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Abstract Detecting epileptic seizures from electroencephalogram (EEG) signals presents a significant challenge due to the nonlinear and non-stationary nature of brain activity. In this study, we propose a hybrid classifi...

Electroencephalography (EEG) is a crucial technique for interpreting neurocognitive functions and the underlying neural information. Despite its advantages, such as high portability, cost-effectiveness and exceptional te...

Abstract Accurate classification of phonocardiogram (PCG) signals is vital for the early detection of cardiovascular diseases (CVDs), a leading cause of global mortality. However, conventional machine learning and deep l...

Abstract Contrast enhancement technique is a prevalent problem in aiding interpretation of Magnetic Resonance Imaging (MRI) images. A low contrast MRI image may prove to be problematic in identifying medical problems suc...

The Internet of Things (IoT) has emerged as a large-scale ecosystem that integrates sensing, communication, and computation across diverse application domains. Its deployment spans smart homes, wearable devices, industri...

Free-space optical (FSO) communication using dual-polarization self-coherent (DP-SC) transceivers is a promising solution for achieving high data rates and enhanced spectral efficiency in the next optical wireless system...

Abstract In the present study, we examine how optical solitons behave in a synthetic nonlocal nonlinear medium. An analytical investigation is conducted into the nonlinear dynamical model that represents the propagation ...

Abstract Medical images are inherently high-resolution and contain locally varying structures that are crucial for diagnosis. Efficient compression of such data must therefore preserve diagnostic fidelity while minimizin...

Abstract Emotion recognition is fundamental to building socially intelligent robotic systems capable of effective and adaptive Human-Robot Interaction (HRI) and Collaboration (HRC). This literature review synthesizes rec...

Abstract This manuscript presents the feasibility of designing a digital Lock-In Amplifier (LIA) for measuring experimental sys-tems through optical measurement techniques, from 32-bit micro-controller platforms, derived...