Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 17 of 17
Full-Text Articles in Entire DC Network
Machine Learning Techniques For The Identification Of Risk Factors Associated With Food Insecurity Among Adults In Arab Countries During The Covid-19 Pandemic, Radwan Qasrawi, Maha Hoteit, Reema Tayyem, Khlood Bookari, Haleama Al Sabbah, Iman Kamel, Somaia Dashti, Sabika Allehdan, Hiba Bawadi, Mostafa Waly, Mohammed O. Ibrahim, Stephanny Vicuna Polo, Diala Abu Al-Halawa
Machine Learning Techniques For The Identification Of Risk Factors Associated With Food Insecurity Among Adults In Arab Countries During The Covid-19 Pandemic, Radwan Qasrawi, Maha Hoteit, Reema Tayyem, Khlood Bookari, Haleama Al Sabbah, Iman Kamel, Somaia Dashti, Sabika Allehdan, Hiba Bawadi, Mostafa Waly, Mohammed O. Ibrahim, Stephanny Vicuna Polo, Diala Abu Al-Halawa
All Works
BACKGROUND: A direct consequence of global warming, and strongly correlated with poor physical and mental health, food insecurity is a rising global concern associated with low dietary intake. The Coronavirus pandemic has further aggravated food insecurity among vulnerable communities, and thus has sparked the global conversation of equal food access, food distribution, and improvement of food support programs. This research was designed to identify the key features associated with food insecurity during the COVID-19 pandemic using Machine learning techniques. Seven machine learning algorithms were used in the model, which used a dataset of 32 features. The model was designed to …
Artificial Intelligence Tool For The Study Of Covid-19 Microdroplet Spread Across The Human Diameter And Airborne Space, Hesham H. Alsaadi, Monther Aldwairi, Faten Yasin, Sandra C.P. Cachinho, Abdullah Hussein
Artificial Intelligence Tool For The Study Of Covid-19 Microdroplet Spread Across The Human Diameter And Airborne Space, Hesham H. Alsaadi, Monther Aldwairi, Faten Yasin, Sandra C.P. Cachinho, Abdullah Hussein
All Works
The 2019 novel coronavirus (SARS-CoV-2 / COVID-19), with a point of origin in Wuhan, China, has spread rapidly all over the world. It turned into a raging pandemic wrecking havoc on health care facilities, world economy and affecting everyone’s life to date. With every new variant, rate of transmission, spread of infections and the number of cases continues to rise at an international level and scale. There are limited reliable researches that study microdroplets spread and transmissions from human sneeze or cough in the airborne space. In this paper, we propose an intelligent technique to visualize, detect, measure the distance …
Intelligent Health Care And Diseases Management System: Multi-Day-Ahead Predictions Of Covid-19, Ahed Abugabah, Farah Shahid
Intelligent Health Care And Diseases Management System: Multi-Day-Ahead Predictions Of Covid-19, Ahed Abugabah, Farah Shahid
All Works
The rapidly growing number of COVID-19 infected and death cases has had a catastrophic worldwide impact. As a case study, the total number of death cases in Algeria is over two thousand people (increased with time), which drives us to search its possible trend for early warning and control. In this paper, the proposed model for making a time-series forecast for daily and total infected cases, death cases, and recovered cases for the countrywide Algeria COVID-19 dataset is a two-layer dropout gated recurrent unit (TDGRU). Four performance parameters were used to assess the model’s performance: mean absolute error (MAE), root …
Covid-19 Pandemic And The Cyberthreat Landscape: Research Challenges And Opportunities, Heba Saleous, Muhusina Ismail, Saleh H. Aldaajeh, Nisha Madathil, Saed Alrabaee, Kim Kwang Raymond Choo, Nabeel Al-Qirim
Covid-19 Pandemic And The Cyberthreat Landscape: Research Challenges And Opportunities, Heba Saleous, Muhusina Ismail, Saleh H. Aldaajeh, Nisha Madathil, Saed Alrabaee, Kim Kwang Raymond Choo, Nabeel Al-Qirim
All Works
Although cyber technologies benefit our society, there are also some related cybersecurity risks. For example, cybercriminals may exploit vulnerabilities in people, processes, and technologies during trying times, such as the ongoing COVID-19 pandemic, to identify opportunities that target vulnerable individuals, organizations (e.g., medical facilities), and systems. In this paper, we examine the various cyberthreats associated with the COVID-19 pandemic. We also determine the attack vectors and surfaces of cyberthreats. Finally, we will discuss and analyze the insights and suggestions generated by different cyberattacks against individuals, organizations, and systems.
