On the difficulty of achieving differential privacy in practice: User-level safeguards in aggregated location data: Although large-scale human mobility data contains crucial information for understanding human behavior, it is also very sensitive.
In the work developed by Bassolas et al., we studied the structure of cities and their impact on urban livability using a highly aggregated mobility dataset. In order to protect privacy, random noise was added using an automated Laplace mechanism (ε, δ)-differential privacy, with ε =0.66 and δ =2.1×10−29. Where ε defines the noise intensity and δ represents the deviation from pure ε privacy. Differential privacy mathematically guarantees that a person, who observes the result of a differential private analysis, is likely to produce the same inference about one's private information or not, that person's private information is combined as input for the analysis
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That species has genes that yield red, pink or white flowers. The pink gene is dominant. All hybrids contain red/white genes, but they are recessive. Thus, the cross can unite red/white genes in hybrids with no pink, yielding red/white flowers.
There are 9 phylum of the animal kingdom. Hope this helps!