Energy Efficiency
The integration of uncrewed aerial vehicles (UAVs)
with fifth-generation (5G) cellular networks has been a prominent
research focus in recent years and continues to attract significant
interest in the context of sixth-generation (6G) wireless networks.
UAVs can serve as aerial wireless platforms to provide on-demand
coverage, mobile edge computing, and enhanced sensing and
communication services. However, UAV-assisted networks present
new opportunities and challenges due to the inherent size, weight,
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This dataset contains two subjects. The first one is a Matlab App created for PMSMs (Permanent Magnet Synchronous Motors) parameters estimation, both in the electrical and in the mechanical energetic domains. The second one is a generalized PMSM Simulink superblock equipped with a user-friendly interface allowing to select options and to input the model parameters. The Matlab App and the PMSM superblock can be easily interfaced with each other.
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This work develops a novel power control framework for energy-efficient powercontrol in wireless networks. The proposed method is a new branch-and-boundprocedure based on problem-specific bounds for energy-efficiency maximizationthat allow for faster convergence. This enables to find the global solution forall of the most common energy-efficient power control problems with acomplexity that, although still exponential in the number of variables, is muchlower than other available global optimization frameworks.
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Matlab Simulink was used to develop an emulator for the Viessmann Vitorond 200 Gas Fired Boiler VD2 Series 380 and a series of faults were modeled along with normal data across the expected range of operation to create a labelled dataset with approximately 27,500 cases for training and testing boiler fault classification models.
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An emulator for the Viessmann Vitorond 200 Gas Fired Boiler VD2 Series 380 dataset was created in Matlab/Simulink based on the Simscape boiler model.
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High energy consumption is a challenging issue that an ever increasing number of mobile applications face today.
However, energy consumption is being tested in an ad hoc way, despite being an important non-functional requirement of an application.
Such limitation becomes particularly disconcerting during software testing: on the one hand, developers do not really know how to measure energy; on the other hand, there is no knowledge as to what is the energy overhead imposed by the testing framework.
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