Results 71 to 80 of about 309,134 (265)
MultiBUGS: A Parallel Implementation of the BUGS Modeling Framework for Faster Bayesian Inference
Journal of Statistical Software, 2020 MultiBUGS is a new version of the general-purpose Bayesian modeling software BUGS that implements a generic algorithm for parallelizing Markov chain Monte Carlo (MCMC) algorithms to speed up posterior inference of Bayesian models.
Robert J. B. Goudie +3 more
doaj +1 more source
Arthritis Care &Research, EarlyView.Objective Youth who experience a sport‐related knee injury have elevated odds of becoming overweight or developing obesity in 3 to 10 years, compounding their risk for posttraumatic osteoarthritis (PTOA). To inform prevention strategies, this study compared patterns of adiposity change between youth with a sport‐related knee injury and uninjured youth ...
Justin M. Losciale +6 more
wiley +1 more source
Evaluating goodness-of-fit indicators for the construct validity and reliability of the scale of the "Dragons of Inaction" Psychological Barriers to climate change mitigation and adaptation: Studying differences using Bayesian probability [PDF]
مجلة جامعة الأنبار للعلوم الإنسانيةThis study aimed to culturally adapt the "Dragons of Inaction Psychological Barriers" scale developed by Lacroix and her colleagues (Lacroix et al., 2019) in the Canadian context, and measure the construct validity good-fit-indexes of the standard model ...
Boshra Arnout
doaj +1 more source
A new indicator of leaf stomatal conductance based on thermal imaging for field grown cowpea
Plant Production Science, 2020 Compared with a porometer, a thermal camera can be easily applied to large plant populations comprising a set of varieties, treatments, and replications, whereby, leaf temperature-based indicators are widely used to estimate stomatal conductance (gs ...
Kohtaro Iseki, Olajumoke Olaleye
doaj +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +2 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Global HeartObjective: Despite significant advancements in understanding risk factors and treatment strategies, ischemic heart disease (IHD) remains the leading cause of mortality worldwide, particularly within specific regions in Brazil, where the disease is a ...
Amanda de Carvalho Dutra +12 more
doaj +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
Advanced Engineering Materials, EarlyView.This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source