R ecognition of o cclude d obje cts in synthetic ap erture radar (SAR) images is a signi cant problem for automatic target recognition. In this paper, we present a hidden Markov modeling (HMM) based approach for recognizing objects in synthetic ap ertur eradar (SAR) images. We identify the peculiar char acteristics of SAR sensors and using these characteristics we develop featur ebased multiple...

Abstract. Statistical learning methods offer a promising approach for low-flow regionalization. We examine seven statistical models (Lasso, linear, and nonlinear-model-based boosting, sparse partial least squares, principal component regression, random forest, support vector regression) the prediction of winter summer low flow based on hydrologically diverse dataset 260 catchments in Austria. I...

User Equilibrium Models are used to analyse a network with given O-D matrix to find out the flows in each link that is a part of the network. This problem has been studied at different levels of comprehension ranging from deterministic, probabilistic, as well as dynamic models. This report gives a brief on the methods that are part of a group represented by Stochastic User Equilibrium (commonly...

We derive an analytic condition that predicts the exact location of inertial particle clustering in three-dimensional steady or two-dimensional time-periodic flows. The particles turn out to cluster on attracting inertial Lagrangian coherent structures that are smooth deformations of invariant tori. We illustrate our results on three-dimensional steady flows, including the Hill's spherical vort...

Nonzero currents characterize the nonequilibrium state in stochastic dynamics (or master equation) models of natural systems. In such models there is a matrix R of transition probabilities connecting the states of the system. We show that if the strength of a transition increases, so does the current along the corresponding bond. We also address the inverse problem: given a set of observed curr...