28 citations · 45 across the 7 of their papers we have counts for
7 papers
Integrating Robotic Navigation with Blockchain: A Novel PoS-Based Approach for Heterogeneous Robotic Teams
Nasim Paykari, Ali Alfatemi, Damian M. Lyons +1
This work explores a novel integration of blockchain methodologies with Wide Area Visual Navigation (WAVN) to address challenges in visual navigation for a heterogeneous team of mo…
Towards Equitable ASD Diagnostics: A Comparative Study of Machine and Deep Learning Models Using Behavioral and Facial Data
Mohammed Aledhari, Mohamed Rahouti, Ali Alfatemi
Autism Spectrum Disorder (ASD) is often underdiagnosed in females due to gender-specific symptom differences overlooked by conventional diagnostics. This study evaluates machine le…
Optimizing Control Strategies for Wheeled Mobile Robots Using Fuzzy Type I and II Controllers and Parallel Distributed Compensation
Nasim Paykari, Razieh Jokar, Ali Alfatemi +2
Adjusting the control actions of a wheeled robot to eliminate oscillations and ensure smoother motion is critical in applications requiring accurate and soft movements. Fuzzy contr…
Enabling Trustworthy Federated Learning in Industrial IoT: Bridging the Gap Between Interpretability and Robustness
Senthil Kumar Jagatheesaperumal, Mohamed Rahouti, Ali Alfatemi +3
Federated Learning (FL) represents a paradigm shift in machine learning, allowing collaborative model training while keeping data localized. This approach is particularly pertinent…
Cryptocurrency Price Forecasting Using XGBoost Regressor and Technical Indicators
Abdelatif Hafid, Maad Ebrahim, Ali Alfatemi +2
The rapid growth of the stock market has attracted many investors due to its potential for significant profits. However, predicting stock prices accurately is difficult because fin…
Redefining DDoS Attack Detection Using A Dual-Space Prototypical Network-Based Approach
Fernando Martinez, Mariyam Mapkar, Ali Alfatemi +4
Distributed Denial of Service (DDoS) attacks pose an increasingly substantial cybersecurity threat to organizations across the globe. In this paper, we introduce a new deep learnin…
Advancing DDoS Attack Detection: A Synergistic Approach Using Deep Residual Neural Networks and Synthetic Oversampling
Ali Alfatemi, Mohamed Rahouti, Ruhul Amin +3
Distributed Denial of Service (DDoS) attacks pose a significant threat to the stability and reliability of online systems. Effective and early detection of such attacks is pivotal…