Tuning of level-set speed function for speckled image segmentation

The segmentation of speckled images, as the synthetic aperture radar (SAR) images, is usually recognized as a very complex problem, because of the speckle, multiplicative noise, which produces granular images. In segmentation problems, based on level set method, the evolution of the curve is determined by a speed function, which is fundamental to achieve a good segmentation. In this paper we propose a study of the new speed function obtained by the linear combination of image average intensity and image gradient speed functions.

Robust Design Optimization for the refit of a cargo ship using real seagoing data

Robust Design Optimization (RDO) represents a really interesting opportunity when the specifications of the design are careful and accurate: the possibility to optimize an industrial object for the real usage situation, improving the overall performances while reducing the risk of occurrence of off-design con- ditions, strictly depends on the availability of the information about the probability of occurrence of the various operative conditions during the lifetime of the design.

Long-range hydrodynamic effect due to a single vesicle in linear flow

Vesicles are involved in a vast variety of transport processes in living organisms. Additionally, they serve as a model for the dynamics of cell suspensions. Predicting the rheological properties of their suspensions is still an open question, as even the interaction of pairs is yet to be fully understood. Here we analyse the effect of a single vesicle, undergoing tank-treading motion, on its surrounding shear flow by studying the induced disturbance field delta(V) over right arrow, the difference between the velocity field in its presence and absence.

Linear and anomalous front propagation in systems with non-Gaussian diffusion: The importance of tails

We investigate front propagation in systems with diffusive and subdiffusive behavior. The scaling behavior of moments of the diffusive problem, both in the standard and in the anomalous cases, is not enough to determine the features of the reactive front. In fact, the shape of the bulk of the probability distribution of the transport process, which determines the diffusive properties, is important just for preasymptotic behavior of front propagation, while the precise shape of the tails of the probability distribution determines asymptotic behavior of front propagation.

Dynamics and rheology of cells and vesicles in shear flow

A deep understanding of the dynamics and rheology of suspensions of vesicles, cells, and capsules is relevant for different applications, ranging from soft glasses to blood flow [1]. I will present the study of suspensions of fluid vesicles by a combination of molecular dynamics and mesoscale hydrodynamics simulations (multi-particle collision dynamics) in two dimensions [2], pointing out the big potential of the numerical method to address problems in soft matter.

A numerical algorithm for the assessment of the conjecture of a subglacial lake tested at Amundsenisen, Svalbard

The melting of glaciers coming with climate change threatens the heritage of the last glaciation of Europe likely contained in subglacial lakes in Greenland and Svalbard. This aspect urges specialists to focus their studies (theoretical, numerical, and on-field) on such fascinating objects. Along this line, we have approached the validation of the conjecture of the existence of a subglacial lake beneath the Amundsenisen Plateau at South-Spitzbergen, Svalbard, where ground penetrating radar measurements have revealed several flat signal spots, the sign of the presence of a body of water.

Coupling weakly-compressible SPH with Finite Volume Method: an algorithm for simulating free-surface flows

An algorithm for coupling a classical Finite Volume (FV) approach, that discretize the Navier-Stokes equations on a block structured Eulerian grid, with the weakly-compressible SPH is presented. The coupling procedure aims at applying each solver in the region where its intrinsic characteristics can be exploited in the most efficient and accurate way: the FV solver is used to resolve the bulk flow and the wall regions, whereas the SPH solver is implemented in the free surface region to capture details of the front evolution.

Petaflop biofluidics simulations on a two million-core system

We present a computational framework for multi-scale simulations of real-life biofluidic problems. The framework allows to simulate suspensions composed by hundreds of millions of bodies interacting with each other and with a surrounding fluid in complex geometries. We apply the methodology to the simulation of blood flow through the human coronary arteries with a spatial resolution comparable with the size of red blood cells, and physiological levels of hematocrit (the red blood cell volume fraction).

A leaky integrate-and-fire model with adaptation for the generation of a spike train

A model is proposed to describe the spike-frequency adaptation observed in many neuronal systems. We assume that adaptation is mainly due to a calcium-activated potassium current, and we consider two coupled stochastic differential equations for which an analytical approach combined with simulation techniques and numerical methods allow to obtain both qualitative and quantitative results about asymptotic mean firing rate, mean calcium concentration and the firing probability density. A related algorithm, based on the Hazard Rate Method, is also devised and described.

A hierarchical Krylov-Bayes iterative inverse solver for MEG with physiological preconditioning

Magnetoencephalopgraphy (MEG) is a non-invasive functional imaging modality for mapping cerebral electromagnetic activity from measurements of the weak magnetic field that it generates. It is well known that the MEG inverse problem, i.e. the problem of identifying electric currents from the induced magnetic fields, is a severely underdetermined problem and, without complementary prior information, no unique solution can be found.