objective of this paper is to examine the suitability of the alternative TLA methods adopted in laboratory courses in ODL during the pandemic. Document review was carried out on various laboratory courses for a civil engineering programme in Universiti Teknologi MARA. The findings show that the assessment methods commonly used during ODL are individual and group reports, lab demonstration, video presentation, laboratory projects, online tests, individual online interviews, home-based mini projects, peer evaluation, and simulation using various software. Each alternative assessment was evaluated based on three (3) criteria which are the relevancy of knowledge, TLA activities, and suitability of the TLA activities to address the respective learning domain of the courses. Overall, the alternative assessment methods used during ODL were found to be relevant in imparting knowledge in laboratory courses, except for the development of specialist knowledge (WK4) as students are not able to utilize the equipment in the laboratory. Meanwhile, alternative activities are found less suitable to address the psychomotor domain imparted in the learning outcomes that involve specified equipment or machinery. Finally, the alternative assessments are found to effectively capture the cognitive skills and the programme outcomes related to knowledge application (PO1) and analysis (PO2) but are less effective in capturing investigation skills (PO4) addressing the psychomotor domain. © 2022, Asian Journal of University Education. All Rights Reserved.

3.
IEEE Access ; : 1-1, 2022.
Article in English | Scopus | ID: covidwho-2037807

ABSTRACT

Generative adversarial networks (GANs) gained tremendous growth due to its potential and efficacy in producing realistic samples. This study proposes a light-weight GAN (LiWGAN) to learn the non-image synthesis with minimum computational time for less power computing. Hence, the LiWGAN method enhanced a new skip-layer channel-wise excitation module (SLE) and a self-supervised discriminator design for the non-synthesis performance using the facemask dataset. The facemask is one of the preventative strategies pioneered by the current COVID-19 pandemic. LiWGAN manipulates a non-image synthesis of facemask that could be beneficial for some researchers to identify an individual using lower power devices, occlusion challenges for face recognition, and alleviate the accuracy challenges due to limited datasets. The performance compared the processing time for a facemask dataset in terms of batch sizes and image resolutions. The Fréchet inception distance (FID) was also measured on the facemask images to evaluate the quality of the augmented image using LiWGAN. The findings for 3000 generated images showed a nearly similar FID score at 220.43 with significantly less processing time per iteration at 1.03s than StyleGAN at 219.97 FID score. One experiment was conducted using the CelebA dataset to compare with GL-GAN and DRAGAN, proving LiWGAN is appropriate for other datasets. The outcomes found LiWGAN performed better than GL-GAN and DRAGAN at 91.31 FID score with 3.50s processing time per iteration. Therefore, LiWGAN could aim to enhance the FID score to be near zero in the future with less processing time by using different datasets. Author

4.
Malaysian Journal of Medicine and Health Sciences ; 18(4):173-181, 2022.
Article in English | Scopus | ID: covidwho-2026814

ABSTRACT

Big data analytics (BDA) in digital health is critical for gaining the knowledge needed to make decisions, with Asia at the forefront of utilising this technology for the Coronavirus disease 2019 (COVID-19). This review aims to study how BDA was incorporated into digital health in managing the COVID-19 pandemic in six selected Asian countries, discuss its advantages and barriers and recommend measures to improve its adoption. A narrative review was conducted. Online databases were searched to identify all relevant literature on the roles of BDA in digital health for COVID-19 preventive and control measures. The findings showed that these countries had used BDA for contact tracing, quarantine compliance, outbreak prediction, supply rationing, movement control, information update, and symptom monitoring. Compared to conventional approaches, BDA in digital health plays a more efficient role in preventing and controlling COVID-19. It may inspire other countries to adopt this technology in managing the pandemic. © 2022 UPM Press. All rights reserved.

5.
ENVIRONMENT-BEHAVIOUR PROCEEDINGS JOURNAL ; 7:287-295, 2022.
Article in English | Web of Science | ID: covidwho-1939545

ABSTRACT

Police officers play a crucial role in guaranteeing the safety of residents by protecting their lives. However, due to the COVID-19 epidemic, police officers were supposed to organize local shutdowns, promote social distance, and enforce stay-at-home orders. Hence, this research aims to explore potential sources of stress, and causes of conflict. The respondents are the police officers from Petaling Jaya District Police Headquarter. Data is collected using a questionnaire and analyzed using SPSS. Findings show that most police officers feel stressed since the outbreak of the COVID-19 pandemic, along with their workload.

