Browsing by Author "Khalil Ibrahim, Mohamed"

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    Detecting Asteroids and Comets using Machine Learning and Deep Learning
    (October university for modern sciences and Arts MSA, 2023) Khalil Ibrahim, Mohamed; Said, M.; M. El-Sedfy, S.; Khaled, M.; Ibrahim, A.; Abdellah, N. N. Khaled
    Asteroids and comets are potentially hazardous objects that may make close approaches and enter into Earth's orbit. Detecting and tracking asteroids and comets is a global challenge. Machine learning and deep learning are powerful tools that can be used to observe such hazardous objects early to protect our planet from any future impact. In this paper, we attempt to present a concise review on using machine learning and deep learning in tracking asteroids and comets.
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    Mathematical Modelling of Fractional-order Covid-19 Pandemic With Memory Effect: A Review
    (October university for modern sciences and Arts MSA, 2023) Khalil Ibrahim, Mohamed; Said, M.; El-Sedfy, S. M.; Khaled, M.; Ibrahim, A.; Abdellah, N.; Khaled, N.
    Mathematical models with memory effect play an important role in the field of epidemiology. The fractional-order derivatives are powerful tools to characterize the memory effect in the dynamical systems of infectious diseases. Hence, we attempt to present a systematic survey on the fractional-order compartmental models of Covid-19 pandemic to explain how the fractional-order models have been employed to study and forecast the spread of Covid-19 pandemic. Such non-integer order models can help decision makers in control programs to put strategic plans to control Covid-19 outbreakMathematical models with memory effect play an important role in the field of epidemiology. The fractional-order derivatives are powerful tools to characterize the memory effect in the dynamical systems of infectious diseases. Hence, we attempt to present a systematic survey on the fractional-order compartmental models of Covid-19 pandemic to explain how the fractional-order models have been employed to study and forecast the spread of Covid-19 pandemic. Such non-integer order models can help decision makers in control programs to put strategic plans to control Covid-19 outbreak