Machine learning helps intrusion detection systems learn new assaults quickly. These systems train on a dataset with several threats and may identify odd behavior. This research detects intrusion using Random Forest, KNN, and Gaussian Naive Bayes. We run the model on a comprehens…
Despite the general improvement of living conditions and the ways of building buildings, the sense of security in or around them is often not satisfactory for their users, resulting in the search and implementation of increasingly effective protection measures. The insecurity tha…
This study investigates the optimization of traffic scheduling in autonomous vehicle networks using time-sensitive networking (TSN), a type of deterministic Ethernet. Ethernet has high bandwidth and compatibility to support various protocols, and its application range is expandin…
Recent advances in the field of artificial intelligence (AI) have been pivotal in enhancing the effectiveness and efficiency of many systems and in all fields of knowledge, including medical diagnosis [...]
This paper introduces a study on stress recognition utilizing mobile EEG and GSR sensors. The research involved collecting samples from a group of 55 refugees who participated in Virtual Reality stress-reduction sessions. The timing of the study coincided with an influx of refuge…
Advancements in wearable sensors and digital technologies/computational tools (e.g., machine learning (ML), general data analytics, mobile and desktop applications) have been explored in existing studies. However, challenges related to sensor efficacy and the application of digit…