3d Indoor Modeling And Game Theory Based Navigation For Pre And Post Covid-19 Situation, Jaiteg Singh, Noopur Tyagi, Saravjeet Singh, Babar Shah, Farman Ali, Ahmad Ali Alzubi, Abdulrhman Alkhanifer
3d Indoor Modeling And Game Theory Based Navigation For Pre And Post Covid-19 Situation, Jaiteg Singh, Noopur Tyagi, Saravjeet Singh, Babar Shah, Farman Ali, Ahmad Ali Alzubi, Abdulrhman Alkhanifer
All Works
The COVID-19 pandemic has greatly affected human behavior, creating a need for individuals to be more cautious about health and safety protocols. People are becoming more aware of their surroundings and the importance of minimizing the risk of exposure to potential sources of infection. This shift in mindset is particularly important in indoor environments, especially hospitals, where there is a greater risk of virus transmission. The implementation of route planning in these areas, aimed at minimizing interaction and exposure, is crucial for positively influencing individual behavior. Accurate maps of buildings help provide location-based services, prepare for emergencies, and manage infrastructural …
Of Stances, Themes, And Anomalies In Covid-19 Mask-Wearing Tweets, Jwen Fai Low, Benjamin C.M. Fung, Farkhund Iqbal, Ebrahim Bagheri
Of Stances, Themes, And Anomalies In Covid-19 Mask-Wearing Tweets, Jwen Fai Low, Benjamin C.M. Fung, Farkhund Iqbal, Ebrahim Bagheri
All Works
COVID-19 is an opportunity to study public acceptance of a ‘‘new’’ healthcare intervention, universal masking, which unlike vaccination, is mostly alien to the Anglosphere public despite being practiced in ages past. Using a collection of over two million tweets, we studied the ways in which proponents and opponents of masking vied for influence as well as the themes driving the discourse. Pro-mask tweets encouraging others to mask up dominated Twitter early in the pandemic though its continued dominance has been eroded by anti-mask tweets criticizing others for their masking behavior. Engagement, represented by the counts of likes, retweets, and replies, …
Air Quality Improvement Following Covid-19 Lockdown Measures And Projected Benefits For Environmental Health, Yuei An Liou, Trong Hoang Vo, Kim Anh Nguyen, James P. Terry
Air Quality Improvement Following Covid-19 Lockdown Measures And Projected Benefits For Environmental Health, Yuei An Liou, Trong Hoang Vo, Kim Anh Nguyen, James P. Terry
All Works
Many regions worldwide suffer from heavy air pollution caused by particulate matter (PM2.5) and nitrogen dioxide (NO2), resulting in a huge annual disease burden and significant welfare costs. Following the outbreak of the COVID-19 global pandemic, enforced curfews and restrictions on human mobility (so-called periods of ‘lockdown’) have become important measures to control the spread of the virus. This study aims to investigate the improvement in air quality following COVID-19 lockdown measures and the projected benefits for environmental health. China was chosen as a case study. The work projects annual premature deaths and welfare costs by integrating PM2.5 and NO2 …
Smartphone Usage Before And During Covid-19: A Comparative Study Based On Objective Recording Of Usage Data, Khansa Chemnad, Sameha Alshakhsi, Mohamed Basel Almourad, Majid Altuwairiqi, Keith Phalp, Raian Ali
Smartphone Usage Before And During Covid-19: A Comparative Study Based On Objective Recording Of Usage Data, Khansa Chemnad, Sameha Alshakhsi, Mohamed Basel Almourad, Majid Altuwairiqi, Keith Phalp, Raian Ali
All Works
Most studies that claimed changes in smartphone usage during COVID-19 were based on self-reported usage data, e.g., that collected through a questionnaire. These studies were also limited to reporting the overall smartphone usage, with no detailed investigation of distinct types of apps. The current study investigated smartphone usage before and during COVID-19. Our study used a dataset from a smartphone app that objectively logged users’ activities, including apps accessed and each app session start and end time. These were collected during two periods: pre-COVID-19 (161 individuals with 77 females) and during COVID-19 (251 individuals with 159 females). We report on …
Predicting The Level Of Respiratory Support In Covid-19 Patients Using Machine Learning, Hisham Abdeltawab, Fahmi Khalifa, Yaser Elnakieb, Ahmed Elnakib, Fatma Taher, Norah Saleh Alghamdi, Harpal Singh Sandhu, Ayman El-Baz
Predicting The Level Of Respiratory Support In Covid-19 Patients Using Machine Learning, Hisham Abdeltawab, Fahmi Khalifa, Yaser Elnakieb, Ahmed Elnakib, Fatma Taher, Norah Saleh Alghamdi, Harpal Singh Sandhu, Ayman El-Baz
All Works
