Soft Computing (SC) is an Artificial Intelligence (AI) approach that is more effective at solving real-life problems than traditional computing models. Soft Computing models are tolerant of partial ...

ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...

Decoding emotional states from electroencephalography (EEG) signals is a fundamental goal in affective neuroscience. This endeavor requires accurately modeling the complex spatio-temporal dynamics of ...

Graph Neural Networks (GNNs) are reshaping AI by enhancing data interpretation and improving applications. Learn how GNNs are crucial in advancing machine learning models. Graph Neural Networks (GNNs) ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

Abstract: Auto parts inventory management is an important link of the automobiles multi-value chain, which has a certain impact on the upstream procurement, downstream production and other links.

Abstract: Graph convolutional neural networks have demonstrated promising solutions for processing non-Euclidean data in tasks such as node classification. While existing graph convolution models aim ...

Cues predictive of target locations orient covert attention, improving perceptual performance. Studies have focused on attentional influences on neural activity, but how cues activate attention and ...