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Following a series of unusual transmission system disturbances involving unexpected IBR behaviors, there has been a significant need for monitoring, control, and protection functions that can help system operators more rapidly understand and respond to these disturbances. The IBR-rich transmission system datakit (IRTSD) is focused on transient disturbances in IBR-rich transmission systems and consists of a dataset, power system model, and automation scripting.
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253 Views
This paper presents a comparative study of sampling methods within the FedHome framework, designed for personalized in-home health monitoring. FedHome leverages federated learning (FL) and generative convolutional autoencoders (GCAE) to train models on decentralized edge devices while prioritizing data privacy. A notable challenge in this domain is the class imbalance in health data, where critical events such as falls are underrepresented, adversely affecting model performance.
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161 Views
This paper investigated how to increase the number of connections among users in hierarchical non-terrestrial networks (HNTNs) assisted disaster relief service (DRS). We aim to maximize the number of satisfactory connections (NSCs) by optimizing the unmanned aerial vehicles (UAV) radio resources, computing resources, and trajectory at each time slot. In particular, the UAVs are exploited as aerial base stations (ABSs) to provide a link for the reduced capability (RedCap) user equipment (UE) based on power domain non-orthogonal multiple access (PD-NOMA).
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587 Views
The Internet of Things (IoT) is reshaping our connected world, due to the prevalence of lightweight devices connected to the Internet and their communication technologies. Therefore, research towards intrusion detection in the IoT domain has a lot of significance. Network intrusion datasets are fundamental for this research, as many attack detection strategies have to be trained and evaluated using these datasets.
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2262 Views