Sentence examples for detection data sets from inspiring English sources

Clearly, the relative lack of high-quality Intrusion Detection data sets is a problem for the academic research community.

Another important consideration is that Intrusion Detection data sets should also accommodate many diverse heterogeneous security sources to adequately address the issue of improving situational awareness.

It is important to understand where and how feature selection can be applied effectively, especially with regards to unstable Intrusion Detection data sets.

Many authors discuss the problems with existing public Intrusion Detection data sets: for example, Sommer and Paxson [25] give an excellent summary regarding some of the underlying reasons why this is a significant problem.

Our results show that the proposed model can deal with highly expressive and partially occluded faces while outperforming the state-of-the-art face detectors by a large margin on challenging benchmarks such as the Face Detection Data Set and Benchmark (FDDB) [1] and the Annotated Facial Landmarks in the Wild (AFLW) [2] databases.

This section addresses some issues found with Intrusion Detection data set challenges and feature selection.

Various techniques and issues such as those mentioned in the preceding paragraph and in the Intrusion Detection Data Set Challenges section should be considered when developing such data sets.

Using the observed data from the detection data set and simplified adapting it to the bi-allelic case to derive a power estimate for the confirmatory sample using Quanto 1.2.4, we estimated that 363 trios would have a power of 97% to detect an RR effect of RR = 1.7 under a log-additive mode of inheritance (minor allele frequency 15%, αtwo-sided = 0.05).

Two data sets were created; one was the assembly data set and the other the SNP detection data set.

The SNP detection was performed with MAQ [ 19] (default parameters) using the SNP detection data set and one of the reference genomes (c50, c50ca, or c50caB).

In the SNP detection data set, we required a per base quality score of at least 10 if the read was singly represented.