Results 101 to 110 of about 1,488,586 (258)
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
Learner preferences prediction with mixture embedding of knowledge and behavior graph
To solve the problems of inaccurate prediction of learner preference and insufficient utilization of structural information in the knowledge recommendation model, for the knowledge structure and learner behavior structure in the learner’s preference ...
Xiaoguang LI +4 more
doaj
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
Open-World Knowledge Graph Completion
Knowledge Graphs (KGs) have been applied to many tasks including Web search, link prediction, recommendation, natural language processing, and entity linking. However, most KGs are far from complete and are growing at a rapid pace.
Shi, Baoxu, Weninger, Tim
core +1 more source
Carbon nanomaterial‐reinforced epoxy composites exhibit pronounced piezoresistive behavior, enabling intrinsic damage sensing under cyclic and fatigue loading. This review critically compares carbon nanotube and graphene systems, correlating filler content, percolation threshold, and gauge factor with sensing stability and damage evolution.
J. M. Parente +3 more
wiley +1 more source
Knowledge Graph Essentials and Key Technologies
In recent decades, the amount of information that humankind has accumulated has increased tremendously. People cannot analyze it effectively using simple algorithms, and data structures due to these approaches do not understand the se¬mantics of the data.
Vladislav Gurin +5 more
doaj +1 more source
Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks
We propose a distance supervised relation extraction approach for long-tailed, imbalanced data which is prevalent in real-world settings. Here, the challenge is to learn accurate "few-shot" models for classes existing at the tail of the class ...
Chen, Huajun +6 more
core
Fungal mycelia grown into biodegradable scaffolds and infused with titania nanoparticles show enhanced ultraviolet shielding, thermal protection, and surface nonwettability. Properties were tuned by drying methods, revealing structure–function relationships.
Juwon S. Afolayan +2 more
wiley +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
Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana +2 more
wiley +1 more source

