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Florin Leon, Marius Gavrilescu, Sabina-Adriana Floria and Alina Adriana Minea
This paper proposes a classification methodology aimed at identifying correlations between job ad requirements and transversal skill sets, with a focus on predicting the necessary skills for individual job descriptions using a deep learning model. The ap...
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Zongshun Wang, Ce Li, Jialin Ma, Zhiqiang Feng and Limei Xiao
In this study, we introduce a novel framework for the semantic segmentation of point clouds in autonomous driving scenarios, termed PVI-Net. This framework uniquely integrates three different data perspectives?point clouds, voxels, and distance maps?exec...
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Yuhan Li, Shuguang Zhang, Ruichen He and Florian Holzapfel
Urban Air Mobility (UAM) has emerged in response to increasing traffic demands. As UAM involves commercial flights in complex urban areas, well-established automation technologies are critical to ensure a safe, accessible, and reliable flight. However, t...
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Dibo Dong, Shangwei Wang, Qiaoying Guo, Yiting Ding, Xing Li and Zicheng You
Predicting wind speed over the ocean is difficult due to the unequal distribution of buoy stations and the occasional fluctuations in the wind field. This study proposes a dynamic graph embedding-based graph neural network?long short-term memory joint fr...
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Michalis K. Chondros, Anastasios S. Metallinos and Andreas G. Papadimitriou
Ensuring sea surface tranquility within port basins is of paramount importance for safe and efficient port operations and vessels? accommodation. The present study aims to introduce a robust numerical model based on mild-slope equations, capable of accur...
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