*.csv

Readily available animal tissue such as ground beef is a convenient material for mimicking the dielectric properties of biological tissue when validating microwave imaging and sensing hardware and techniques. The reliable use of these materials depends on the accurate characterization of their properties. Tissue water content is a dominant factor in microwave frequency tissue properties, thus the effect of dehydration must be considered. The dependence of tissue properties on hydration is also important for new applications of microwave sensing for hydration monitoring.

This dataset has EV charging data from 2019 to the present day. SFU's Burnaby campus currently has two different types of Electric Vehicle Charging Stations on campus. There is no additional charge to use the station; however, the Permit or Daily Rate required in each lot remains in effect for the EV Reserved stalls.

To utilize a quantum annealing system such as D-Wave's to solve a graph coloring problem,
it is necessary to convert the utility polynomial into a quadratic polynomial in binary variables.
This is called QUBO (quadratic unconstrained binary optimization) problem.
In any degree reduction process, we need to introduce auxiliary variables,
and more variables we have in the QUBO problem, less likely a
quantum annealing system can find an optimal solution.
The current degree reduction methods applies to monomials.

This dataset consists of “.csv” files of 4 different routing attacks (Blackhole Attack, Flooding Attack, DODAG Version Number Attack, and Decreased Rank Attack) targeting the RPL protocol, and these files are taken from Cooja (Contiki network simulator). It allows researchers to develop IDS for RPL-based IoT networks using Artificial Intelligence and Machine Learning methods without simulating attacks. Simulating these attacks by mimicking real-world attack scenarios is essential to developing and testing protection mechanisms against such attacks.