In this paper, a machine learning-based system for the prediction of the required level of respiratory support in COVID-19 patients is proposed. The level of respiratory support is divided into three classes: class 0 which refers to minimal support, class 1 which refers to non-invasive support, and class 2 which refers to invasive support. A two-stage classification system is built. First, the classification between class 0 and others is performed. Then, the classification between class 1 and class 2 is performed. The system is built using a dataset collected retrospectively from 3491 patients admitted to tertiary care hospitals at the …
Role Of Imaging And Ai In The Evaluation Of Covid-19 Infection: A Comprehensive Survey, Mayada Elgendy, Hossam Magdy Balaha, Mohamed Shehata, Ahmed Alksas, Mahitab Ghoneim, Fatma Sherif, Ali Mahmoud, Ahmed Elgarayhi, Fatma Taher, Mohammed Sallah, Mohammed Ghazal, Ayman El-Baz
Role Of Imaging And Ai In The Evaluation Of Covid-19 Infection: A Comprehensive Survey, Mayada Elgendy, Hossam Magdy Balaha, Mohamed Shehata, Ahmed Alksas, Mahitab Ghoneim, Fatma Sherif, Ali Mahmoud, Ahmed Elgarayhi, Fatma Taher, Mohammed Sallah, Mohammed Ghazal, Ayman El-Baz
All Works
Coronavirus disease 2019 (COVID-19) is a respiratory illness that started and rapidly became the pandemic of the century, as the number of people infected with it globally exceeded 253.4 million. Since the beginning of the pandemic of COVID-19, over two years have passed. During this hard period, several defies have been coped by the scientific society to know this novel disease, evaluate it, and treat affected patients. All these efforts are done to push back the spread of the virus. This article provides a comprehensive review to learn about the COVID-19 virus and its entry mechanism, its main repercussions on …
Sel-Covidnet: An Intelligent Application For The Diagnosis Of Covid-19 From Chest X-Rays And Ct-Scans, Ahmad Al Smadi, Ahed Abugabah, Ahmad Mohammad Al-Smadi, Sultan Almotairi
Sel-Covidnet: An Intelligent Application For The Diagnosis Of Covid-19 From Chest X-Rays And Ct-Scans, Ahmad Al Smadi, Ahed Abugabah, Ahmad Mohammad Al-Smadi, Sultan Almotairi
All Works
COVID-19 detection from medical imaging is a difficult challenge that has piqued the interest of experts worldwide. Chest X-rays and computed tomography (CT) scanning are the essential imaging modalities for diagnosing COVID-19. All researchers focus their efforts on developing viable methods and rapid treatment procedures for this pandemic. Fast and accurate automated detection approaches have been devised to alleviate the need for medical professionals. Deep Learning (DL) technologies have successfully recognized COVID-19 situations. This paper proposes a developed set of nine deep learning models for diagnosing COVID-19 based on transfer learning and implementation in a novel architecture (SEL-COVIDNET). In which …
Interpretable Deep Learning For The Prediction Of Icu Admission Likelihood And Mortality Of Covid-19 Patients, Amril Nazir, Hyacinth Kwadwo Ampadu
Interpretable Deep Learning For The Prediction Of Icu Admission Likelihood And Mortality Of Covid-19 Patients, Amril Nazir, Hyacinth Kwadwo Ampadu
All Works
The global healthcare system is being overburdened by an increasing number of COVID-19 patients. Physicians are having difficulty allocating resources and focusing their attention on high-risk patients, partly due to the difficulty in identifying high-risk patients early. COVID-19 hospitalizations require specialized treatment capabilities and can cause a burden on healthcare resources. Estimating future hospitalization of COVID-19 patients is, therefore, crucial to saving lives. In this paper, an interpretable deep learning model is developed to predict intensive care unit (ICU) admission and mortality of COVID-19 patients. The study comprised of patients from the Stony Brook University Hospital, with patient information such …
A Non-Invasive Interpretable Diagnosis Of Melanoma Skin Cancer Using Deep Learning And Ensemble Stacking Of Machine Learning Models, Iftiaz A. Alfi, Mahfuzur Rahman, Mohammad Shorfuzzaman, Amril Nazir
A Non-Invasive Interpretable Diagnosis Of Melanoma Skin Cancer Using Deep Learning And Ensemble Stacking Of Machine Learning Models, Iftiaz A. Alfi, Mahfuzur Rahman, Mohammad Shorfuzzaman, Amril Nazir
All Works
A skin lesion is a portion of skin that observes abnormal growth compared to other areas of the skin. The ISIC 2018 lesion dataset has seven classes. A miniature dataset version of it is also available with only two classes: malignant and benign. Malignant tumors are tumors that are cancerous, and benign tumors are non-cancerous. Malignant tumors have the ability to multiply and spread throughout the body at a much faster rate. The early detection of the cancerous skin lesion is crucial for the survival of the patient. Deep learning models and machine learning models play an essential role in …