6.
NeuroQuantology ; 20(6):1653-1656, 2022.
Article in English | EMBASE | ID: covidwho-1928911

ABSTRACT

Nurses’ Quality Work Life affects the quality of services provided by the hospital. Nurses’ QWL has decreased especially since the covid-19 pandemic. This phenomenon may cause nurses at risk of experiencing physical and psychological problems which can leads to burnout among nurses. This study aims to find a relationship between quality of work life and burnout, especially in the midst of the COVID-19 pandemic at Dirgahayu Hospital in Samarinda. This study used a cross-sectional design with a sample size of 266 respondents who meet the inclusion criteria. Data collection was conducted in April 2021. The results of the research are there is a relationship between the quality of work life on burnout of nurses during the COVID-19 pandemic at Dirgahayu Hospital with the variable found with the greatest influence is the relationship with managers. High motivation and hard work of nurses in carrying out their responsibilities make the performance of nurses good. Evaluation of the quality of work life of nurses needs to be carried out as a whole so that improvements can be made to the quality of work life and prevent burnout.

7.
Journal of Clinical Outcomes Management ; 29(1):27-31, 2022.
Article in English | EMBASE | ID: covidwho-1884742

ABSTRACT

Background: Patient outcomes of COVID-19 have improved throughout the pandemic. However, because it is not known whether outcomes of COVID-19 in the type 1 diabetes (T1D) population improved over time, we investigated differences in COVID-19 outcomes for patients with T1D in the United States. Methods: We analyzed data collected via a registry of patients with T1D and COVID-19 from 56 sites between April 2020 and January 2021. We grouped cases into first surge (April 9, 2020, to July 31, 2020, n = 188) and late surge (August 1, 2020, to January 31, 2021, n = 410), and then compared outcomes between both groups using descriptive statistics and logistic regression models. Results: Adverse outcomes were more frequent during the first surge, including diabetic ketoacidosis (32% vs 15%, P< .001), severe hypoglycemia (4% vs 1%, P= .04), and hospitalization (52% vs 22%, P< .001). Patients in the first surge were older (28 [SD,18.8] years vs 18.0 [SD, 11.1] years, P< .001), had higher median hemoglobin A1c levels (9.3 [interquartile range {IQR}, 4.0] vs 8.4 (IQR, 2.8), P< .001), and were more likely to use public insurance (107 [57%] vs 154 [38%], P< .001). The odds of hospitalization for adults in the first surge were 5 times higher compared to the late surge (odds ratio, 5.01;95% CI, 2.11-12.63). Conclusion: Patients with T1D who presented with COVID-19 during the first surge had a higher proportion of adverse outcomes than those who presented in a later surge.

8.
10th AMER International Conference on Quality of Life (AicQoL) ; 7, 2022.
Article in English | Web of Science | ID: covidwho-1790720

ABSTRACT

Police officers play a crucial role in guaranteeing the safety of residents by protecting their lives. However, due to the COVID-19 epidemic, police officers were supposed to organize local shutdowns, promote social distance, and enforce stay-at-home orders. Hence, this research aims to identify potential sources of stress, and causes of conflict. The respondents are the police officers from Petaling Jaya District Police Headquarter. Data is collected using a questionnaire and analyzed using SPSS. Findings show that most police officers feel stressed since the outbreak of the COVID-19 pandemic, along with their workload.

