Computer applications have considerably shifted from single data processing to machine
learning in recent years due to the accessibility and availability of massive volumes of data …

In recent years, machine learning (ML) and deep learning (DL) have been the leading
approaches to solving various challenges, such as disease predictions, drug discovery …

Network security becomes indispensable to our daily interactions and networks. As attackers
continue to develop new types of attacks and the size of networks continues to grow, the …

The widespread deployment of the Internet of Things (IoT) into critical sectors such as
industrial and manufacturing has resulted in the Industrial Internet of Things (IIoT). The IIoT …

Logical analysis of data (LAD), an approach to data analysis based on Boolean functions,
combinatorics, and optimization, can be considered one of the methods of interpretable …

Several sectors have embraced Cloud Computing (CC) due to its inherent characteristics,
such as scalability and flexibility. However, despite these advantages, security concerns …

Recently, networks are moving toward automation and getting more and more intelligent.
With the advent of big data and cloud computing technologies, lots and lots of data are being …

The rise of Vehicular Ad-hoc Networks (VANETs) has led to the growing significance in
intelligent transportation systems. This research suggests a deep learning model for …

Digital twins (DTs) are an emerging digitalization technology with a huge impact on today's
innovations in both industry and research. DTs can significantly enhance our society and …

In order to achieve collision-free path planning in complex environment, Munchausen deep
Q-learning network (M-DQN) is applied to mobile robot to learn the best decision. On the …