The Role Of 3d Ct Imaging In The Accurate Diagnosis Of Lung Function In Coronavirus Patients, Ibrahim Shawky Farahat, Ahmed Sharafeldeen, Mohamed Elsharkawy, Ahmed Soliman, Ali Mahmoud, Mohammed Ghazal, Fatma Taher, Maha Bilal, Ahmed Abdel Khalek Abdel Razek, Waleed Aladrousy, Samir Elmougy, Ahmed Elsaid Tolba, Moumen El-Melegy, Ayman El-Baz
The Role Of 3d Ct Imaging In The Accurate Diagnosis Of Lung Function In Coronavirus Patients, Ibrahim Shawky Farahat, Ahmed Sharafeldeen, Mohamed Elsharkawy, Ahmed Soliman, Ali Mahmoud, Mohammed Ghazal, Fatma Taher, Maha Bilal, Ahmed Abdel Khalek Abdel Razek, Waleed Aladrousy, Samir Elmougy, Ahmed Elsaid Tolba, Moumen El-Melegy, Ayman El-Baz
All Works
Early grading of coronavirus disease 2019 (COVID-19), as well as ventilator support machines, are prime ways to help the world fight this virus and reduce the mortality rate. To reduce the burden on physicians, we developed an automatic Computer-Aided Diagnostic (CAD) system to grade COVID-19 from Computed Tomography (CT) images. This system segments the lung region from chest CT scans using an unsupervised approach based on an appearance model, followed by 3D rotation invariant Markov–Gibbs Random Field (MGRF)-based morphological constraints. This system analyzes the segmented lung and generates precise, analytical imaging markers by estimating the MGRF-based analytical potentials. Three Gibbs …
The Use Of Mobile Payment Systems In Post-Covid-19 Economic Recovery: Primary Research On An Emerging Market For Experience Goods, Maiya M. Suyunchaliyeva, Raghav Nautiyal, Aijaz A. Shaikh, Ravishankar Sharma
The Use Of Mobile Payment Systems In Post-Covid-19 Economic Recovery: Primary Research On An Emerging Market For Experience Goods, Maiya M. Suyunchaliyeva, Raghav Nautiyal, Aijaz A. Shaikh, Ravishankar Sharma
All Works
This study investigated whether mobile payment services could drive post-COVID-19 pandemic recovery in the ‘experience goods’ sector (e.g., tourism) utilising Bandura’s self-efficacy or social cognitive theory. It explored the factors influencing the intention to continue using mobile payment services and the intention to recommend these to others. An empirical survey was conducted to assess the study variables, and the data obtained therefrom were analysed using the industry-standard Cross-Industry Standard Process for Data Mining method. The study results suggest that personal innovativeness and perceived trust influence consumers’ intention to continue using mobile payment services and that perceived trust, personal innovativeness and …
Active Learning Strategy For Covid-19 Annotated Dataset, Amril Nazir, Ricky Maulana Fajri
Active Learning Strategy For Covid-19 Annotated Dataset, Amril Nazir, Ricky Maulana Fajri
All Works
The efficient diagnosis of COVID-19 plays a key role in preventing its spread. Recently, many artificial intelligence techniques, such as the deep neural network approach, have been implemented to help efficient diagnosis of COVID-19. However, the accurate performance of deep learning depends on the tuning of many hyperparameters and a large amount of labeled data. This COVID-19 data bottleneck also leads to insufficient human resources for data labeling, which presents a challenging obstacle. In this paper, a novel discriminative batch-mode active learning (DS3) is proposed to allow faster and more effective COVID-19 data annotation. The framework specifically designed to suit …
Digital Transformation In Higher Education: A Framework For Maturity Assessment, Adam Marks, Maytha Al-Ali, Reem Atassi, Abedallah Zaid Abualkishik, Yacine Rezgui
Digital Transformation In Higher Education: A Framework For Maturity Assessment, Adam Marks, Maytha Al-Ali, Reem Atassi, Abedallah Zaid Abualkishik, Yacine Rezgui
All Works
© 2020 Science and Information Organization. All rights reserved. —Literature in digital transformation maturity is scarce. Digital transformation in higher education, especially after COVID-19 is seen as inevitable. This research explores digital transformation maturity and challenges within Higher Education. The significance of this study stems from the role digital transformation plays in today’s knowledge economy. This study proposes a new framework based on Deloitte’s 2019 digital transformation assessment framework with Petkovic 2014 mega and major higher education process mapping. The study triangulates the findings of multiple research instruments, including survey, interviews, case study, and direct observation. The research findings show …