In this paper, we propose a malicious user detection scheme for overlapping communities based on community topic propagation prediction. First, we construct a malicious topic classification model based on topic text f...
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Accurate prediction of battery state of health (SOH) and remaining useful life (RUL) is crucial for reducing the risk of lithium battery failure and intelligent management of energy storage power plants. Currently, mo...
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Recent advancements in AI and ML have brought on substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, amongst a few. AI and ML models are in...
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This paper proposes an efficient hierarchical solution framework, null-space guidance vector field (NSGVF) with deep reinforcement learning (DRL) based coefficient adjustment, to solve the problem of obstacle avoidanc...
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The Dynamic Resource Allocation Multi-Objective Optimization Algorithm (MOEA/D-DRA) is a method for solving multi-objective optimization problems (MOPs). This algorithm enhances the performance of the original MOEA/D ...
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Existing terramechanics-based dynamic models for tracked vehicles (TRVs) are widely used in dynamics analysis. However, these models are incompatible with model-based controller design due to their high complexity and...
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Existing terramechanics-based dynamic models for tracked vehicles (TRVs) are widely used in dynamics analysis. However, these models are incompatible with model-based controller design due to their high complexity and computational costs. This study presents a novel and simplified terramechanics-based dynamic model for TRVs that can be used in optimization-based real-time motion controller design. To this end, we approximated the track-ground interactions with an averaged term of the track-ground shear stresses to make the model computationally efficient and linearizable. By introducing the concepts of slip ratio and slip angle in the field of wheeled vehicles, the terramechanics-based dynamic model was finally simplified into a compact and practical single-track dynamic model reducing the demand for precise slip ratio measurements. The single-track model enables us to design an efficient motion control scheme by considering lateral and longitudinal dynamics separately. Finally, the proposed dynamic model was verified and validated under various road conditions using a real TRV. Additionally, the performance of different models was compared in simulation as an example to demonstrate that the proposed model outperforms the existing ones in TRV path-following tasks. IEEE
Graph neural networks(GNNs)have achieved state-of-the-art performance on graph classification tasks,which aim to pre-dict the class labels of entire graphs and have widespread ***,existing GNN based methods for graph ...
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Graph neural networks(GNNs)have achieved state-of-the-art performance on graph classification tasks,which aim to pre-dict the class labels of entire graphs and have widespread ***,existing GNN based methods for graph classification are data-hungry and ignore the fact that labeling graph examples is extremely expensive due to the intrinsic *** import-antly,real-world graph data are often scattered in different *** by these observations,this article presents federated collaborative graph neural networks for few-shot graph classification,termed *** its owned graph examples,each client first trains two branches to collaboratively characterize each graph from different views and obtains a high-quality local few-shot graph learn-ing model that can generalize to novel categories not seen while *** each branch,initial graph embeddings are extracted by any GNN and the relation information among graph examples is incorporated to produce refined graph representations via relation aggrega-tion layers for few-shot graph classification,which can reduce over-fitting while learning with scarce labeled graph ***,multiple clients owning graph data unitedly train the few-shot graph classification models with better generalization ability and effect-ively tackle the graph data island *** experimental results on few-shot graph classification benchmarks demonstrate the ef-fectiveness and superiority of our proposed framework.
Knowledge graphs have emerged as powerful tools for representing and organizing information in a structured and interconnected manner. In this research, we aim to build a knowledge graph and a recommendation system fo...
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Distributed Denial Service of Service (DDoS) is very sophisticated attack which brute-force packet jamming to a network to render it useless, if done with large number of nodes. It can be easily countered by a number ...
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Diffusion MRI tractography is employed to delineate the white matter tracts in the brain, which plays a pivotal role in investigating brain development and psychiatric disorders. The segmentation of fibers into cohere...
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