In formal methods, rich specifications, such as languages and formulae of temporal logics, are checked against simple models of software programs and digital circuits, such as finite transition graphs.
Most carbons prepared through this method were rich in mesopores.
Under the new method, the rich take home less than 7.5 times what the poor do.
The immersive path-based method gives rich objective results that we propose in WT studies.
The method provided rich qualitative data and we found that an improving trend of perceived attractiveness of mobile phones was related to user satisfaction and willingness to recommend their phone to friends.
The NCA method requires rich concentration time profiles for each individual and is therefore not applicable where data are limited.
This method provides rich data; however, there may be recall bias especially pertaining to the start and end dates of partnerships.
The method extracts rich features from both the unweighted and weighted networks to train a Regression model, which is then used for the cliques filtering, growth, and candidate complex filtering.
Literature on pan-sharpening methods is rich with diversity, encompassing methods based upon the use of discrete wavelet transform (DWT [20, 21], Laplacian Pyramids[22], PCA transform[4], and IHS transform[23].
Our research centers around using probabilistic and other machine learning methods over rich linguistic representations in a variety of languages.
