We present a new approach for the parallel adaption of multigrids on distributed memory architectures. It is based on a simple, object-oriented data structure employing arrays rather than the more customary linked lists. The particular problem of dynamic load balancing is solved using an innovative recursive partitioning strategy. Large-scale computations on a Cray T3E system using up to 512 pr...

We propose partitioning-based methods to facilitate the classification of 3-D binary image data sets of regions of interest (ROIs) with highly non-uniform distributions. The first method is based on recursive dynamic partitioning of a 3-D volume into a number of 3-D hyper-rectangles. For each hyper-rectangle, we consider, as a potential attribute, the number of voxels (volume elements) that bel...

The self–organizing properties of ant colonies are employed to tackle the classical combinatorial optimization problem of graph partitioning. Structural information from the graph is mapped onto an environment upon which a number of colonies compete for resources. Using Genetic Programming, a Foraging Strategy is evolved which when executed by the ants in each colony leads to a restructuring of...

Much appreciates and love is extended to all of my family and friends. I would like to especially acknowledge my parents, Fouad and Ganimah, and my wife, Huda, for their continued support and love throughout this work. Abstract Multi-FPGA systems offer the potential to deliver higher performance solutions than traditional computers for some low-level computing tasks. This requires a flexible ha...

PURPOSE AND EXPERIMENTAL DESIGN Cancer sera contain antibodies which react with a unique group of autologous cellular antigens called tumor-associated antigens (TAAs), but the low frequency of positive reactions against any individual antigen has precluded use of autoantibodies as useful diagnostic markers. With enzyme immunoassay, we examined antibody frequencies to a panel of seven TAAs, c-my...

Stability aspects of recursive partitioning procedures are investi gated Using resampling techniques diagnostic tools to assess single split stability and overall tree stability are introduced To correct for the procedure s preference for covariates with many unique realiza tions corrected p values are used in the factor selection component of the algorithm Finally methods to stabilize tree bas...

MOB is a generic algorithm for model-based recursive partitioning (Zeileis, Hothorn, and Hornik 2008). Rather than fitting one global model to a dataset, it estimates local models on subsets of data that are “learned”by recursively partitioning. It proceeds in the following way: (1) fit a parametric model to a data set, (2) test for parameter instability over a set of partitioning variables, (3...

Complex diseases such as cardiovascular disease are likely due to the effects of high-order interactions among multiple genes and demographic factors. Therefore, in order to understand their underlying biological mechanisms, we need to consider simultaneously the effects of genotypes across multiple loci. Statistical methods such as multifactor dimensionality reduction (MDR), the combinatorial ...

c classes are characterized by unknown probability distributions. A data sample containing labelled vectors from each of the c classes is available. The data sample is divided into test and training samples. A classifier is designed based on the training sample and evaluated with the test sample. The classifier is also evaluated based on its asymptotic properties as sample size increases. A mul...

A new method for identifying Hammerstein/Wiener models is proposed, where the parameters of a piecewise linear characteristic and a linear transfer function are estimated by recursive least-squares (RLS). Using smooth validity functions and an adaptive algorithm for optimal partitioning of the local linear models an efficient and accurate model can be identified.