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Fulfilled analysis gives a possibility in zero approximation of the application of representation of numbers of filling to the protein molecule, considering it as the nanowire.
As the core of context modeling, this layer involves the application of representation and reasoning techniques, which usually entail an integration of different modeling approaches for an effective outcome as to the estimation of the situation of urban systems.
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Specific applications of representations (6) and (4) below are presented in Sections 5.2 and 5.3, respectively.
The possibility of application of the representation of the numbers of filling to the protein molecule, as to the nanowire, was analyzed.
As an application of the representation, we construct a solution of the Dunkl-Poisson equations in Clifford analysis.
The application of the representation is illustrated in data compression and fractal dimension estimation temporal signals and images.
An important feature of this design is the application of knowledge representation technology—specifically conceptual structures to explicitly capture and represent the navigational semantics of each document.
Although there are some pioneering studies carried out in the late nineties, e.g., [20, 21], the application of sparse representation to direction finding has gained noticeable interest during the last decade.
The aim of this workshop is to provide a forum for discussion and debate on the application of knowledge representation and ontologies in computational science and the techniques used for the manipulation of such data.
The successful application of sparse representation-based classification (SRC) in image recognition inspires us to use SRC on the weighted dictionary and test image to perform the final identification.
In other words: activation and application of mental representations or knowledge structures, such as person schemas, formerly thought to be subconscious and automatic, are influenced by the social context in which judgments are made.
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