9.
J Epidemiol Glob Health ; 12(2): 188-195, 2022 06.
Article in English | MEDLINE | ID: covidwho-1783064

ABSTRACT

BACKGROUND: Coinfection at various sites can complicate the clinical course of coronavirus disease of 2019 (COVID-19) patients leading to worse prognosis and increased mortality. We aimed to investigate the occurrence of coinfection in critically ill COVID-19 cases, and the predictive role of routinely tested biomarkers on admission for mortality. METHODS: This is a retrospective study of all SARS-CoV-2-infected cases, who were admitted to King Fahad Hospital of the University between March 2020 and December 2020. We reviewed the data in the electronic charts in the healthcare information management system including initial presentation, clinical course, radiological and laboratory findings and reported all significant microbiological cultures that indicated antimicrobial therapy. The mortality data were reviewed for severely ill patients who were admitted to critical care units. RESULTS: Of 1091 admitted patients, there were 70 fatalities (6.4%). 182 COVID-19 persons were admitted to the critical care service, of whom 114 patients (62.6%) survived. The in-hospital mortality was 13.4%. Coinfection was noted in 67/68 non-survivors, and Gram-negative pathogens (Enterobacterales, Pseudomonas aeruginosa, and Acinetobacter baumanni) represented more than 50% of the etiological agents. We noted that the serum procalcitonin on admission was higher for non-survivors (Median = 1.6 ng/mL ± 4.7) than in survivors (Median = 0.2 ng/mL ± 4.2) (p ≤ 0.05). CONCLUSION: Coinfection is a serious complication for COVID-19 especially in the presence of co-morbidities. High levels of procalcitonin on admission may predict non-survival in critically ill cases in whom bacterial or fungal co-infection is likely.


Subject(s)
COVID-19 , Coinfection , COVID-19/epidemiology , COVID-19/therapy , Coinfection/epidemiology , Critical Illness , Humans , Procalcitonin , Retrospective Studies , SARS-CoV-2
10.
11th International Conference on Robotics, Vision, Signal Processing and Power Applications, RoViSP 2021 ; 829 LNEE:419-425, 2022.
Article in English | Scopus | ID: covidwho-1718617

ABSTRACT

The novel Corona Virus (COVID-19) has spread so rapidly that cause a devastating effect on public well-being and create an emergency around the world. Hence, the rapid identification of COVID-19 has become a challenging work within a short period. Clinical trials of patients with COVID-19 have shown that most of the patients affected by COVID-19 experience lung infection that can cause inflammation in the lung after virus-contiguity. It can damage the cells and tissue that is inside the lung. However, pneumonia is also a lung infection that can cause inflammation in the air sacs inside the lung. Chest X-rays and CT scans perform an essential role in the detection of lung-related illnesses. Therefore, concerning the diagnosis of COVID-19, radiography and chest CT are considered as fundamental imaging approaches. This study presents a densely interconnected convolutional neural network-based approach to identify COVID-19, Pneumonia and Normal patients from chest X-ray images. To experiment with the proposed methodology, a new dataset is generated by combining two different datasets from Kaggle named COVID-19 Radiography Database and Chest X-ray (COVID-19 & Pneumonia). The dataset comprises of 500 X-ray images of COVID-19 affected people, 2600 X-ray images of Normal people, and 3418 X-ray images of pneumonia affected people. The proposed densely interconnected convolutional neural network model produces 99% testing accuracy for COVID-19, 98% testing accuracy for Pneumonia and 98% testing accuracy for Normal people without the application of any augmentation techniques. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

11.
3rd International Conference on Green Environmental Engineering and Technology, IConGEET 2021 ; 214:9-17, 2022.
Article in English | Scopus | ID: covidwho-1718609

ABSTRACT

Most institutions and organizations nowadays have been taking responsibility in reducing their carbon footprint (CF) to curtail the global warming impact to at least 20–25% reduction by 2030. Universities and higher learning institutions are starting to invest in becoming greener and carbon-free. Current COVID19 communicable disease has swayed the routine and concurrently influenced regular trends of greenhouse gases (GHG) emissions throughout the world. This study explored the possible GHG emissions (calculated as CO2e) from internal campus commute and purchased electricity consumption from the year 2018–2020 at Universiti Malaysia Perlis main campus to analyze the influence of COVID19 pandemic on its CO2e emission. The average amount of CO2e emitted during pre-COVID19 period (n = 26) was 1,518.8 tCO2e/year while during COVID19 period, it was 1,071.5 tCO2e/year (n = 10), marked as 29.5% reduction. Due to completeness and quality of data for contracted bus (monitoring period of years 2018, 2019 and 2020 as 12 months, 12 months, and 2 months, respectively), year 2019 was determined as the appropriate baseline year for setting the CO2e reduction target due to COVID19 pandemic precedented year. In comparison to pre-COVID19 pandemic, almost 95%/year and 7%/year reductions of CO2e were recorded for both Scope 1 and Scope 2, respectively. Comparing Scope 1 and 2, it was obviously observed that the purchased electricity consumption (Scope 2) was the predominant contributor to GHG emission at UniMAP campus by 78% despite of current pandemic influence and its reduction was indistinct (7%/year reduction). Thus, the reduction target in future should be venturing in energy savings and energy auditing in addition to carbon offsetting. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

