Most existing prescribed-time (PT) control results focus on the stabilization/regulation problem, with only a few results considering the tracking control problem. In this paper, an adaptive PT tracking control method...
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3D object detection play a pivotal role in various applications, such as autonomous driving and environmental perception. However, the challenging task of detecting targets (e.g., vehicles and pedestrians) in 3D point...
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Microgrids equipped with hybrid energy storage systems (ESSs) are increasingly critical for balancing the intermittency of renewable energy sources (RESs) and the fluctuations in demand. This paper introduces a novel ...
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The C language, traditionally used in developing safety-critical systems, often faces memory management issues, leading to potential vulnerabilities. Rust emerges as a safer and secure alternative, aiming to mitigate ...
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ISBN:
(数字)9783982674100
ISBN:
(纸本)9798331534646
The C language, traditionally used in developing safety-critical systems, often faces memory management issues, leading to potential vulnerabilities. Rust emerges as a safer and secure alternative, aiming to mitigate these risks with its robust memory protection features, making it suitable for producing reliable code in critical environments, such as the automotive industry. This study proposes employing Rust code hardened by control Flow Checking (CFC) in real-time embedded systems, which software is traditionally developed by Assembly and C languages. The methods have been implemented at the application level, i.e., in the Rust source code, to make them platform-agnostic. A methodology for leveraging the Rust advantages is presented, such as stronger security guarantees and modern features, to implement these methods more effectively. Highlighting a use case in the automotive sector, our research demonstrates the Rust capacity to enhance system reliability through CFC, especially against Random Hardware Faults. Two CFC algorithms from the literature, YACCA, and RACFED, have been implemented in the Rust language to assess their effectiveness, obtaining 46.5% Diagnostic Coverage for the YACCA method and 50.1% for RACFED. The proposed approach is aligned with functional safety standards, showcasing how Rust can balance safety requirements and cost considerations in industries reliant on software solutions for critical functionalities.
High node mobility, rapid topology changes provide specific challenges for vehicular ad hoc networks (VANETs), which have an immediate impact on the routing protocols' performance. Traditional approaches, like the...
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ISBN:
(数字)9798331542726
ISBN:
(纸本)9798331542733
High node mobility, rapid topology changes provide specific challenges for vehicular ad hoc networks (VANETs), which have an immediate impact on the routing protocols' performance. Traditional approaches, like the Optimized Link State Routing (OLSR) protocol, provide proactive route management but fail to fully account for critical dynamic parameters like link stability, relative vehicle speed, node distance, and bandwidth availability. This work proposes a hybrid method combining OLSR with Q-learning to facilitate real-time adaptive routing. The model leverages dynamic metrics to proactively evaluate links while employing Q-learning to optimize routing decisions based on rewards computed from performance factors like delay, packet loss rate, and link duration. Simulation results demonstrate that our approach significantly outperforms classic OLSR. The improvements include reduced packet loss rates, increased average throughput, lower average latency, and a reduction in control overhead. These findings confirm that integrating dynamic metrics and adaptive learning effectively addresses the challenges posed by VANETs.
In computational pathology, whole slide images represent the primary data source for AI-driven diagnostic algorithms. However, due to their high resolution and large size, these images undergo a patching phase. In thi...
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This paper examines finite-time (F-T) observer-based control of fractional-order nonlinear systems with time delay, employing the Takagi–Sugeno fuzzy (T-SF) approach. This study utilizes the conformable fractional de...
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Energy-based learning algorithms are alternatives to backpropagation and are well-suited to distributed implementations in analog electronic devices. However, a rigorous theory of convergence is lacking. We make a fir...
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One of the leading causes of cancer-related death for women is still breast cancer, which highlights the importance of early and precise diagnosis techniques. Despite medical imaging and deep learning advances, curren...
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In this paper, we present a geometric framework for the reachability analysis of attitude control systems. We model the attitude dynamics on the product manifold SO(3) × 3 and introduce a novel parametrized famil...
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