Outputs (463)

ARUC-GAN: A CycleGAN-based attention residual U-Net for low-dose CT denoising in smart healthcare (2025)
Journal Article

Low-dose computed tomography (LDCT) is increasingly adopted in medical imaging to minimize radiation exposure. However, the diagnostic accuracy is primarily affected by different noise sources, e.g., quantum, electronic, and reconstruction. Moreover,... Read More about ARUC-GAN: A CycleGAN-based attention residual U-Net for low-dose CT denoising in smart healthcare.

Leveraging activation and optimisation layers as dynamic strategies in the multi-task fuzzing scheme (2025)
Journal Article

Fuzzing is a common technique for identifying vulnerabilities in software. Recent approaches, like She et al.’s Multi-Task Fuzzing (MTFuzz), use neural networks to improve fuzzing efficiency. However, key elements like network architecture and hyperp... Read More about Leveraging activation and optimisation layers as dynamic strategies in the multi-task fuzzing scheme.

Thermal colloid programming (2025)
Journal Article

This paper investigates the computational capabilities of colloidal systems, focusing on the integration of Boolean logic operations within gold nanoparticle suspensions under varying temperature conditions. As climate change, artificial intelligence... Read More about Thermal colloid programming.

An explainable ensemble-based intrusion detection system for software-defined vehicle ad-hoc networks (2025)
Journal Article

Intrusion Detection Systems (IDS) are widely employed to detect and mitigate external network security events. Vehicle ad-hoc Networks (VANETs) continue to evolve, especially with developments related to Connected Autonomous Vehicles (CAVs). In this... Read More about An explainable ensemble-based intrusion detection system for software-defined vehicle ad-hoc networks.

Liquid ferrofluid synapses for spike-based neuromorphic learning (2025)
Journal Article

Solid-state memory devices have emerged as promising synapses for neuromorphic engineering and computing. However, features such as limited endurance, static sensitivity, and lower ON/OFF ratios, as well as the need for peculiar conditions including... Read More about Liquid ferrofluid synapses for spike-based neuromorphic learning.

Federated learning in IoT environments: Examining the three-way see-saw for privacy, model-performance, and network-efficiency (2025)
Journal Article

This survey paper provides an in-depth exploration of Federated Learning (FL) in Internet of Things (IoT) environments , focusing on privacy-preserving techniques and their influence on model performance and network efficiency. It highlights key chal... Read More about Federated learning in IoT environments: Examining the three-way see-saw for privacy, model-performance, and network-efficiency.

An integrated approach to mitigate poisoning attacks in federated learning frameworks (2025)
Presentation / Conference Contribution

While Federated learning (FL) is considered privacy-preserving by nature, it remains vulnerable to many attacks, such as data and model poisoning, that compromise data integrity and model accuracy. Conventional privacy-preserving federated learning (... Read More about An integrated approach to mitigate poisoning attacks in federated learning frameworks.

Enhancing public participation in urban planning: The role of VR, HBIM, and gamification (2025)
Presentation / Conference Contribution

The study demonstrates a novel method of urban planning through a col-laborative digital platform that promotes engagement and interaction among people, technicians, and administrators. Utilizing the suggested digital plat-form, the citizen acts as a... Read More about Enhancing public participation in urban planning: The role of VR, HBIM, and gamification.

The evolution of phishing and future directions: A review (2025)
Presentation / Conference Contribution

Phishing has emerged as one of the most persistent and evolving threats in cybersecurity. Its development from simple email scams to highly sophisticated and targeted attacks has been driven by technological advancements, the rise of social media, an... Read More about The evolution of phishing and future directions: A review.

A machine learning-based intrusion detection algorithm for securing bioinformatics pipelines (2025)
Presentation / Conference Contribution

Bioinformatics pipelines, which process vast amounts of sensitive biological data, are increasingly targeted by cyberattacks. Traditional security measures often fail to provide adequate protection due to the unique computational and network characte... Read More about A machine learning-based intrusion detection algorithm for securing bioinformatics pipelines.