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A Greedy Layer-Wise Learning Algorithm for Open-Circuit Fault Diagnosis of Grid-Connected Inverters
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
This paper introduces a greedy layer-wise learning algorithm to diagnose open-circuit faults of grid-connected inverters. Inverters play important roles in energy conversion, especially when converting direct current to ...
Flow-based intrusion detection algorithm for supervisory control and data acquisition systems: A real-time approach
(
John Wiley and Sons Inc
, 2021 , Article)
Intrusion detection in supervisory control and data acquisition (SCADA) systems is integral because of the critical roles of these systems in industries. However, available approaches in the literature lack representative ...
A Deep Reinforcement Learning Framework for Data Compression in Uplink NOMA-SWIPT Systems
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
<comment< Non-orthogonal multiple access (NOMA) shall play an important role in the current and foreseeable design of 5G and beyond networks. NOMA allows multiple users to share the same time-frequency ...
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 ...
On Designing Smart Agents for Service Provisioning in Blockchain-powered Systems
(
IEEE Computer Society
, 2021 , Article)
Service provisioning systems assign users to service providers according to allocation criteria that strike an optimal trade-off between users Quality of Experience (QoE) and the operation cost endured by providers. These ...
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 ...
I-SEE: Intelligent, Secure, and Energy-Efficient Techniques for Medical Data Transmission Using Deep Reinforcement Learning
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
The rapid evolution of remote health monitoring applications is foreseen to be a crucial solution for facing an unpredictable health crisis and improving the quality of life. However, such applications come with many ...
Reinforcement learning approaches for efficient and secure blockchain-powered smart health systems
(
Elsevier B.V.
, 2021 , Article)
Emerging technological innovation toward e-Health transition is a worldwide priority for ensuring people's quality of life. Hence, secure exchange and analysis of medical data amongst diverse organizations would increase ...
Smart and Secure Blockchain-based Healthcare System Using Deep Q-Learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Healthcare is one of the top priorities in modern society to provide better health facilities. Therefore, investments in health care systems increased rapidly, aligned with the population growth rate. Besides, the data ...
A Deep Learning Model for LoRa Signals Classification Using Cyclostationay Features
(
IEEE Computer Society
, 2021 , Conference Paper)
With the witnessed exponential growth of Internet of Things (IoT) nodes deployment following the emerging applications, multiple variants of technologies have been proposed to handle the IoT requirements. Among the proposed ...