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Machine learning-based management of electric vehicles charging: Towards highly-dispersed fast chargers
(
MDPI AG
, 2020 , Article)
Coordinated charging of electric vehicles (EVs) improves the overall efficiency of the power grid as it avoids distribution system overloads, increases power quality, and decreases voltage fluctuations. Moreover, the ...
Optimal User-Edge Assignment in Hierarchical Federated Learning Based on Statistical Properties and Network Topology Constraints
(
IEEE Computer Society
, 2022 , Article)
Distributed learning algorithms aim to leverage distributed and diverse data stored at users' devices to learn a global phenomena by performing training amongst participating devices and periodically aggregating their local ...
Long-term performance analysis and power prediction of PV technology in the State of Qatar
(
Elsevier Ltd
, 2017 , Article)
?Solar photovoltaic (PV) energy in GCC?- the term seems convincing to many solar PV industries due to high solar exposure in GCC region. However, long-term effects such as dust accumulation and seasonal variation are major ...
Energy-efficient networks selection based deep reinforcement learning for heterogeneous health systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Smart health systems improve the existing health services by integrating information and technology into health and medical practices. However, smart healthcare systems are facing major challenges including limited network ...
Information sharing in cooperative networks: A generic trustworthy issue
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
In a cooperative network, users share information with each other to achieve a common target. Due to the concerns of privacy and cost, users may be reluctant to share genuine information with each other, which incurs the ...
RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Due to their high computational and memory demand, deep learning applications are mainly restricted to high-performance units, e.g., cloud and edge servers. Particularly, in Internet of Things (IoT) systems, the data ...
Image Steganography: A Review of the Recent Advances
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Image Steganography is the process of hiding information which can be text, image or video inside a cover image. The secret information is hidden in a way that it not visible to the human eyes. Deep learning technology, ...
Machine Learning Based Cloud Computing Anomalies Detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Recently, machine learning algorithms have been proposed to design new security systems for anomalies detection as they exhibit fast processing with real-time predictions. However, one of the major challenges in machine ...
Real-time throughput prediction for cognitive Wi-Fi networks
(
Academic Press
, 2020 , Article)
Wi-Fi as a wireless networking technology has become a widely acceptable commonplace. Over the course of time, the applications landscape of Wi-Fi networks is growing tremendously. The proliferation of new services is ...
Deep Reinforcement Learning for Network Selection over Heterogeneous Health Systems
(
IEEE Computer Society
, 2022 , Article)
Smart health systems improve our quality oflife by integrating diverse information and technologies into health and medical practices. Such technologies can significantly improve the existing health services. However, ...