Results 41 to 50 of about 9,156,471 (236)

Geometry Interaction Embeddings for Interpolation Temporal Knowledge Graph Completion

Mathematics
Knowledge graphs (KGs) have become a cornerstone for structuring vast amounts of information, enabling sophisticated AI applications across domains. The progression to temporal knowledge graphs (TKGs) introduces time as an essential dimension, allowing ...
Xuechen Zhao, Jinfeng Miao, Fuqiang Yang, Shengnan Pang   +3 more
doaj   +1 more source

Semantic Modeling in Materials Science and Engineering With Platform MaterialDigital Core Ontology 3.0

Advanced Engineering Materials, EarlyView.
The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling, Philipp von Hartrott, Jörg Waitelonis, Thomas Hanke, Henk Birkholz, Hossein Beygi Nasrabadi, Khashayar Razghandi, Kamilla Zaripova, Felix Thonagel, Fabian Neuhaus, Martin Glauer, Lars Vogt, Harald Sack, Lutz Mädler, Bernd Bayerlein, Chris Eberl   +15 more
wiley   +1 more source

RPHF-GNN: Recurrent Perception of History-Future Graph Neural Networks for Temporal Knowledge Graph Reasoning

IEEE Access
TKG (Temporal Knowledge Graph) reasoning has become a hot research topic in recent years. its purpose is to predict the future by modeling historical information. However, existing research has primarily focused on comprehending the patterns and rules of
Siling Feng, Zimin Ye, Qian Liu, Mengxing Huang   +3 more
doaj   +1 more source

When Poor Exciton Dissociation Limits Photocurrents in Organic Solar Cells: Why Low Offset Non‐Fullerene Acceptor Blends Can't Be Efficient

Advanced Materials, EarlyView.
The energetic offset between the donor and the acceptor components in organic photoactive layers is central to the tradeoff between photovoltage and photocurrent losses. This Perspective covers the most important issues surrounding this topic in non‐fullerene acceptor blends, from the difficulty of accurately determining state energies and driving ...
Dieter Neher, Manasi Pranav
wiley   +1 more source

Commonsense knowledge representation and reasoning with fuzzy neural networks [PDF]

, 1996
This paper highlights the theory of common-sense knowledge in terms of representation and reasoning. A connectionist model is proposed for common-sense knowledge representation and reasoning.
Kouzani, Abbas, Sammut, Karl, He, Fangpo
core  

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

Temporal knowledge graph reasoning using global and recent history information

Scientific Reports
Since the static Knowledge Graph cannot meet the dynamics of knowledge in the real world, Temporal Knowledge Graph has become a potential method for processing temporal knowledge.
Changlong Wang, Jianlong Cao, Wenzheng Guo, Jie Hu, Yaoyao Hu, Yi Liu, Yawei Li, Huimei Tian, Pengjuan Lu, Wenhao Zhao, Zhixiong Yin   +10 more
doaj   +1 more source

Construction and application of integrated knowledge graph for mine disasters

Meikuang Anquan
In order to achieve a novel disaster early warning mode of “autonomous modeling + integrated early warning + root cause tracing”, and improve the knowledge engineering infrastructure for integrated intelligent disaster warning, this study developed an ...
Yabo HE
doaj   +1 more source

Disaster Prediction Knowledge Graph Based on Multi-Source Spatio-Temporal Information

, 2022
Natural disasters have frequently occurred and caused great harm. Although the remote sensing technology can effectively provide disaster data, it still needs to consider the relevant information from multiple aspects for disaster analysis. It is hard to
Chen, Jiahui, Li, Weichao, Zhang, Wenyue, Ge, Xingtong, Peng, Ling, Wenyue Zhang, Huang, Zhisheng, Weichao Li, Yi Yang, Zhisheng Huang, Xingtong Ge, Jiahui Chen, Ling Peng, Yang, Yi   +13 more
core   +1 more source

Jumping Knowledge Based Spatial-Temporal Graph Convolutional Networks for Automatic Sleep Stage Classification [PDF]

, 2022
A novel jumping knowledge spatial-temporal graph convolutional network (JK-STGCN) is proposed in this paper to classify sleep stages. Based on this method, different types of multi-channel bio-signals, including electroencephalography (EEG ...
Ji, Xiaopeng, Wen, Peng, Li, Yan
core   +1 more source