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Sungwon Moon, Seolwon Koo, Yujin Lim and Hyunjin Joo
With recent technological advancements, the commercialization of autonomous vehicles (AVs) is expected to be realized soon. However, it is anticipated that a mixed traffic of AVs and human-driven vehicles (HVs) will persist for a considerable period unti...
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Hy Nguyen, Srikanth Thudumu, Hung Du, Kon Mouzakis and Rajesh Vasa
Several approaches have applied Deep Reinforcement Learning (DRL) to Unmanned Aerial Vehicles (UAVs) to do autonomous object tracking. These methods, however, are resource intensive and require prior knowledge of the environment, making them difficult to...
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Bin Li, Caijie Yang and Zhongzhen Yang
In response to the evolving challenges of the integration and combination of multiple container terminal operations under berth water depth constraints, the multi-terminal dynamic and continuous berth allocation problem emerges as a critical issue. Based...
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Shao Xuan Seah and Sutthiphong Srigrarom
This paper explores the use of deep reinforcement learning in solving the multi-agent aircraft traffic planning (individual paths) and collision avoidance problem for a multiple UAS, such as that for a cargo drone network. Specifically, the Deep Q-Networ...
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Chengpeng Jiang, Shuai Chen, Jinglin Li, Haoran Wang, Jing Wang, Taian Xu and Wendong Xiao
Wireless energy transfer technology (WET)-enabled mobile charging provides an innovative strategy for energy replenishment in wireless rechargeable sensor networks (WRSNs), where the mobile charger (MC) can charge the sensors sequentially by WET accordin...
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Antonio Maci, Alessandro Santorsola, Antonio Coscia and Andrea Iannacone
Web phishing is a form of cybercrime aimed at tricking people into visiting malicious URLs to exfiltrate sensitive data. Since the structure of a malicious URL evolves over time, phishing detection mechanisms that can adapt to such variations are paramou...
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Yuxin Zhao, Yanlong Liu and Xiong Deng
The observation path planning of an ocean mobile observation network is an important part of the ocean mobile observation system. With the aim of developing a traditional algorithm to solve the observation path of the mobile observation network, a comple...
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Minh Tran, Duc Pham-Hi and Marc Bui
In this paper, we propose a novel approach to optimize parameters for strategies in automated trading systems. Based on the framework of Reinforcement learning, our work includes the development of a learning environment, state representation, reward fun...
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Zeyang Wang, Jun Huang and Mingxu Yi
Unmanned aerial helicopters (UAHs) have been widely used recently for reconnaissance operations and other risky missions. Meanwhile, the threats to UAHs have been becoming more and more serious, mainly from radar and flights. It is essential for a UAH to...
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Tongyang Xu, Yuan Liu, Zhaotai Ma, Yiqiang Huang and Peng Liu
As a new distributed machine learning (ML) approach, federated learning (FL) shows great potential to preserve data privacy by enabling distributed data owners to collaboratively build a global model without sharing their raw data. However, the heterogen...
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