The next wave of wireless technologies is proliferating in connecting things among
themselves as well as to humans. In the era of the Internet of Things (IoT), billions of …

Recent years have seen an increasing interest in Demand Response (DR) as a means to
provide flexibility, and hence improve the reliability of energy systems in a cost-effective way …

6G and beyond will fulfill the requirements of a fully connected world and provide ubiquitous
wireless connectivity for all. Transformative solutions are expected to drive the surge for …

The widespread deployment of machine learning applications in ubiquitous environments
has sparked interests in exploiting the vast amount of data stored on mobile devices. To …

Priority dispatching rule (PDR) is widely used for solving real-world Job-shop scheduling
problem (JSSP). However, the design of effective PDRs is a tedious task, requiring a myriad …

For a machine learning model to generalize well, one needs to ensure that its decisions are
supported by meaningful patterns in the input data. A prerequisite is however for the model …

A large set of the explainable Artificial Intelligence (XAI) literature is emerging on feature
relevance techniques to explain a deep neural network (DNN) output or explaining models …

This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …

The incumbent Internet of Things suffers from poor scalability and elasticity exhibiting in
communication, computing, caching and control (4Cs) problems. The recent advances in …

Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …