Electroencephalogram (EEG) signals play a critical role in advancing brain-computer interface (BCI) systems, particularly for detecting motor imagery (MI) movements. However, analysing large volume of EEG datasets faces some challenges due to redunda...
This study presents a comprehensive analysis of soft finger actuators using finite element modeling to assess their performance in various structural configurations. By conducting detailed numerical simulations, we explore how variations in structura...
To enhance crop yield, detecting leaf diseases has become a crucial research focus. Deep learning and computer vision excel in digital image processing. Various techniques grounded in deep learning have been utilized for detecting plant leaf diseases...
In recent years, there has been a significant increase in research activity on electroencephalography (EEG)-based motor imagery brain-computer interfaces (MI-BCI) in the field of deep learning. However, despite achieving high accuracy, the size of mo...
Gas-insulated switchgear (GIS) systems extensively employ sulfur hexafluoride (SF) as an insulating medium and are widely deployed in modern power systems. Under partial discharge (PD) conditions, SF decomposes to generate hazardous byproducts such a...
Integrating machine learning (ML) into nanotechnology represents a promising strategy for rational design and accelerated development of drug delivery systems. However, studies in this field are scarce and face methodological and interpretative probl...
The rapid development of deep learning has promoted its application in disease diagnosis, treatment, and prognosis prediction. Medical imaging plays a crucial role in the management of rifampicin-resistant tuberculosis/multidrug-resistant tuberculosi...
The growing interest in using peptide molecules as therapeutic agents, driven by their high selectivity and efficacy, has become a significant trend in the pharmaceutical industry. However, their oral administration remains challenging due to their l...
The deployment of advanced reinforcement learning algorithms in edge computing environments presents significant challenges for real-time aquaculture management, particularly in resource-constrained recirculating aquaculture systems (RAS). Building u...
This study addresses persistent challenges in traditional talent cultivation models, including misalignment with industry demands, outdated instructional content, and limited depth in school-enterprise collaboration. To overcome these issues, the stu...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.