Results 81 to 90 of about 6,811,694 (242)
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
Automatic question-answering modeling in English by integrating TF-IDF and segmentation algorithms
Online network education offers convenience, however, the inefficiency and time-consuming nature of question-answering models negatively impact the demand for online learning.
Hainan Wang
doaj +1 more source
MultiCGCN: Multi-Label Text Classification using GCNs and Heterogeneous Graphs [PDF]
Multi-label text classification is a critical challenge in natural language processing, where the goal is to assign multiple labels to a given document.
Milad Allahgholi +3 more
doaj +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
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
Effect of losses in an active device and harmonic network on the efficiency of Class F and inverse Class F power amplifiers [PDF]
High frequency class F and inverse class F power amplifiers obtain high efficiency of dc to ac power conversion, by reducing the overlap of voltage and current waveforms at the output of the active device, to ensure that the power dissipated in the ...
Ghassemlooy, Zabih +5 more
core
New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare +5 more
wiley +1 more source
Analyzing Documents with TF-IDF
This lesson focuses on a foundational natural language processing and information retrieval method called Term Frequency - Inverse Document Frequency (tf-idf).
Matthew J. Lavin
doaj
The OntOMat ontology establishes a structured framework for polymer matrix fiber reinforced composite materials, integrating manufacturing processes, characterization methods, and multiscale design through the VDI/VDE 3682 formalized process description standard.
Nicolas Christ +19 more
wiley +1 more source
A Note on Inverse Document Frequency Weighting Scheme
Based on the Shannon information theory, a measure for term value is introduced. This study is an attempt to provide a theoretical justification for the inverse document frequency (IDF) weighting scheme.
Yao, Y. Y., Wong, S. K. M.
core +5 more sources