12.
Journal of Biostatistics and Epidemiology ; 7(4):403-412, 2021.
Article in English | Scopus | ID: covidwho-1695620

ABSTRACT

Introduction: Handling the COVID-19 outbreak is one of the most novelties modern work is facing by many countries today. Massive outbreak needs countries efficacy and talent in creating new approaches. These approaches need to prevent the spread of the outbreak and increase the citizens' belief as the outbreak will damage the countries' functional capacity. Technical efficiency is used maximally to gain total control of the conditions. This study aims to measure the relative efficiency level of Southeast Asian countries in dealing with COVID-19 pandemic over one year. Methods: The relative efficiency level of the most successful countries in Southeast Asia in managing COVID-19 infection was determined using Frontier 4.1 through Stochastic Frontier Analysis (SFA) and Excel software. The technical efficiency of the SFA model is defined as the ratio of observed output to maximum feasible production. If the country's technical efficiency (TE) is greater than 80%, it is the most effective in Southeast Asia at managing COVID-19 infection, but if it is less than 80% or close to 0, it is inefficient. Results: This research aims at the COVID-19 epidemic in a Southeast Asian country, where the country with the highest technical efficiency score is the most efficient and indicates the country's ability to deal with the COVID-19 outbreak without any complications. Laos was ranked first (TE = 0.99901), with a technical efficiency score that was higher than that of most other Southeast Asian countries. Singapore comes in second position with a technical efficiency score of 0.99882. Brunei is in third place for COVID-19, with a technical efficiency score of 0.99870. Cambodia is in last place, with a score of 0.84675 for technical efficiency. Conclusion: Laos is the highest technical efficiency score among the southeast Asian countries. Various things that can lead to inefficiency include lack of awareness about standard operating procedures (SOP) among the causes of COVID-19 case infection in the workplace, and the community continues to increase. This condition may also be due to the lack of medication or vaccines to cure COVID-19. All communities around the world are expected to adopt standard operating procedures (SOP) such as wearing face masks, hand sanitizers, and social distance to curb the increasingly violent spread of COVID-19. © 2021 Tehran University of Medical Sciences.

13.
1st National Biomedical Engineering Conference, NBEC 2021 ; : 95-99, 2021.
Article in English | Scopus | ID: covidwho-1672839

ABSTRACT

According to the World Health Organization, there are approximately 17.9 million people in the world who will die under the cause of Cardiovascular diseases (CVDs) in 2019. Heart and Brain are both related to Cardiovascular diseases. Even if the patients do not pass away due to the disease, the post-effect of this illness burdens the patients and their families. Also, the outbreak of COVID-19 makes the patients take a risk of undergoing rehabilitation in the hospital. Thus, a smart healthcare solution which is a Smart Healthcare Tracker through the Internet of Things is designed. The system consists of an EMG sensor, accelerometer, gyroscope, and heart rate/pulse oximeter connected to ESP 32 with an interface of NodeMCU to study the patients' health condition for arms and legs strength by sending the data to the caregivers or physicians. The project aimed to obtain a consistent and accurate reading for each of the features for arms and legs strength analysis and sleeping disturbance analysis. The BLYNK app is also applied to the project design as a platform to display the analysis result to the caregivers/physicians on the gadgets at any time and anywhere. The prototype has been constructed and the data collection is built successfully. The prototype is trusted to obtain accurate and consistent results and can provide a sustainable way for the rehabilitation to indicate the health condition and the recovery stage of the patients. © 2021 IEEE.

14.
1st National Biomedical Engineering Conference, NBEC 2021 ; : 146-150, 2021.
Article in English | Scopus | ID: covidwho-1672838

ABSTRACT

COVID-19 and lung diseases have been the major focus of research currently due to the pandemic's reach and effect. Deep Learning (DL) is playing a large role today in various fields from disease classification to drug response identification. The conventional DL method used for images is the Convolutional Neural Network (CNN). A potential method that will replace the usage of CNNs is Transformer specifically Vision Transformers (ViT). This study is a preliminary exploration to determine the performance of using ViT on diseased lungs, COVID-19 infected lungs, and normal lungs. This study was performed on two datasets. The first dataset was a publicly accessible dataset from Iran that has a large cohort of patients. The second dataset was a Malaysian dataset. These images were utilized to verify the usage of ViT and its effectiveness. Images were segregated into several sized patches (16x16, 32x32, 64x64, 128x128, 256x256) pixels. To determine the performance of ViT method, performance metrics of accuracy, sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) and F1-score. From the results of this study, ViT is a promising method with a peak accuracy of 95.36%. © 2021 IEEE.

