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Kyle DeMedeiros, Chan Young Koh and Abdeltawab Hendawi
The Chicago Array of Things (AoT) is a robust dataset taken from over 100 nodes over four years. Each node contains over a dozen sensors. The array contains a series of Internet of Things (IoT) devices with multiple heterogeneous sensors connected to a p...
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Yuyan Zheng, Jianhua Qu and Jiajia Yang
Similarity measures in heterogeneous information networks (HINs) have become increasingly important in recent years. Most measures in such networks are based on the meta path, a relation sequence connecting object types. However, in real-world scenarios,...
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Fengjie Xie, Xiao Wang and Cuiping Ren
The Belt and Road has developed rapidly in recent years. Constructing a comprehensive traffic network is conducive to promoting the development of the the Belt and Road. To optimize the layout of the Belt and Road comprehensive traffic network, this pape...
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Thang Trung Nguyen, Hung Duc Nguyen and Minh Quan Duong
The paper applies jellyfish search algorithm (JSA) for reaching the maximum profit of IEEE 30-node and IEEE 118-node transmission power networks considering electrical market and wind turbines (WTs). JSA is compared with the particle swarm optimization (...
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Sejeong Kim and Jongho Park
Recently, an Unmanned Aerial Vehicle (UAV)-based Wireless Sensor Network (WSN) for data collection was proposed. Multiple UAVs are more effective than a single UAV in wide WSNs. However, in this scenario, many factors must be considered, such as collisio...
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Ying Zhang, Qi Zhang, Yu Zhang and Zhiyuan Zhu
Ocean wireless sensor networks (OWSNs) play an important role in marine environment monitoring, underwater target tracking, and marine defense. OWSNs not only monitor the surface information in real time but also act as an important relay layer for under...
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Jingjing Liu, Xinli Yang, Denghui Zhang, Ping Xu, Zhuolin Li and Fengjun Hu
Multi-node wind speed forecasting is greatly important for offshore wind power. It is a challenging task due to unknown complex spatial dependencies. Recently, graph neural networks (GNN) have been applied to wind forecasting because of their capability ...
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Jianhe Li and Suohai Fan
In recent years, graph neural networks (GNNs) have played an important role in graph representation learning and have successfully achieved excellent results in semi-supervised classification. However, these GNNs often neglect the global smoothing of the...
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Zhiyuan Wang, Hong Ni and Rui Han
As the Internet communication model changes from host-centric to content-centric, information-centric networking (ICN) as a new network architecture has received increasing attention. There are often multiple replicas of content in ICN, and how to reason...
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Fotis Nikolaidis, Moysis Symeonides and Demetris Trihinas
Federated learning (FL) is a transformative approach to Machine Learning that enables the training of a shared model without transferring private data to a central location. This decentralized training paradigm has found particular applicability in edge ...
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