Results 141 to 150 of about 25,561,218 (304)
bizicount: Bivariate Zero-Inflated Count Copula Regression Using R
Two common issues arise in regression modelling of bivariate count data: (i) dependence across outcomes, and (ii) excess zero counts (i.e., zero inflation).
John M. Niehaus +3 more
doaj +1 more source
An origami worm‐inspired robot achieves multimodal locomotion in confined pipelines through mechatronic integration that embeds actuation, control, and communication within each origami module. Large, reversible configuration and dimensional changes enable 25 gaits synthesized by a unified framework across peristaltic, inchworm, and wheel‐rolling modes
Qiwei Zhang +6 more
wiley +1 more source
Communication-efficient distributed statistical inference on zero-inflated Poisson models
Zero-inflated count outcomes are common in many studies, such as counting claim frequency in the insurance industry in which identifying and understanding excessive zeros are of interest.
Ran Wan, Yang Bai
doaj +1 more source
Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram +4 more
wiley +1 more source
Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami
This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning +3 more
wiley +1 more source
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
Modeling Zero-Inflated Continuous Data with Varying Dispersion
Zero-inflated data are often observed in empirical studies of different scientific fields. Data are considered as zero-inflated if the observed values of a random vector contain significantly more zeros than expected.
Li, WK, Wu, KYK
core
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi +7 more
wiley +1 more source
Geometric constraint reconfiguration enables a rigid–foldable kirigami‐inspired mechanism to switch between twisting, directional translation, and self‐locking states. By encoding multifunctionality directly into its architecture, the mechanism achieves multimodal motion and passive locking without reassembly, providing a compact platform for adaptive ...
Jianlin Wang, Zhongmin Song, Ketao Zhang
wiley +1 more source
Modeling count data with marginalized zero-inflated distributions [PDF]
In this article, we present new commands for modeling count data using marginalized zero-inflated distributions. While we mainly focus on presenting new commands for estimating count data, we also present examples that illustrate some of these new ...
Hardin, James W., Cummings, Tammy H.
core +1 more source

