This research addresses the pressing global demand for food by leveraging cutting-edge deep learning techniques for automating plant disease detection. Focusing on tomato and potato leaf diseases, the study utilized t...
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A collaborative system that includes mobile devices (MDs), edge nodes (ENs), and the cloud is needed where ENs at the network edge can run offloaded tasks of MDs with limited resources and energy for timely processing...
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Lately, there has been a lot of interest in game-theoretic approaches to the trajectory planning of autonomous vehicles (AVs). But most methods solve the game independently for each AV while lacking coordination mecha...
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Lately, there has been a lot of interest in game-theoretic approaches to the trajectory planning of autonomous vehicles (AVs). But most methods solve the game independently for each AV while lacking coordination mechanisms, and hence result in redundant computation and fail to converge to the same equilibrium, which presents challenges in computational efficiency and safety. Moreover, most studies rely on the strong assumption of knowing the intentions of all other AVs. This paper designs a novel autonomous vehicle trajectory planning approach to resolve the computational efficiency and safety problems in uncoordinated trajectory planning by exploiting vehicle-to-everything (V2X) technology. Firstly, the trajectory planning for connected and autonomous vehicles (CAVs) is formulated as a game with coupled safety constraints. We then define the interaction fairness of the planned trajectories and prove that interaction-fair trajectories correspond to the variational equilibrium (VE) of this game. Subsequently, we propose a semi-decentralized planner for the vehicles to seek VE-based fair trajectories, in which each CAV optimizes its individual trajectory based on neighboring CAVs’ information shared through V2X, and the roadside unit takes the role of updating multipliers for collision avoidance constraints. The approach can significantly improve computational efficiency through parallel computing among CAVs, and enhance the safety of planned trajectories by ensuring equilibrium concordance among CAVs. Finally, we conduct Monte Carlo experiments in multiple situations at an intersection, where the empirical results show the advantages of SVEP, including the fast computation speed, a small communication payload, high scalability, equilibrium concordance, and safety, making it a promising solution for trajectory planning in connected traffic scenarios. To the best of our knowledge, this is the first study to achieve semi-distributed solving of a game with coupled constr
Multi-object tracking (MOT) is one of the most important problems in computer vision and a key component of any vision-based perception system used in advanced autonomous mobile robotics. Therefore, its implementation...
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Managing fluctuating workloads and optimizing resource utilization in cloud environments pose significant challenges, particularly in fields requiring real-time data processing, such as healthcare. This paper introduc...
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For permanent magnet synchronous machines(PMSMs),accurate inductance is critical for control design and condition *** to magnetic saturation,existing methods require nonlinear saturation model and measurements from mu...
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For permanent magnet synchronous machines(PMSMs),accurate inductance is critical for control design and condition *** to magnetic saturation,existing methods require nonlinear saturation model and measurements from multiple load/current conditions,and the estimation is relying on the accuracy of saturation model and other machine parameters in the *** harmonic produced by harmonic currents is inductance-dependent,and thus this paper explores the use of magnitude and phase angle of the speed harmonic for accurate inductance *** estimation models are built based on either the magnitude or phase angle,and the inductances can be from d-axis voltage and the magnitude or phase angle,in which the filter influence in harmonic extraction is considered to ensure the estimation *** inductances can be estimated from the measurements under one load condition,which is free of saturation ***,the inductance estimation is robust to the change of other machine *** proposed approach can effectively improve estimation accuracy especially under the condition with low current *** and comparisons are conducted on a test PMSM to validate the proposed approach.
We develop a general framework for clustering and distribution matching problems with bandit feedback. We consider a K-armed bandit model where some subset of K arms is partitioned into M groups. Within each group, th...
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Text mining techniques, particularly those leveraging machine learning for natural language processing, have gained significant attention for qualitative data analysis in software testing. However, their complexity an...
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Moving target defense (MTD) is a promising approach to defend against load redistribution attacks on the internet-of-things (IoT)-based smart grid networks by probing the distorted state estimates with the distributed...
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Abnormal event detection in video surveillance is critical for security, traffic management, and industrial monitoring applications. This paper introduces an innovative methodology for anomaly detection in video data,...
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