As a final step of the recognition task, some systems also exploit pattern-recognition techniques based on the use of classifiers, or in combination with a shape analysis with gait detection [14, 17].
While AIDA uses data from the network layer, it treats the application layer as a black box and therefore cannot exploit patterns in application traffic flows.
In order to accurately and timely predict the workload on v-TerraFly, we propose new forecasting techniques to discover and exploit patterns in user visiting behaviors such as those observed in Figure 3.
Contact: [email protected]; [email protected] The ability to identify and exploit patterns of protein small-molecule interaction is a critical comprotein small-moleculetinteractionisn, pharmacriticalinferencomponentular dofking and protein design (Halperin et al., 2002; Langer and Hofunction2006; predictional., 2006; Sousa et al., 2006).
While SNP arrays only produce unphased alleles, statistical methods can exploit patterns of linkage disequilibrium to impute haplotypes (phased alleles) and other forms of genetic variation, based on a reference panel where both the SNPs and the imputed variation are known (a training dataset).
In [28, 29], BSAs are utilized at user devices and improve multi-user system throughput by exploiting pattern diversity.
Second, this semantics makes it possible to systematically exploit design patterns at runtime by dynamically deploying them in the managed software application.
This leads us to the idea that finite random sequences, like their infinite cousins, are not able to be generated by an algorithm which exploits patterns in the outcome sequence.
Unlike GRM, NCD exploits patterns that are present in haplotypes and unlike ROH-based methods, NCD can identify and exploit haplotypes that have a more complex genotype composition.
The underlying philosophy of this research approach is that a dense panel of single nucleotide polymorphisms (SNPs) can mark broader genomic regions by exploiting patterns of linkage disequilibrium.
Thus data mining techniques have become a popular research tool among medical researchers for identifying and exploiting patterns and relationships among numerous variables, interpreting complex diagnostic tests and predicting the outcome of a disease by historical data sets.
