Results 81 to 90 of about 118,631 (311)
Data‐Driven Materials Science for Energy‐Sustainable Applications
Advanced Materials, EarlyView.Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
On‐Chip Photonic Neural Network Architectures
Advanced Optical Materials, EarlyView.This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong +7 more
wiley +1 more source
Prediction of concrete fatigue durability using Bayesian neural networks
Computer Assisted Methods in Engineering and Science, 2022 The utility of Bayesian neural networks to predict concrete fatigue durability as a function of concrete mechanical parameters of a specimen and characteristics of the loading cycle is investigated.
Marek Słoński
doaj
3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends
Advanced Robotics Research, EarlyView.Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu +5 more
wiley +1 more source
Frontiers in Computational Neuroscience, 2014 This work presents a spatial-component (SC) based approach to aid the diagnosis of Alzheimer's disease (AD) using magnetic resonance images. In this approach, the whole brain image is subdivided in regions or spatial components, and a Bayesian network is
Ignacio eA. Illán +3 more
doaj +1 more source
Frontiers in Water, 2020 The rivers of KwaZulu-Natal, South Africa, are being impacted by various anthropogenic activities that threaten their sustainability. Our study demonstrated how Bayesian networks could be used to conduct an environmental risk assessment of ...
Olalekan A. Agboola +3 more
doaj +1 more source
Advanced Robotics Research, EarlyView.Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek +3 more
wiley +1 more source
Rock typing and causality analysis in unconventional formation using Bayes nets
Petroleum ResearchUnconventional formations are characterized by high heterogeneity and anisotropy, making it difficult to interpret logging data, perform core analysis, and create accurate petrophysical models.
Evgeny Chekhonin +5 more
doaj +1 more source
Journal of the Brazilian Computer Society, 1997 Bayesian techniques have been developed over many years in a range of different fields, but have only recently been applied to the problem of learning in neural networks. As well as providing a consistent framework for statistical pattern recognition, the Bayesian approach offers a number of practical advantages including a solution to the problem of ...
openaire +3 more sources