With the growth of age, the body function of the elderly gradually declines, and falling has become the main factor endangering the life safety of the elderly. In order to solve the problem of the lack of data support...
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Residue theorem is an important part of complex variable functions, and its theorems have been widely used in real life, such as mathematics, physics and computer fields, but because the residue theorem is the most di...
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Spiking Neural Networks (SNN) are biologically inspired networks working on the principle of communication triggered while crossing of threshold potentials. During the COVID-19 pandemic, immunity has been acquired by ...
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Digital filter design plays a crucial role in signal processing applications, aiming to enhance, extract, or suppress specific components of a signal. Soft computing techniques have emerged as effective methods for de...
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The progress of science, technology, and innovation is greatly aided by the advancement, improvement, and use of methodology. Our work developed a Characteristic Recognition Algorithm based on text mining to extract m...
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In the context of the Industrial Internet of Things (IIoT), multiple access edge computing (MEC) enables the provision of computational resources closer to users. The work presented in this paper explores a common IIo...
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ISBN:
(纸本)9781728190549
In the context of the Industrial Internet of Things (IIoT), multiple access edge computing (MEC) enables the provision of computational resources closer to users. The work presented in this paper explores a common IIoT application scenario wherein autonomous mobile robots (AMR) operate in a MEC-enabled network and depend on multimedia content stored at the MEC servers over the course of operation. The age of information (AoI) metric is used to measure the freshness of the cached content from the perspective of the AMR. At the same time, the energy cost associated with refreshing the cache files is simultaneously considered as well. This paper delves into achieving an optimal trade-off between minimizing the weighted AoI cost and the energy expended for cache refreshing. We address this problem by introducing a cache refreshing-deep deterministic policy gradient (CR-DDPG) algorithm, a model-free deep reinforcement learning method, to optimize both AoI and energy usage. Various simulation studies are conducted to evaluate the proposed CR-DDPG algorithm, and the results demonstrate that CR-DDPG consistently outperforms its baseline counterparts, rendering it a robust approach for cache-refreshing in dynamic IIoT environments.
This technical summary examines the design and violation analysis of analog and virtual circuits with bilateral complementary switches. The primary consciousness is on examining the electric traits and operation of sw...
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The rapid growth of social media has amplified the dissemination of hate speech, posing a substantial threat to online communities. While traditional text-based approaches have limitations, e.g., they often fall short...
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adverse transfer learning for Left Ventricle Segmentation in Cardiac CT photos is an emerging method in clinical photograph analysis. It pursues to transfer the learned expertise from a source area to a goal area, tha...
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The rapid development of intelligent transportation technology has promoted the progress of multiple trains cooperative technology. This paper proposes an online cooperative cruise control method based on improved par...
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