Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

piecewise-regression (aka segmented regression) in python. For fitting straight line models to data with one or more breakpoints where the gradient changes. APLR builds predictive, interpretable ...

This work integrates microfluidic technology to demonstrate a one-step fabrication of aptamer-conjugated emodin liposomes via a novel micromixer, achieving efficient production and effective therapy ...

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

Abstract: Due to its heavy-tailed and fully parametric form, the multivariate generalized Gaussian distribution (MGGD) has been receiving much attention in signal and image processing applications.

Please note that sometimes github doesn't load the .ipynb file or use a incorrect diagram for a matrix, feel free to download it and use in your own reader The aim of ...

Abstract: In this paper, a multi-dimensional holomorphic embedding method (MDHEM) is developed to solve three-phase unbalanced power flow in AC-DC hybrid distribution systems (DSs). According to the $ ...

This work is divided to two parts; the first part analyzes the features of Hénon–Heiles’s potential and finding the energy levels for bounded and unbounded motions. The critical points are explored in ...