Experimental setup for online fault diagnosis of induction machines via promising IoT and machine learning: Towards industry 4.0 empowerment
In recent years, the internet of things (IoT) represents the main core of Industry 4.0 for cyber-
physic systems (CPS) in order to improve the industrial environment. Accordingly, the …
physic systems (CPS) in order to improve the industrial environment. Accordingly, the …
A game-based deep reinforcement learning approach for energy-efficient computation in MEC systems
Many previous energy-efficient computation optimization works for mobile edge computing
(MEC) systems have been based on the assumption of synchronous offloading, where all …
(MEC) systems have been based on the assumption of synchronous offloading, where all …
Role of machine learning and deep learning in securing 5G-driven industrial IoT applications
Abstract The Internet of Things (IoT) connects millions of computing devices and has set a
stage for future technology where industrial use cases like smart cities and smart houses will …
stage for future technology where industrial use cases like smart cities and smart houses will …
Robust fault recognition and correction scheme for induction motors using an effective IoT with deep learning approach
Maintaining electrical machines in good working order and increasing their life expectancy
is one of the main challenges. Precocious and accurate detection of faults is crucial to this …
is one of the main challenges. Precocious and accurate detection of faults is crucial to this …
Computational intelligence intrusion detection techniques in mobile cloud computing environments: Review, taxonomy, and open research issues
S Shamshirband, M Fathi, AT Chronopoulos… - Journal of Information …, 2020 - Elsevier
With the increasing utilization of the Internet and its provided services, an increase in cyber-
attacks to exploit the information occurs. A technology to store and maintain user's …
attacks to exploit the information occurs. A technology to store and maintain user's …
Cryptocurrency malware hunting: A deep recurrent neural network approach
In recent years, cryptocurrency trades have increased dramatically, and this trend has
attracted cyber-threat actors to exploit the existing vulnerabilities and infect their targets. The …
attracted cyber-threat actors to exploit the existing vulnerabilities and infect their targets. The …
A deep reinforcement learning based offloading game in edge computing
Edge computing is a new paradigm to provide strong computing capability at the edge of
pervasive radio access networks close to users. A critical research challenge of edge …
pervasive radio access networks close to users. A critical research challenge of edge …
Dynamic offloading for multiuser muti-CAP MEC networks: A deep reinforcement learning approach
In this paper, we study a multiuser mobile edge computing (MEC) network, where tasks from
users can be partially offloaded to multiple computational access points (CAPs). We …
users can be partially offloaded to multiple computational access points (CAPs). We …
A systematic review on Deep Learning approaches for IoT security
The constant spread of smart devices in many aspects of our daily life goes hand in hand
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …
IoT vulnerability assessment for sustainable computing: threats, current solutions, and open challenges
Over the last few decades, sustainable computing has been widely used in areas like social
computing, artificial intelligence-based agent systems, mobile computing, and Internet of …
computing, artificial intelligence-based agent systems, mobile computing, and Internet of …