Multiscale community detection can be viewed from a dynamical perspective within the Markov Stability framework, which uses the diffusion of a Markov process on the graph to uncover intrinsic network substructures across all scales. Here we reformulate multiscale community detection as a max-sum length vector partitioning problem with respect to the set of time-dependent node vectors expressed ...

This paper presents, a hybrid method, low-resolution and high-resolution, for Persian page segmentation. In the low-resolution page segmentation, a pyramidal image structure is constructed for multiscale analysis and segments document image to a set of regions. By high-resolution page segmentation, by connected components analysis, each region is segmented to homogeneous regions and identifyi...

In this survey paper, we overview the various network traffic models, especially focusing on the multiscale analysis. By multiscale analysis we mean wavelet-based self-similar and multifractal analysis. Multiscale analysis is advantageous in that it can reveal the scaling behavior of the traffic on large time scale, at the same time characterize small-scale irregularity. We also discuss how we ...

In this primarily expository paper we study the analysis of the Diederich-Fornæss worm domain in complex Euclidean space. We review its importance as a domain with nontrivial Nebenhülle, and as a counterexample to a number of basic questions in complex geometric analysis. Then we discuss its more recent significance in the theory of partial differential equations: the worm is the first smoothly...

We present a computational modeling and numerical simulation framework that enables the integration of multiple physics and spatiotemporal scales in models of physiological systems. This framework is the foundation of the IUPS (International Union of Physiological Sciences) Physiome Project. One novel aspect is the use of CellML, an annotated mathematical representation language, to specify mod...

a novel discrete singular convolution (dsc)  formulation  is  presented for the seepage analysis in irregular geometric porous media. the dsc is a new promising numerical approach which has been recently applied to solve several engineering problems. for a medium with regular geometry, realizing of the dsc for the seepage analysis is straight forward. but dsc implementation for a medium with ir...

We propose an automatic and accurate technique for classifying normal and abnormal magnetic resonance (MR) images of human brain. Ripplet transform Type-I (RT), an efficient multiscale geometric analysis (MGA) tool for digital images, is used to represent the salient features of the brain MR images. The dimensionality of the image representative feature vector is reduced by principal component ...

The study of geometric flows for smoothing, multiscale representation, and analysis of two and three dimensional objects has received much attention in the past few years. In this paper, we first present results mainly related to Euclidean invariant geometric smoothing of three dimensional surfaces. We describe results concerning the smoothing of graphs (images) via level sets of geometric heat...