This dataset is a collection of brainwave EEG signals from eight subjects. The data is collected in a lab controlled environment under a specific visualization experiment. 

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A simple dataset that gives the processing cost (in cycles) for verifying multiple messages signed with ECDSA and implicitly certified public keys. It considers two implicit certification models: ECQV and SIMPL. 

 

This dataset is used in article "Schnorr-based implicit certification: improving the security and efficiency of vehicular communications", submitted to IEEE Transactions on Computers. Namely, it is used as basis for building that article's Figure 2.

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This dataset includes two kinds of dust experiment data.

(1)    blackbody furnace experiment data

(2)    water cup experiment data

The two experiments were carried out in a lab by using blackbody furnace, infrared thermal imager and dust. The specific parameter can be found in the data file.

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The analysis is based on two kinds of measured dataset. In both cases, uplink data are measured (A-UL0) i.e. the transmitters are UBSs and the receiver is UBSC and FDD is used. The first dataset has been collected from August 17, 2018, to August 20, 2018. The experiment has been carried over two separate distances, i.e., 1 km, and 3 km between the transmitter (Tx) and receiver (Rx) in Mohang Port (Taean-gun).  

 

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