Results 131 to 140 of about 529,167 (319)
Dynamic Safety Analysis CNG Stations Using Fault Tree Approach and Bayesian Network
Introduction: The safety of CNG stations is important because of their location in urban areas, as well as to prevent accidents and to protect the safety of personnel, property, and environment.
Tahereh Eskandari +2 more
doaj
Multi-Factor superposition influence analysis in engineering projects: a Bayesian network approach
The existing studies rarely examine whether multiple risk factors superimposed on a particular activity result in superposed or non-superposed effects.
Chaoyong Zhang, Keming Hu, Xun Liu
doaj +1 more source
The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry
ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
wiley +1 more source
Food Prices and Inflation Expectations in New Zealand
ABSTRACT Food prices are conspicuous, and spending on food constitutes a considerable share of household expenditure. In this study, we use partially identified Bayesian structural vector autoregression models to analyze the effects of food price shocks on core inflation and 1‐ and 5‐year inflation expectations in New Zealand.
Puneet Vatsa +2 more
wiley +1 more source
Development of dynamic Bayesian network for the analysis of high-dimensional biomedical data [PDF]
Arinze Akutekwe
openalex
AI in chemical engineering: From promise to practice
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
Computational study of permeability in cardboard coating layers
Abstract We develop a virtual material structure model based on a combination of tessellations and Gaussian random fields for a coating layer of paperboard used for packaging and designed to facilitate printing on the surface. To fit the model to tomographic image data acquired using combined focused ion beam and scanning electron microscopy (FIB‐SEM),
Sandra Barman +6 more
wiley +1 more source
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour +5 more
wiley +1 more source
A System Engineering Approach Using FMEA and Bayesian Network for Risk Analysis—A Case Study [PDF]
Sima Rastayesh +5 more
openalex +1 more source
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir +4 more
wiley +1 more source

