This is a valuable study on how past sensory experiences shape perception across multiple time scales. Using a behavioural task and reanalysed EEG data, the authors identify two unifying mechanisms ...

As countries begin to establish AI regulations, engineers designing AI-enabled systems must meet newly introduced ...

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

The triggering receptor expressed on myeloid cells 2 (TREM2) plays a pivotal role in the activation of myeloid cells and is ...

Network intrusion detection and pattern matching techniques form a critical pillar in contemporary cybersecurity. These methods enable the identification of malicious activities by scrutinising ...

Autonomous driving systems mainly rely on accurate detection of lane markings for navigation and safety. This paper explores an enhanced lane detection methodology employing deformable linear ...

Anomaly detection in multivariate time series (MTS) is crucial in domains such as industrial monitoring, cybersecurity, healthcare, and autonomous driving. Deep learning approaches have improved ...

An ANN model using feedforward backpropagation was developed in MATLAB ® and its Neural Network Pattern Recognition tool. Through an iterative and systematic experimental process, 339 training ...

Decision Tree and Linear Discriminant Analysis-Assisted Design of Polydopamine Nanoparticle-Based Colorimetric Array Sensor Modulated by Metal Ions for High-Efficiency Detection of Physiological ...