Sensitivity analysis helps predict outcomes by varying key variables in financial models. It simplifies complex models, aids in understanding variable effects, and reduces uncertainty. This analysis ...

We investigate glucose-insulin regulation through a delay differential equation model formulated in Sobolev spaces. A physiologically motivated time delay is incorporated into an advanced modeling ...

ABSTRACT: The research examines how different key parameters affect the SEIRD epidemic model through MATLAB Simulink simulations. The simulation model includes three scenarios which consist of a ...

Light sensitivity in one eye could occur for many reasons, ranging from minor injuries, dry eye, and migraine to more serious conditions, such as multiple sclerosis. Light sensitivity, or photophobia, ...

High-sensitivity climate models should not be excluded when predicting future regional climate impacts because the level of warming measured globally is not always the only good indicator of regional ...

Abstract: Graph Neural Networks (GNNs), particularly Graph Convolutional Neural Networks (GCNNs), have emerged as pivotal instruments in machine learning and signal processing for processing ...

Department of Chemical Engineering, University of Louisiana, Lafayette, Louisiana 70504, United States Energy Institute of Louisiana, University of Louisiana, Lafayette, Louisiana 70504, United States ...

The National Center for Education Statistics recently reported that of the 49.6 million students enrolled in public schools across America, approximately 55% identified as members of ethnic or racial ...

The majority of research predicted heating demand using linear regression models, but they did not give current building features enough context. Model problems such as Multicollinearity need to be ...

The paper explores the nexus between the financial and business cycles in a semi-structural New Keynesian model with a financial accelerator, an active banking sector, and an endogenous ...