Training a Convolutional Neural Network (CNN) from scratch is time-consuming and expensive. In this study, we propose implementing the DenseNet architecture for classification of AD in three classes. Our approach leverages transfer learning architectures as the base model and showcases superior...

Identifying models with Infinite Impulse Response (IIR) is crucial in signal processing and system identification. This paper addresses the challenges of IIR model identification by proposing an improved version of the Artificial Rabbits Optimization (ARO) algorithm called improved ARO (IARO)....

Malaria represents a potentially fatal communicable illness triggered by the Plasmodium parasite. This disease is transmitted to humans through the bites of Anopheles mosquitoes that carry the infection. This disease has significant and devastating consequences on the health systems of fragile...

Cities evolve rapidly while providing both opportunities and posing challenges. To cope with the emerging behaviours of cities, contextual innovations and development are essential. Driving innovations through the learning of contextual knowledge in cities is crucial. In this study, we explore...

In today's ever-changing world, research and innovation (R&I) foresight is more relevant than ever. It helps policymakers make better decisions by thinking towards the future. The interest in R&I foresight has grown at both national and European levels as a response to the challenges we face as...

In this paper, we extend the individual evolutionary learning model by incorporating other-regarding considerations and apply the model to some Cournot games. Using the model fitted to the experimental data of a repeated 3-player Cournot game (with nonlinear cost and demand functions), we...