نتایج جستجو برای: dimensional similarity
تعداد نتایج: 501061 فیلتر نتایج به سال:
This article describes an innovative method for the determination of heat flow (specific loss; linear density) from a one-metre length twin pipe directly-buried network. Such losses are currently described by applying analytical procedures based on transfer theory. It is rather complicated to accurately express loss using such procedures, due necessity determine individual values thermal resist...
background: lipophosphoglycan 3 (lpg3) is required for the lpg assembly, a well known virulent molecule. in this study, the lpg3 gene of the lizard and mammalian leishmania species were cloned and sequenced. a three-dimensional structure (3d) for the target sequence was also predicted by comparative (homology) modeling. materials and methods: an optimization pcr amplification was performed on g...
The effect of a transverse magnetic field on the boundary layer flow and heat transfer of anisothermal stretching cylinder is analyzed. The governing partial differential equations for themagnetohydrodynamic, temperature, and concentration boundary layers are transformed into a setof ordinary differential equations using similarity transformations. The obtained ordinarydifferential equations ar...
The order and arrangement of dimensions (variates) is crucial for the effectiveness of a large number of visualization techniques such as parallel coordinates, scatterplots, recursive pattern, and many others. In this paper, we describe a systematic approach to arrange the dimensions according to their similarity. The basic idea is to rearrange the data dimensions such that dimensions showing a...
Subspace clustering is a challenging task in the field of data mining. Traditional distance measures fail to differentiate the furthest point from the nearest point in very high dimensional data space. To tackle the problem, we design minimal subspace distance which measures the similarity between two points in the subspace where they are nearest to each other. It can discover subspace clusters...
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