Zobrazeno 1 - 10
of 348
pro vyhledávání: '"Wang Lujia"'
Publikováno v:
e-Polymers, Vol 23, Iss 1, Pp 724-38 (2023)
For microscopic analysis of the effect of doping with carbon nanotubes (CNTs) of different radii on the thermal and mechanical properties of addition liquid silicone rubber (ALSR) composites, models of pure silicone rubber and silicone rubber composi
Externí odkaz:
https://doaj.org/article/ac1c848aba12498f996f39d02572a974
Publikováno v:
e-Polymers, Vol 22, Iss 1, Pp 821-833 (2022)
The dry-type on-board traction transformer (DOBTT) has the characteristics of huge heat generation and high heat dissipation requirements, so it has higher requirements for heat dissipation performance of epoxy resin (EP) insulation. However, the tou
Externí odkaz:
https://doaj.org/article/145e1ba3088645af84c1328240445452
With the expansion of the scale of robotics applications, the multi-goal multi-agent pathfinding (MG-MAPF) problem began to gain widespread attention. This problem requires each agent to visit pre-assigned multiple goal points at least once without c
Externí odkaz:
http://arxiv.org/abs/2404.19518
Autor:
Wei, Hexiang, Jiao, Jianhao, Hu, Xiangcheng, Yu, Jingwen, Xie, Xupeng, Wu, Jin, Zhu, Yilong, Liu, Yuxuan, Wang, Lujia, Liu, Ming
Simultaneous Localization and Mapping (SLAM) technology has been widely applied in various robotic scenarios, from rescue operations to autonomous driving. However, the generalization of SLAM algorithms remains a significant challenge, as current dat
Externí odkaz:
http://arxiv.org/abs/2404.08563
Autor:
Hu, Xiangcheng, Zheng, Linwei, Wu, Jin, Geng, Ruoyu, Yu, Yang, Wei, Hexiang, Tang, Xiaoyu, Wang, Lujia, Jiao, Jianhao, Liu, Ming
Accurately generating ground truth (GT) trajectories is essential for Simultaneous Localization and Mapping (SLAM) evaluation, particularly under varying environmental conditions. This study introduces a systematic approach employing a prior map-assi
Externí odkaz:
http://arxiv.org/abs/2401.17826
Autor:
Wang, Lujia, Wang, Hairong, D'Angelo, Fulvio, Curtin, Lee, Sereduk, Christopher P., De Leon, Gustavo, Singleton, Kyle W., Urcuyo, Javier, Hawkins-Daarud, Andrea, Jackson, Pamela R., Krishna, Chandan, Zimmerman, Richard S., Patra, Devi P., Bendok, Bernard R., Smith, Kris A., Nakaji, Peter, Donev, Kliment, Baxter, Leslie C., Mrugała, Maciej M., Ceccarelli, Michele, Iavarone, Antonio, Swanson, Kristin R., Tran, Nhan L., Hu, Leland S., Li, Jing
Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learnin
Externí odkaz:
http://arxiv.org/abs/2401.00128
Ordinal learning (OL) is a type of machine learning models with broad utility in health care applications such as diagnosis of different grades of a disease (e.g., mild, modest, severe) and prediction of the speed of disease progression (e.g., very f
Externí odkaz:
http://arxiv.org/abs/2312.09540
In the field of robotics, the point cloud has become an essential map representation. From the perspective of downstream tasks like localization and global path planning, points corresponding to dynamic objects will adversely affect their performance
Externí odkaz:
http://arxiv.org/abs/2307.07260
Predicting accurate depth with monocular images is important for low-cost robotic applications and autonomous driving. This study proposes a comprehensive self-supervised framework for accurate scale-aware depth prediction on autonomous driving scene
Externí odkaz:
http://arxiv.org/abs/2304.10719
Multi-agent path finding (MAPF) is the problem of moving agents to the goal vertex without collision. In the online MAPF problem, new agents may be added to the environment at any time, and the current agents have no information about future agents.
Externí odkaz:
http://arxiv.org/abs/2301.04446