Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from superlinear increases in ...
Karthik Nagarajan, Brian Holland, Alan D. George, ...
This paper proposes a method for predicting the complexity of meshing Computer Aided Design (CAD) geometries with unstructured, hexahedral, finite elements. Meshing complexity ref...
Background: Direct synthesis of genes is rapidly becoming the most efficient way to make functional genetic constructs and enables applications such as codon optimization, RNAi re...
Alan Villalobos, Jon E. Ness, Claes Gustafsson, Je...
Background: The methodologies we use both enable and help define our research. However, as experimental complexity has increased the choice of appropriate methodologies has become...
James M. Eales, John W. Pinney, Robert D. Stevens,...
Inspired by our past manual aspect mining experiences, this paper describes a random walk model to approximate how crosscutting concerns can be discovered in the absence of domain...