Results 51 to 60 of about 123,539 (262)

Innovating Aircraft Repair Processes: The Role of Digitalization in Sustainability

Advanced Engineering Materials, EarlyView.
This research explores how digitalization—by storing detailed non‐destructive testing data in structured DICONDE databases and creating a standard data model of the component—innovates aviation maintenance and repair processes. Coupled with a developed state‐based simulation model, it enables data‐driven, sustainable repair strategies that reduce waste,
Johanna Aigner, Geo Jacob, Florian Raddatz, Gerko Wende   +3 more
wiley   +1 more source

Incorporating Domain Knowledge Into Language Models by Using Graph Convolutional Networks for Assessing Semantic Textual Similarity: Model Development and Performance Comparison

JMIR Medical Informatics, 2021
BackgroundAlthough electronic health record systems have facilitated clinical documentation in health care, they have also introduced new challenges, such as the proliferation of redundant information through the use of copy and ...
David Chang, Eric Lin, Cynthia Brandt, Richard Andrew Taylor   +3 more
doaj   +1 more source

On finding augmenting graphs

Discrete Applied Mathematics, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lozin, Vadim V., Milanič, Martin
openaire   +1 more source

Approximating k-Forest with Resource Augmentation: A Primal-Dual Approach

, 2016
In this paper, we study the $k$-forest problem in the model of resource augmentation. In the $k$-forest problem, given an edge-weighted graph $G(V,E)$, a parameter $k$, and a set of $m$ demand pairs $\subseteq V \times V$, the objective is to construct a
A Blum, A Blum, A Borodin, A Gupta, A Srivastav, A Wigderson, B Birnbaum, B Kalyanasundaram, B Kalyanasundaram, C Chung, C Lund, CA Phillips, D Segev, DP Williamson, DS Johnson, E Koutsoupias, J Könemann, K Jain, K Jain, M Haimovich, MX Goemans, NE Young, O Ohrimenko, PN Klein, S Khot, U Feige, U Feige, VV Vazirani, Y Asahiro   +28 more
core   +2 more sources

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
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, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Contrastive learning for traffic flow forecasting based on multi graph convolution network

IET Intelligent Transport Systems
Contrastive learning is an increasingly important research direction and has attracted considerable attention in the field of computer vision. It can greatly improve the representativeness of image features through data augmentation, unsupervised ...
Kan Guo, Daxin Tian, Yongli Hu, Yanfeng Sun, Zhen (Sean) Qian, Jianshan Zhou, Junbin Gao, Baocai Yin   +7 more
doaj   +1 more source

Denoising Long-Tail Augmented Contrastive Network for Multi-Behavior Recommendation

IEEE Access
Recommendation systems in multi-behavior recommendation systems integrate various user behavior data (e.g., favorites, cart) for representation learning, often alleviating the problem of data sparsity and enabling a more comprehensive user profile ...
Jinle He, Chengyong Yang, Jiayi Liu, Jianlin Cheng   +3 more
doaj   +1 more source

Graph-Augmentation-Free Self-Supervised Learning for Social Recommendation

Applied Sciences, 2023
Social recommendation systems can improve recommendation quality in cases of sparse user–item interaction data, which has attracted the industry’s attention. In reality, social recommendation systems mostly mine real user preferences from social networks.
Nan Xiang, Xiaoxia Ma, Huiling Liu, Xiao Tang, Lu Wang   +4 more
doaj   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

A data augmentation model integrating supervised and unsupervised learning for recommendation

Scientific Reports
Recommendation models based on Graph Neural Networks (GNNs) are typically employed within a supervised learning paradigm. However, the label data is extremely sparse across the entire interaction space, hindering the model’s ability to learn high-quality
Jiaying Chen, Zhongrui Zhu, Haoyang Li, Wanlong Jiang, Gwanggil Jeon, Yurong Qian   +5 more
doaj   +1 more source