This work addresses the sensitivity analysis on the settings of fuzzy inference systems where multiple, yet dissimilar inputs are aggregated and resolved into a single output.
The entertainment industry and the "war" on drugs are not that dissimilar, where for every bust, or superstar taken away from us, invariably there will be another to take their place.
The discovery of these missing genes solves a long-standing mystery and provides novel examples of convergent evolutions where proteins of dissimilar architectures perform the same biochemical function.
Alternatively, in markets where brands are quite dissimilar, sales promotions can alter market shares more permanently.
At the pubs group Mitchell & Butlers – a not dissimilar situation, where billionaire Joe Lewis and his associates own a 42% stake and seem intent on running the business – the Association of British Insurers has complained loudly in support of other shareholders.
Moreover, special cases of joined similar rate dependent materials, as well as dissimilar materials where one substrate remains either elastic or approaches the rate independent limit is also included.
As with so many first novels, the central character was not unlike my teenage self, the house and town not dissimilar to where I had grown up, and the day might just as usefully have been spent looking at old photographs, or even writing.
Indeed, history may very well reward both Soros, Buffett and Levy mightily for their philanthropy, where they have become dissimilar models for giving vast sums away.
The vision of Pervasive computing has the potential to offer low-cost, high performance, and user centric solutions to exchange the information and communicate seamlessly in highly dynamic, heterogeneous environment where small and influential dissimilar devices or nodes have to set up independent network unknown by the user.
Given a positive training set of n1 pairs of similar and n2 pairs of dissimilar interfaces, where each pair is represented as a vector of N numerical features, x i = (x1,..,xN,xN), the basic goal is to train a classifier that would classify a pair of the interfaces as either similar or dissimilar.
