Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Abstract: Calibration of the composite load model with distributed generation (CMPLDWG) can be challenging due to its nonlinear and high-dimensional characteristics. To address this issue, this paper ...

1 Department of Biochemistry, Brandeis University, Waltham, MA, United States 2 Department of Biology, Brandeis University, Waltham, MA, United States This study explores the efficacy of Bayesian ...

Based on the compounding mechanism, a unique discrete probability distribution is investigated in this paper. The Poisson distribution is mixed with a lifetime model called as the Fav-Jerry model. The ...

Abstract: This work studies the problem of jointly estimating unknown parameters from Kronecker-structured multidimensional signals, which arises in applications like intelligent reflecting surface ...

Regression models with intractable normalizing constants are valuable tools for analyzing complex data structures, yet parameter inference for such models remains highly challenging—particularly when ...

The mathematics that enable sensor fusion include probabilistic modeling and statistical estimation using Bayesian inference and techniques like particle filters, Kalman filters, and α-β-γ filters, ...

ABSTRACT: Vehicle tracking plays a crucial role in intelligent transportation, autonomous driving, and video surveillance. However, challenges such as occlusion, multi-target interference, and ...

I'm working on the length-weight relationships provided in the estimate.csv and trying to find more explanations about the parameters . I wonder where I could find more specific reference about the ...