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Ryota Higashimoto, Soh Yoshida and Mitsuji Muneyasu
This paper addresses the performance degradation of deep neural networks caused by learning with noisy labels. Recent research on this topic has exploited the memorization effect: networks fit data with clean labels during the early stages of learning an...
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Guoqing Zhang, Shilin Yin, Chenfeng Huang and Weidong Zhang
This paper focuses on the intervehicle security-based robust formation control of unmanned surface vehicles (USVs) to implement the formation switch mission. In the scheme, a novel adaptive potential ship (APS)-based guidance principle is developed to pr...
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Yi Ren, Lei Zhang, Wenbin Huang and Xi Chen
This study describes a circular curve path-following controller for an underactuated unmanned surface vessel (USV) experiencing unmodeled dynamics and external disturbances. Initially, a three degrees of freedom kinematic model of the USV is proposed for...
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Weixiang Zhou, Mengyan Ning, Jian Ren and Jiqiang Xu
An effective path-following controller is a guarantee for stable sailing of underactuated unmanned surface vehicles (USVs). This paper proposes an event-triggered robust control approach considering an unknown model nonlinearity, external disturbance, an...
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Ruben Tapia-Olvera, Francisco Beltran-Carbajal and Antonio Valderrabano-Gonzalez
The synchronous generator is one of the most important active components in current electric power systems. New control methods should be designed to guarantee an efficient dynamic performance of the synchronous generator in strongly interconnected nonli...
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Mateusz Malarczyk, Mateusz Zychlewicz, Radoslaw Stanislawski and Marcin Kaminski
In this paper, the problem of the remote control of electric drives with a complex mechanical structure is discussed. Oscillations of state variables and control precision are the main issues found in such applications. The article proposes a smart, IoT-...
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Cihan Ates, Dogan Bicat, Radoslav Yankov, Joel Arweiler, Rainer Koch and Hans-Jörg Bauer
In this study, we propose a population-based, data-driven intelligent controller that leverages neural-network-based digital twins for hypothesis testing. Initially, a diverse set of control laws is generated using genetic programming with the digital tw...
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Petros Brimos, Areti Karamanou, Evangelos Kalampokis and Konstantinos Tarabanis
Traffic forecasting has been an important area of research for several decades, with significant implications for urban traffic planning, management, and control. In recent years, deep-learning models, such as graph neural networks (GNN), have shown grea...
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Abubakar Ahmad Musa, Adamu Hussaini, Cheng Qian, Yifan Guo and Wei Yu
The Internet of Things (IoT) constitutes a vast network comprising various components such as physical devices, vehicles, buildings, and other items equipped with sensors, actuators, and software. These components are interconnected, facilitating the col...
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Alice Wang, Rozita Dara, Samira Yousefinaghani, Emily Maier and Shayan Sharif
Infectious diseases take a large toll on the global population, not only through risks of illness but also through economic burdens and lifestyle changes. With both emerging and re-emerging infectious diseases increasing in number, mitigating the consequ...
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