Results 51 to 60 of about 149,463 (272)

Leak Detection in Water Supply Network Using a Data-Driven Improved Graph Convolutional Network

IEEE Access, 2023
Due to the complex correlation within data collection, it is a challenging task to detect leakage in the water supply network. The Graph Convolutional Network (GCN) has recently gained significant attention in correlation research. However, most existing
Suisheng Chen, Yun Wang, Wei Zhang, Hairong Zhang, Yuchen He   +4 more
doaj   +1 more source

End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

, 2018
Knowledge graph embedding has been an active research topic for knowledge base completion, with progressive improvement from the initial TransE, TransH, DistMult et al to the current state-of-the-art ConvE.
Bi, Jinbo, He, Xiaodong, Huang, Jing, Shang, Chao, Tang, Yun, Zhou, Bowen   +5 more
core   +1 more source

Drug-target interaction prediction based on spatial consistency constraint and graph convolutional autoencoder

BMC Bioinformatics, 2023
Background Drug-target interaction (DTI) prediction plays an important role in drug discovery and repositioning. However, most of the computational methods used for identifying relevant DTIs do not consider the invariance of the nearest neighbour ...
Peng Chen, Haoran Zheng
doaj   +1 more source

Graph convolutional networks for graphs containing missing features

Future Generation Computer Systems, 2021
Graph Convolutional Network (GCN) has experienced great success in graph analysis tasks. It works by smoothing the node features across the graph. The current GCN models overwhelmingly assume that the node feature information is complete. However, real-world graph data are often incomplete and containing missing features.
Hibiki Taguchi, Xin Liu 0020, Tsuyoshi Murata   +2 more
openaire   +2 more sources

Texoskeletons: Developing the Fundamental Technologies for Creating Intelligent Soft Robotic Clothing With Integrated 1D Sensors and Actuators

Advanced Functional Materials, EarlyView.
ABSTRACT Traditional wearable exoskeletons rely on rigid structures, which limit comfort, flexibility, and everyday usability. This work introduces the fundamental technologies to create the first soft, lightweight, intelligent textile‐based exoskeletons (Texoskeletons) built using 1D sensors and actuators.
Amy Lukomiak, Rameesh Bulathsinghala, Jack Varga, Shuxin Meng, Kalana Marasinghe, Imaad Refai, Biyon Fernando, Amitkumar Patel, Chamika M. Halloluwa‐Arachchige, Carlos Oliveira, Arash M. Shahidi, Zahra Rahemtulla, Alexander Turner, Ziyun Ding, Bernard X. W. Liew, Andy Kerr, Ezio Preatoni, Theo Hughes‐Riley, Ishara Dharmasena, Pasindu Lugoda   +19 more
wiley   +1 more source

Sports behavior analysis technology based on GCN and domain knowledge graph

Discover Computing
To improve the performance of sports behavior recognition, the spatial temporal graph convolutional network is introduced to analyze the spatial temporal features of sports behavior, achieving accurate action recognition. In the experimental results, the
Jiaojiao Hu, Shengnan Ran
doaj   +1 more source

Relational graph convolutional networks: a closer look

PeerJ Computer Science, 2022
In this article, we describe a reproduction of the Relational Graph Convolutional Network (RGCN). Using our reproduction, we explain the intuition behind the model. Our reproduction results empirically validate the correctness of our implementations using benchmark Knowledge Graph datasets on node classification and link prediction
Thiviyan Thanapalasingam, Lucas van Berkel, Peter Bloem, Paul Groth   +3 more
openaire   +7 more sources

Packed for Ossification: High‐Density Bioprinting of hPDC Spheroids in HAMA Toward Endochondral Ossification

Advanced Healthcare Materials, EarlyView.
Human periosteum‐derived cell spheroids bioprinted at high density within a hyaluronic acid matrix promote fusion and hypertrophic cartilage formation in vitro. Early encapsulation enhances spheroid interaction and matrix maturation, generating scalable cartilage templates intended for endochondral bone regeneration.
Ane Albillos Sanchez, Maria Paula Marks, Paula Casademunt, Adrián Seijas‐Gamardo, Ioannis Papantoniou, Lorenzo Moroni, Carlos Mota   +6 more
wiley   +1 more source

Linear Graph Convolutional Networks. [PDF]

, 2020
Many neural networks for graphs are based on the graph convolution operator, proposed more than a decade ago. Since then, many alternative definitions have been proposed, that tend to add complexity (and non-linearity) to the model. In this paper, we follow the opposite direction by proposing a linear graph convolution operator. Despite its simplicity,
Navarin N., Erb W., Pasa L., Sperduti A.
openaire   +1 more source

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

Advanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 more
wiley   +1 more source