We study the robustness of symmetrically coupled and clustering-based weighted heterogeneous inter-connected networks with respect to load-failure-induced cascades. This is done under the assumption that the flow dynamics are governed by global redistribution of loads based on weighted betweenness centrality. Our results indicate that no weighting bias should be assigned to inter-links when cal...

In text categorization, the class agnostic (unsupervised) tf× idf term weighting scheme has seen widespread usage. Recently proposed supervised term weighting methods including tf×rf and tf× δidf make use of term class distribution to improve the classification accuracy. However, they only account for the presence of terms in classes, ignoring the absence of key categorical terms, which may giv...

The effectiveness of three stop words lists for Arabic Information Retrieval---General Stoplist, CorpusBased Stoplist, Combined Stoplist ---were investigated in this study. Three popular weighting schemes were examined: the inverse document frequency weight, probabilistic weighting, and statistical language modelling. The Idea is to combine the statistical approaches with linguistic approaches ...

Nucleotide transitions are frequently down-weighted relative to transversions in phylogenetic analysis. This is based on the assumption that transitions, by virtue of their greater evolutionary rate, exhibit relatively more homoplasy and are therefore less reliable phylogenetic characters. Relative amounts of homoplastic and consistent transition and transversion changes in mitochondrial protei...

The effectiveness of three stop words lists for Arabic Information Retrieval---General Stoplist, CorpusBased Stoplist, Combined Stoplist ---were investigated in this study. Three popular weighting schemes were examined: the inverse document frequency weight, probabilistic weighting, and statistical language modelling. The Idea is to combine the statistical approaches with linguistic approaches ...

We present a method to decrease the storage and communication complexity of the context-tree weighting method. This method is based on combining the estimated probability of a node in the context tree and weighted probabilities of its children in one single variable. This variable is represented by its logarithm.

This project develops spatially selective RF excitation schemes, based on the excitation kspace principle (Pauly et al., 1987). In particular, we develop various k-space trajectories and weighting schemes, in order to excite cylindrical, spherical, and cubical volumes. The excitation pulses are inherenctly refocused, since the trajectories end at the origin of kspace. The analysis is based on a...

This research presents and compares the impact of text preprocessing, which has not been addressed before, on Arabic text classification using popular text classification algorithms; Decision Tree, K Nearest Neighbors, Support Vector Machines, Naïve Bayes and its variations. Text preprocessing includes applying different term weighting schemes, and Arabic morphological analysis (stemming and li...

When the assumption of homoscedasticity is not met for analytical data, a simple and effective way to counteract the greater influence of the greater concentrations on the fitted regression line is to use weighted least squares linear regression (WLSLR). The purpose of the present paper is to stress the relevance of weighting schemes for linear regression analysis and to show how this approach ...