In the rapidly evolving sector of financial analytics, predicting a firm’s going concern status accurately is vital for informed user decisions.This study introduces a novel method that synergizes Anchor Explainable Artificial Intelligence (XAI) with an Attention-Weighted Extreme Gradient Boosting (XGBoost) model, significantly improving the
Abstract Intramedullary astrocytomas (IMAs) are rare tumors, and few studies specific to the molecular alterations of IMAs have been performed.Recently, KIAA1549-BRAF fusions and the H3F3A p.K27M mutation have been described in low-grade (LG) and high-grade (HG) IMAs, respectively.In the present study, we collected clinico-radiological data and per
Spiking neural networks (SNNs) have emerged as a hardware efficient architecture for classification tasks.The challenge of spike-based encoding has been the lack of a universal training mechanism performed entirely using spikes.There have been several attempts to adopt the powerful backpropagation (BP) technique used in non-spiking artificial neura
Understanding the transmission dynamics of COVID-19 is crucial for evaluating its spread pattern, especially in metropolitan areas of China, as its spread could lead to secondary outbreaks.In addition, the experiences gained and lessons learned from China have the potential to provide evidence to support other metropolitan areas and large cities ou
Intraplate faulting and the resultant earthquakes are not well understood because of their complex distribution, long period of seismic network recurrence, and poor exposure of surface rupture.Pre-existing weaknesses should be studied to understand intraplate faulting and earthquakes.We are developing a long-term project to understand Korean-type i