Modern urban development depends on optimizing cognitive sensor communications in smart cities, which is the focus of this investigation. In the era of expanding sensor networks, efficient data transmission is paramou...
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"Artificial lung" is a device that simulates breathing process of occupants in a room. This allows you to safely test, e.g., the impact of HVAC systems on the spread of pathogens. The paper describes the con...
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The AC-DC Energy Nodes (ADENs) concept offers a transformative approach to modernizing power grids, particularly in the context of supergrids. By centralizing power flows from diverse renewable energy sources, such as...
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ISBN:
(数字)9798350377170
ISBN:
(纸本)9798350377187
The AC-DC Energy Nodes (ADENs) concept offers a transformative approach to modernizing power grids, particularly in the context of supergrids. By centralizing power flows from diverse renewable energy sources, such as offshore wind farms, ADENs enable efficient long-distance power transmission through HVDC technology. This design enhances the balance of supply and demand across regions and countries, significantly improving grid stability and resilience. However, the implementation of ADENs presents substantial technical, regulatory, and cybersecurity challenges. This study delves into these challenges while also addressing the geopolitical complexities of transnational connections, underscoring the critical importance of policy alignment for successful deployment.
In recent years, the hyperspectral image (HSI) classification has attracted great attention in the field of earth observation. With the expansion of application scenarios and the continuous improvement of application ...
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Pneumonia is one of the top causes of death in Romania and early detection of this disease improves the recovery chances and shortens the length of hospitalization. In this work, we develop a solution for automatic pn...
Pneumonia is one of the top causes of death in Romania and early detection of this disease improves the recovery chances and shortens the length of hospitalization. In this work, we develop a solution for automatic pneumonia detection based on convolutional neural networks. Four network models are investigated. They are trained on 4.163 images from a public dataset and tested on 530 images. The best results are obtained by one of the proposed models conducting to a sensitivity of 98.72%, an accuracy of 89.81%, and ROC 93.46%. Thus, this research proposes a lightweight screening tool that can help triaging the patients with pneumonia.
The inherent black-box nature of deep reinforcement learning (DRL) poses challenges in ensuring safety constraints. This paper, therefore, introduces a DRL reward design inspired by Lyapunov stability theory for safe ...
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ISBN:
(数字)9798331508272
ISBN:
(纸本)9798331508289
The inherent black-box nature of deep reinforcement learning (DRL) poses challenges in ensuring safety constraints. This paper, therefore, introduces a DRL reward design inspired by Lyapunov stability theory for safe robot navigation in the presence of obstacles. The navigation problem is formulated as a state-space control problem with close obstacle locations integrated into the state representation. To ensure safe obstacle avoidance, we introduce a novel reward-shaping strategy utilizing a Lyapunov function that discourages fast movement toward obstacles. Our numerical experiments demonstrate the effectiveness of the reward design strategy compared to baselines in achieving consistent superior learning with higher mission completion rates while maintaining speeds closer to a desired target speed. In addition, we show that our reward design enables a generally smaller choice for the discount factor for value-function-based DRL algorithms, which can lead to faster convergence. This is possible since the reward design merely penalizes the one-step decay of the Lyapunov function. Furthermore, policy training simulations employ an early episode termination method to constrain exploration and add more valuable samples to the DRL training replay memory. Finally, real-world experiments with a quadrotor validate the ability of our method to safely navigate around varying densities of obstacles. The proposed method consistently takes cautious maneuvers near obstacles by slowing down, achieving greater obstacle clearance compared to baseline, although with an increase in mission completion time.
The increasing prevalence of smart building architectures, driven by the integration of Internet of Things (IoT) devices and automation systems, has led to a surge in energy consumption. This research explores the app...
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One-Sided Lipschitz (OSL) fractional order modeling is a top choice for solving the stabilization issue of nonlinear systems. Despite numerous studies on the subject, there remains a gap in understanding when it comes...
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Feature engineering is a crucial step in building well-performing machine learning pipelines. However, manually constructing highly predictive features is time-consuming and requires domain knowledge. Although the res...
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This study addresses the affine formation maneuver control of cooperative multi-agent systems (MAS) having periodic inter-agent communication for both static and dynamic leader cases. Here, we focus on the leader-foll...
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