Federated learning (FL) allows a set of agents to collaboratively train model without sharing their potentially sensitive data. This makes FL suitable for privacy-preserving applications. At the same time, is susceptible adversarial attacks due decentralized and unvetted One important line against backdoor attacks. In attack, an adversary tries embed functionality during training that can later...

Massive Open Online Courses (MOOCs) have recently received a great deal of attention from the academic communities. However, these courses face low completion rates and there are very limited research pertaining to this problem. Therefore, this study uses Triandis theory to better understand variables that are indicative of MOOC completion. Furthermore, this study scrutinizes the quantitative r...

Adaptive behaviour through machine learning is challenging in many real-world applications such as robotics. This is because learning has to be rapid enough to be performed in real time and to avoid damage to the robot. Models using linear function approximation are interesting in such tasks because they offer rapid learning and have small memory and processing requirements. Adalines are a simp...

background: understanding the learning styles of medical students can drive the institutions to adapt instructional materials to enhance students’ learning of knowledge and skills. this study explored the learning styles of undergraduate medical students, comparing gender variations in terms of their significant preferences. materials and methods: a cross-sectional observational study was perfo...