6 accepted papers
Lower limb exoskeletons have shown great promise for enhancing mobility. Existing systems are limited by either excessive weight or insufficient torque output. In this study, we present a cable-driven hip extension exoskeleton featuring lightweight, compact, and compliant end-effectors with high-tor
Temporal Graph Neural Networks (TGNNs) lay emphasis on capturing node interactions over time but often overlook evolution in node classes and dynamic data distributions triggered by the continuous emergence of new class labels, known as the open-set problem. This problem poses challenges for existin…
Recently, deep graph neural networks (GNNs) have emerged as the predominant architecture for recommender systems based on collaborative filtering. Nevertheless, numerous GNN-based approaches confront challenges such as complex computations and skewed feature distributions, especially with high-dimen…
Electrocardiography(ECG) is a non-invasive tool used to identify the cardiovascular diseases. ECG classification studies have been concerned and made progress well. However, the problems about categories imbalance and absence of labelled clinic data are still dramatically hindered research developme…
Graph classification is a challenging research task in many applications across a broad range of domains. Recently, Graph Neural Network (GNN) models have achieved superior performance on various real-world graph datasets. Despite their successes, most of current GNN models largely suffer from the u…
High contour accuracy is vital to the multi-axis motion system. Improvement in the contour accuracy of the parallel kinematic machine (PKM) has being a challenging issue in the process of its practical application. In analogy to the intelligent structure of the organisms, this paper proposes a smart…