Reliability
Vibration measurement on SAG mill drive motor for Energy harvesting or predictive maintenance
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We introduce a new database of voice recordings with the goal of supporting research on vulnerabilities and protection of voice-controlled systems (VCSs). In contrast to prior efforts, the proposed database contains both genuine voice commands and replayed recordings of such commands, collected in realistic VCSs usage scenarios and using modern voice assistant development kits.
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This dataset accompanies the article "Palisade: A Framework for Anomaly Detection in Embedded Systems." It contains traces, programs, and specifications used in the case studies from the paper.
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The aircraft fuel distribution system has two primary functions: storing fuel and distributing fuel to the engines. These functions are provided in refuelling and consumption phases, respectively. During refuelling, the fuel is first loaded in the Central Reservation Tank and then distributed to the Front and Rear Tanks. In the consumption phase, the two engines receive an adequate level of fuel from the appropriate tanks. For instance, the Port Engine (PE) will receive fuel from Front Tank and the Starboard Engine (SE) will receive fuel from Rear Tank.
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Data for 24-node, 54-node, 86-node, and 138-node test networks for reliability-oriented distribution expansion planning applications; and the results for 24-node and 54-node systems.
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Analysis data
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Collision detection (CD) is a key capability of carrier sense multiple access (CSMA) based medium access control (MAC) protocol. Applying CD, the transmitter can abort transmission immediately so that the power can be saved. This technique does not need the peer receiver to give feedback on whether there is a packet collision, and hence, the overall overhead is significantly low. The challenge, however, is to operate in transmit time and instantly detect the week colliding signal in the presence of strong self-interference (SI).
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This folder contains two csv files and one .py file. One csv file contains NIST ground PV plant data imported from https://pvdata.nist.gov/. This csv file has 902 days raw data consisting PV plant POA irradiance, ambient temperature, Inverter DC current, DC voltage, AC current and AC voltage. Second csv file contains user created data. The Python file imports two csv files. The Python program executes four proposed corrupt data detection methods to detect corrupt data in NIST ground PV plant data.
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