Results 101 to 110 of about 2,176,830 (308)
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia +2 more
wiley +1 more source
Image Semantic Relation Generation
Scene graphs provide structured semantic understanding beyond images. For downstream tasks, such as image retrieval, visual question answering, visual relationship detection, and even autonomous vehicle technology, scene graphs can not only distil complex image information but also correct the bias of visual models using semantic-level relations, which
openaire +3 more sources
Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction
Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong +4 more
wiley +1 more source
Wrong or right? Brain potentials reveal hemispheric asymmetries to semantic relations during word-by-word sentence reading as a function of (fictional) knowledge. [PDF]
Troyer M, McRae K, Kutas M.
europepmc +1 more source
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica +38 more
wiley +1 more source
CCSMR: A Combinatorial Category Space-Based Model for Recommendation
Various side information has been exploited in recommender systems to help users finding items they prefer to alleviate data sparsity. Because item category can be used to view the user's preference in a high-level scope and an item can have more than ...
Chunjing Xiao +4 more
doaj +1 more source
Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers
A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley +1 more source
The #LondonIsOpen campaign : desecuritizing Brexit? [PDF]
Faye Donnelly is a Lecturer in the School of International Relations at the University of St Andrews. She is the author of Securitization and the Iraq War: The Rules of Engagement in World Politics (Routledge, 2013). Her most recent article, ‘The Queen’s
Gani, Jasmine Kamrun Nahar +1 more
core +1 more source
L’accentuation des composés : une histoire de relations
This paper looks at compound word stress in pronouncing dictionaries from the 18th century through to the present day (Walker, 1791; Jones, 1963, 2011; Wells, 1991, 2008), as well as the online version of the Oxford English Dictionary.
Susan Moore Mauroux, Nicolas Trapateau
doaj +1 more source
Abstract Families' experience of homelessness is typically examined from the perspective of parents during or shortly after a shelter stay. Parents complain about rules, surveillance, crowding, and challenges to parenting in both homeless shelters and in doubling up with other households (sharing the others' homes), and relief when they attain their ...
Marybeth Shinn +2 more
wiley +1 more source

