Zubair Md. Fadlullah
Lakehead University
178 Papers
745 Citations
Zubair Md. Fadlullah is an academic researcher from Lakehead University. The author has contributed to research in topics: Computer science & Smart grid. The author has an hindex of 34, co-authored 118 publications. Previous affiliations of Zubair Md. Fadlullah include Tohoku University & Xidian University.
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Papers
An Intelligent Packet Forwarding Approach for Disaster Recovery Networks
Bomin Mao,Fengxiao Tang,Zubair Md. Fadlullah,Nei Kato +3 more
- 20 May 2019
TL;DR: This paper utilizes the deep reinforcement learning technique to propose a self-adaptive routing method for the Movable and Deployable Resource Unit (MDRU) based backbone network that can adapt to the sudden network errors.
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A Two-Step Machine Learning Model for Stage-Specific Disease Survivability Prediction
Aya M. I. Farrag,Zubair Md. Fadlullah,Mostafa M. Fouda +2 more
- 24 Nov 2022
TL;DR: Zhang et al. as mentioned in this paper combined two main strategies in solving the breast cancer survivability prediction problem using Machine Learning techniques, namely classification and regression, to predict whether or not a patient will survive for five years.
3
Joint design of density of access points and partially overlapped channel assignment for capacity optimization in wireless networks
Wei Zhao,Zubair Md. Fadlullah,Hiroki Nishiyama,Nei Kato,Kiyoshi Hamaguchi +4 more
- 22 Dec 2014
TL;DR: This paper derives the existence of the upper bound of the density of APs with POCs, and models the POC assignment to the deployed APs from a novel perspective, and computer-based simulations are conducted to demonstrate the effectiveness of the proposal.
3
Security Challenge in the Smart Grid
Zubair Md. Fadlullah,Nei Kato +1 more
- 01 Jan 2015
TL;DR: This chapter discusses a light-weight message authentication method for securing communication among various smart meters at different points of the smart grid based on the Diffie–Hellman key establishment protocol and hash-based message authentication code.
3
Automated EEG Epileptic Seizure Detection Exploiting Continuous Morlet Wavelet Transform Scalograms and Hybrid Deep Learning Models
Antora Dev,Mostafa M. Fouda,Zubair Md. Fadlullah +2 more
- 28 Nov 2023
TL;DR: This study ventures into transforming an Electroencephalogram signal dataset into Continuous Morlet Wavelet Transform (CMWT) scalograms of the signals processed into four distinct resolutions: 32x32, 48x48, 64x64, and 128x128.
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