Results 101 to 110 of about 391,798 (266)
A CS Recovery Algorithm for Model and Time Delay Identification of MISO-FIR Systems
This paper considers identifying the multiple input single output finite impulse response (MISO-FIR) systems with unknown time delays and orders. Generally, parameters, orders and time delays of an MISO system are separately identified from different ...
Yanjun Liu, Taiyang Tao
doaj +1 more source
A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
SAR 3D Reconstruction Based on Multi-Prior Collaboration
Array synthetic aperture radar (SAR) three-dimensional (3D) image reconstruction enables the extraction of target distribution information in 3D space, supporting scattering characteristic analysis and structural interpretation.
Yangyang Wang +8 more
doaj +1 more source
The temperature dependence of fatigue behavior in nickel‐based superalloys is investigated through high‐resolution measurements of plastic localization. While increasing temperature reduces localization and enhances fatigue performance in René 88DT, Inconel 718 exhibits a sharp degradation at intermediate temperature due to intensified slip ...
M. Calvat +5 more
wiley +1 more source
Dynamic Sparse Training of Diagonally Sparse Networks
Recent advances in Dynamic Sparse Training (DST) have pushed the frontier of sparse neural network training in structured and unstructured contexts, matching dense-model performance while drastically reducing parameter counts to facilitate model scaling. However, unstructured sparsity often fails to translate into practical speedups on modern hardware.
Abhishek Tyagi +4 more
openaire +3 more sources
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
Sparse-ProxSkip: Accelerated Sparse-to-Sparse Training in Federated Learning
In Federated Learning (FL), both client resource constraints and communication costs pose major problems for training large models. In the centralized setting, sparse training addresses resource constraints, while in the distributed setting, local training addresses communication costs.
Meinhardt, Georg +3 more
openaire +2 more sources
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran +6 more
wiley +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

