87 citations · 144 across the 6 of their papers we have counts for
8 papers
Spatiotemporal Data Mining: A Survey on Challenges and Open Problems
Ali Hamdi, Khaled Shaban, Abdelkarim Erradi +3
Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay between space and time. Several available surveys capture STDM advances and report a wealth o…
Spatiotemporal Tensor Completion for Improved Urban Traffic Imputation
Ahmed Ben Said, Abdelkarim Erradi
Effective management of urban traffic is important for any smart city initiative. Therefore, the quality of the sensory traffic data is of paramount importance. However, like any s…
A deep-learning model for evaluating and predicting the impact of lockdown policies on COVID-19 cases
Ahmed Ben Said, Abdelkarim Erradi, Hussein Aly +1
To reduce the impact of COVID-19 pandemic most countries have implemented several counter-measures to control the virus spread including school and border closing, shutting down pu…
Predicting COVID-19 cases using Bidirectional LSTM on multivariate time series
Ahmed Ben Said, Abdelkarim Erradi, Hussein Aly +1
Background: To assist policy makers in taking adequate decisions to stop the spread of COVID-19 pandemic, accurate forecasting of the disease propagation is of paramount importance…
Model-Based Risk Assessment for Cyber Physical Systems Security
Ashraf Tantawy, Abdelkarim Erradi, Sherif Abdelwahed +1
Traditional techniques for Cyber-Physical Systems (CPS) security design either treat the cyber and physical systems independently, or do not address the specific vulnerabilities of…
Deep-Gap: A deep learning framework for forecasting crowdsourcing supply-demand gap based on imaging time series and residual learning
Ahmed Ben Said, Abdelkarim Erradi
Mobile crowdsourcing has become easier thanks to the widespread of smartphones capable of seamlessly collecting and pushing the desired data to cloud services. However, the success…