Results 51 to 60 of about 1,488,475 (251)
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Partial Discharge Location within a Transformer Winding using Principal Component Analysis
Partial discharge (PD) may occur in a transformer winding due to ageing processes, operational over stressing or defects introduced during manufacture. The presence of PD does not necessarily indicate imminent failure of the transformer but it will lead ...
Abd Rahman, M S, Hao, L, Lewin, P L
core +1 more source
Transformer-based progressive residual network for single image dehazing
IntroductionThe seriously degraded fogging image affects the further visual tasks. How to obtain a fog-free image is not only challenging, but also important in computer vision.
Zhe Yang +4 more
doaj +1 more source
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
wiley +1 more source
The PRIMA Thesaurus for Materials Science and Engineering
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa +8 more
wiley +1 more source
The Swin‐Transformer is a variant of the Vision Transformer, which constructs a hierarchical Transformer that computes representations with shifted windows and window multi‐head self‐attention.
Yixuan Xu +3 more
doaj +1 more source
The remote sensing image (RSI) scene classification is currently a popular research topic among many remote sensing tasks. However, RSI scene classification still faces challenges such as complex multiscale key features concentrated in different local ...
Yi Liu +5 more
doaj +1 more source
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
Towards Robust Vision Transformer
Recent advances on Vision Transformer (ViT) and its improved variants have shown that self-attention-based networks surpass traditional Convolutional Neural Networks (CNNs) in most vision tasks.
Mao, Xiaofeng +7 more
core +1 more source
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source