15.
1st National Biomedical Engineering Conference, NBEC 2021 ; : 151-156, 2021.
Article in English | Scopus | ID: covidwho-1672837

ABSTRACT

This paper presented work on supervised machine learning techniques using K-NN, Linear SVM, Naïve Bayes, Decision Tree (J48), Ada Boost, Bagging and Stacking for the purpose to classify the severity group of covid-19 symptoms. The data was obtained from Kaggle dataset, which was obtained through a survey collected from the participant with varying gender and age that had visited 10 or more countries including China, France, Germany Iran, Italy, Republic of Korean, Spain, UAE, other European Countries (Other-EUR) and Others. The survey is Covid-19 symptom based on guidelines given by the World Health Organization (WHO) and the Ministry of Health and Family Welfare, India which then classified into 4 different levels of severity, Mild, Moderate, Severe, and None. The results from the seven classifiers used in this study showed very low classification results. © 2021 IEEE.

16.
Pediatric Diabetes ; 22(SUPPL 30):33, 2021.
Article in English | EMBASE | ID: covidwho-1571042

ABSTRACT

Introduction: An increase in newly diagnosed type 1 diabetes (T1D) has been posited during the COVID-19 pandemic, but data have been conflicting. Objectives: We aimed to determine trends in newly diagnosed T1D and severity of presentation at diagnosis for pediatric and adolescent patients during COVID-19 year (2020) as compared to the previous year (2019) in a multi-center data analysis across the United States. Methods: This retrospective multi-center study included data from seven large U.S. clinical centers recruited from the T1D Exchange Quality Improvement Collaborative (T1DX-QI). Data on diagnosis, diabetic ketoacidosis (DKA), and clinical characteristics were collected from January 1 to December 31, 2020, compared to the prior year. Chi-square tests were used to compare differences in patient characteristics during the pandemic compared to the pre-pandemic comparison group. Results: Across seven member sites, there were 1399 newly diagnosed patients with T1D in 2020, compared to 1277 in 2019 (p=0.007). Of the newly diagnosed patients, a greater number, presented in DKA in 2020 compared to 2019 (599/1399 (42.8%) v. 493/1277 (38.6%), p<0.001), and a higher proportion of these patients presented with severe DKA (p=0.01) as characterized by a pH<7.1 or bicarbonate of <5mmol/L. The mean age at diagnosis was not different, but there were fewer females (p=0.004), and fewer NH White youth diagnosed in 2020 (p<0.001). Newly diagnosed T1D patients in 2020 were less likely to have private insurance (p=0.001). Monthly data trends demonstrated a higher number of new diagnoses of T1D over the spring and summer months (April to September) of 2020 compared to 2019 (p=0.007). Conclusions: We found an increase in newly diagnosed T1D and a greater proportion of newly diagnosed T1D patients presenting in DKA at diagnosis during the COVID-19 pandemic compared to the prior year. Future longitudinal studies are needed to confirm these findings with population level data and determine the long-term impact of COVID-19 on diabetes trends.

17.
Pediatric Diabetes ; 22(SUPPL 30):35-36, 2021.
Article in English | EMBASE | ID: covidwho-1571032

ABSTRACT

Introduction: Health insurance coverage type differs significantly by socio-economic status and racial groups in the United States. There is limited data on the association between insurance and the risk of adverse outcomes for patients with pre-existing T1D and COVID19. Objectives: The aim of this study was to determine if publicly insured pediatric and adolescent patients with Type 1 Diabetes (T1D) were more likely to experience adverse outcomes compared to privately insured patients with acute COVID-19 infections. Methods: Data from 575 patients with previously established T1D aged <24 years with acute COVID-19 infections was analyzed from the T1DX-COVID-19 Surveillance Registry. Data for the registry was collected from 52 endocrinology clinics across the U.S, using an online survey tool. Each site completed the survey using electronic medical record (EMR) data between April 2020 and May 2021. Results: Privately insured patients were more likely to identify as Non-Hispanic White than publicly insured patients (63% vs 18%, p<0.001). T1D patients with COVID-19 that were on public insurance reported higher A1c (9.5% vs 7.9%, p<0.001), lower insulin pump use (29% vs 62%, p<0.001), as well as lower continuous glucose monitor (CGM) use (51% vs 77%, p<0.001) compared to privately insurance patients. Publicly insured patients with T1D and COVID-19 were three times more likely to be hospitalized than privately insured patients (Odds Ratio 3.4, 95% Confidence Interval: 2.1-5.4). Conclusions: Our data reveals a high rate of hospitalization and DKA among children and adolescents with T1D and COVID19 with public health insurance despite controlling for other potential confounders. This underscores that those on public health insurance are more vulnerable to adverse health outcomes during the COVID19 pandemic. (Table Presented).

