activity
20182020
most citedA Comprehensive Review of Wind Energy in Malaysia: Past, Present and Future Research Trends

33 citations · 33 across the 2 of their papers we have counts for

collaborators

7 papers

eess.SP2020

Lightning Mapping: Techniques, Challenges, and Opportunities

Ammar Alammari, Ammar Ahmed Alkahtani, Mohd Riduan Ahmad +4

Despite the significant progress made in studying the lightning phenomenon, precise location and mapping of its occurrence remain a challenge. Lightning mapping can be determined b…

eess.SP2020

Wind Data Analysis for Assessing the Potential of Off-Grid Direct EV Charging Stations

Fuad Noman, Ammar Al-Kahtani, Vassilios Agelidis +1

The integration of large-scale wind farms and large-scale charging stations for electric vehicles with the electricity grids necessitate energy storage support for both technologie…

eess.SY202033 cited

A Comprehensive Review of Wind Energy in Malaysia: Past, Present and Future Research Trends

Fuad Noman, Gamal Alkawsi, Dallatu Abbas +3

Wind energy has gained a huge interest in the recent years in various countries due to the high demand of energy and the shortage of traditional electricity sources. This is becaus…

eess.SP2020

Kalman Filter and Wavelet Cross-correlation for VHF Broadband Interferometer Lightning Mapping

Ammar Alammari, Ammar Alkahtani, Mohd Riduan +7

A lightning mapping system based on perpendicular crossed baseline interferometer (ITF) technology has been developed rapidly in recent years. Several processing methods have been…

cs.LG2019

Classification of EEG-Based Brain Connectivity Networks in Schizophrenia Using a Multi-Domain Connectome Convolutional Neural Network

Chun-Ren Phang, Chee-Ming Ting, Fuad Noman +1

We exploit altered patterns in brain functional connectivity as features for automatic discriminative analysis of neuropsychiatric patients. Deep learning methods have been introdu…

cs.SD2018

Short-segment heart sound classification using an ensemble of deep convolutional neural networks

Fuad Noman, Chee-Ming Ting, Sh-Hussain Salleh +1

This paper proposes a framework based on deep convolutional neural networks (CNNs) for automatic heart sound classification using short-segments of individual heart beats. We desig…