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While non-amplification based methods make use of hybridization strategies with DNA or RNA probes, amplification based methods rely on reactions such as polymerase chain reaction (PCR) to amplify the amount of nucleic acids for better sensitivity [8].
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In contrast to feature-based methods, region-based methods make use of the whole image content to establish correspondence.
Some feature-based methods make use of the properties of HVS to govern the performance of the method for better correlation with subjective assessment.
On the other hand, the lexical-based methods make use of a pre-defined list of words, where each word is associated with a specific sentiment.
The MMSE-based methods make use of the statistics of the wireless channel for channel estimation and achieve excellent bit error rate (BER) performance in a low-mobility environment [2 4].
Revealed preferences based valuation methods record and analyze actualpayments on observable transactions for the commodities/services of interest whilestated preference based valuation methods make use of data on hypothetical choicesand implicit payments (Hensher et al. 2005).
The two methods make use of heuristics based on entity distance.
These new methods make use of physical resources like cloud based architectures.
MHCIIMulti [ 12] is a kernel based method that makes use of multi-instance technique for measuring the similarity between peptides.
➢This method makes use of "abstime" function.
Network inference methods based on GGM make use of the relation, (55) ρ ij | V ∖ { ij } = − ω ij ω ii ω jj, connecting the partial correlation coefficient of full-order (LHS) with the elements of Ω, ω ij ∈ Ω.
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