18.
Transactions on Maritime Science ; 10(2):383-389, 2021.
Article in English | Scopus | ID: covidwho-1566788

ABSTRACT

Life Buoy, also known as a life preserver, is a crucial safety tool on board any marine ships. The most common and conventional lifesaver is operated manually to save people from drowning, yet this method poses a risk for both the victim and rescuer. Hence, with the help of current technology, a smart lifebuoy has been developed, whereby the rescuer just operates the lifebuoy using remote control. Yet, the existing smart life buoy system has been found heavy and hard to be operated, especially for women, children, and other people with disabilities.This paper focuses on the development of a lightweight smart life buoy system and its characteristics. Arduino Uno R3, Arduino Nano, DC motor 775, Transmitter and Receiver kit were the main components used in the development of the lightweight smart life buoy system (LWSLB). The developed LWSLB system was tested at the National Defence University of Malaysia’ swimming pool due to Covid-19 lockdown, and data such as speed, range of remote connection and battery endurance were obtained. It has been found out that the developed LWSLB weighs just 3.5kg overall compared to Brand S which weighs 13.75kg. However, in terms of speed, Brand S proves to be faster at 4.17m/s compared to LWSLB which exhibits a speed of 1.25m/s. © 2021, Faculty of Maritime Studies. All rights reserved.

19.
Comput Biol Med ; 139: 104957, 2021 12.
Article in English | MEDLINE | ID: covidwho-1525748

ABSTRACT

A substantial impediment to widespread Coronavirus disease (COVID-19) vaccination is vaccine hesitancy. Many researchers across scientific disciplines have presented countless studies in favor of COVID-19 vaccination, but misinformation on social media could hinder vaccination efforts and increase vaccine hesitancy. Nevertheless, studying people's perceptions on social media to understand their sentiment presents a powerful medium for researchers to identify the causes of vaccine hesitancy and therefore develop appropriate public health messages and interventions. To the best of the authors' knowledge, previous studies have presented vaccine hesitancy in specific cases or within one scientific discipline (i.e., social, medical, and technological). No previous study has presented findings via sentiment analysis for multiple scientific disciplines as follows: (1) social, (2) medical, public health, and (3) technology sciences. Therefore, this research aimed to review and analyze articles related to different vaccine hesitancy cases in the last 11 years and understand the application of sentiment analysis on the most important literature findings. Articles were systematically searched in Web of Science, Scopus, PubMed, IEEEXplore, ScienceDirect, and Ovid from January 1, 2010, to July 2021. A total of 30 articles were selected on the basis of inclusion and exclusion criteria. These articles were formed into a taxonomy of literature, along with challenges, motivations, and recommendations for social, medical, and public health and technology sciences. Significant patterns were identified, and opportunities were promoted towards the understanding of this phenomenon.


Subject(s)
COVID-19 Vaccines , COVID-19 , Humans , SARS-CoV-2 , Vaccination
20.
Review of International Geographical Education Online ; 11(7):1225-1230, 2021.
Article in English | Scopus | ID: covidwho-1518966

ABSTRACT

Covid-19 is a pandemic that has been declared by the World Health Organization (WHO) as a pandemic that has claimed many lives around the world. As of January 1, 2021, the world has recorded at least two million infected victims. Implementing the movement control order is one of the best ways implemented by the government today in curbing the Covid-19 epidemic until a vaccine is available. The method of discussion found in this article is based on document analysis by referring to authoritative books, journals, articles, and websites. The study’s findings found that the Movement Control Order implemented by the Malaysian government is based on ‘Siyasah Syar’iyyah’ in maintaining and curbing the spread of Covid-19 in Malaysia. © 2021. RIGEO • 11(7), SPRING. All Rights Reserved.

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