Natural disasters (NDs) have always been a major threat to human lives and infrastructure,
causing immense damage and loss. In recent years, the increasing frequency and severity …

In the last decade, there has been a significant surge of interest in machine learning,
primarily driven by advancements in deep learning (DL). DL has emerged as a powerful …

Smart contracts (SCs) are digital agreements that execute themselves and are stored on a
blockchain. Despite the fact that they offer numerous advantages, such as automation and …

With the increasing severity and frequency of cyberattacks, the rapid expansion of smart
objects intensifies cybersecurity threats. The vast communication traffic data between …

Abstract Vehicular Sensor Networks (VSN) introduced a new paradigm for modern
transportation systems by improving traffic management and comfort. However, the …

The field of automated lung cancer diagnosis using Computed Tomography (CT) scans has
been significantly advanced by the precise predictions offered by Convolutional Neural …

Generative Adversarial Networks (GANs) are a type of deep learning techniques that have
shown remarkable success in generating realistic images, videos, and other types of data …

Deep Reinforcement Learning (DRL) is a powerful technique for learning policies for
complex decision-making tasks. In this paper, we provide an overview of DRL, including its …

Underwater acoustic (UWA) communications have been widely used but greatly impaired
due to the complicated nature of the underwater environment. In order to improve UWA …

Abstract Long Short-Term Memory (LSTM) is a popular Recurrent Neural Network (RNN)
algorithm known for its ability to effectively analyze and process sequential data with long …