Picture-based task definition and parameterization support system

Applications for task definition and automation are valuable tools to automated software engineering area. This paper describes a solution to support a parameterized task definition using screen capture images. The approach allows the capture of a sequence of actions defined by the user. Through the captured sequence of actions, the approach assists in the implementation of task automation processes. Based on picture-driven computing the proposed tool aims to reduce the challenges that users face while trying to define tasks. This approach provides also a foundation for the creation of picture-driven based tests for interactive systems, enabling to test any interactive system but also allowing for the definition, parameterization and execution of tests that might involve the use of several independent interactive systems.info:eu-repo/semantics/acceptedVersio

Applications of Continuum Shell Model

The nuclear many-body problem at the limits of stability is considered in the framework of the Continuum Shell Model that allows a unified description of intrinsic structure and reactions. Technical details behind the method are highlighted and practical applications combining the reaction and structure pictures are presented.Comment: 10 pages, 3 figure

Gluon density in nuclei

In this talk we present our detail study ( theory and numbers) [1] on the shadowing corrections to the gluon structure functions for nuclei. Starting from rather contraversial information on the nucleon structure function which is originated by the recent HERA data, we develop the Glauber approach for the gluon density in a nucleus based on Mueller formula [2] and estimate the value of the shadowing corrections in this case. Than we calculate the first corrections to the Glauber approach and show that these corrections are big. Based on this practical observation we suggest the new evolution equation which takes into account the shadowing corrections and solve it. We hope to convince you that the new evolution equation gives a good theoretical tool to treat the shadowing corrections for the gluons density in a nucleus and, therefore, it is able to provide the theoretically reliable initial conditions for the time evolution of the nucleus - nucleus cascade.Comment: Talk at RHIC'96, 43 pages, 23 figure

Deeply virtual Compton scattering off nuclei

We consider the hard leptoproduction of a photon off nuclei up to spin-1. As a new result we present here the general azimuthal angular dependence of the differential cross section for a spin-1 target. Its twist-two Fourier coefficients of the interference and squared deeply virtual Compton scattering amplitude are evaluated in leading order approximation of perturbation theory in terms of generalized parton distributions, while the pure Bethe--Heitler cross section is exactly calculated in terms of electromagnetic form factors. Relying on a simple model for the nucleon generalized parton distribution $H$, which describes the existing DVCS data for a proton target, we estimate the size of unpolarized cross sections, beam and longitudinal target spin as well as unpolarized charge asymmetries for present fixed target experiments with nuclei. These estimates are confronted with preliminary HERMES data for deuterium and neon.Comment: 50 pages LaTeX, 7 figures, 3 tables, page style fixe

Regimes of self-organized criticality in the atmospheric convection

Large scale organization in ensembles of events of atmospheric convection can be generated by the combined effect of forcing and of the interaction between the raising plumes and the environment. Here the "large scale" refers to the space extension that is larger or comparable with the basic resolved cell of a numerical weather prediction system. Under the action of external forcing like heating individual events of convection respond to the slow accumulation of vapor by a threshold-type dynamics. This is due to the a time-scale separation, between the slow drive and the fast convective response, expressed as the "quasi-equilibrium". When there is interaction between the convection plumes, the effect is a correlated response. We show that the correlated response have many of the characteristics of the self-organized criticality (SOC). It is suggested that from the SOC perspective, a description of the specific dynamics induced by "quasi-equilibrium" can be provided by models of "punctuated equilibrium". Indeed the Bak-Sneppen model is able to reproduce (within reasonable approximation) two of the statistical results that have been obtained in observations on the organized convection. We also give detailed derivation of the equations connecting the probabilities of the states in the update sequence of the Bak-Sneppen model with $K=2$ random neighbors. This analytical framework allows the derivation of scaling laws for the size of avalanches, a result that gives support to the SOC interpretation of the observational data.Comment: Text prepared for the Report of COST ES0905 collaboration (2014). Latex 45 page

TextureNet: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes

We introduce, TextureNet, a neural network architecture designed to extract features from high-resolution signals associated with 3D surface meshes (e.g., color texture maps). The key idea is to utilize a 4-rotational symmetric (4-RoSy) field to define a domain for convolution on a surface. Though 4-RoSy fields have several properties favorable for convolution on surfaces (low distortion, few singularities, consistent parameterization, etc.), orientations are ambiguous up to 4-fold rotation at any sample point. So, we introduce a new convolutional operator invariant to the 4-RoSy ambiguity and use it in a network to extract features from high-resolution signals on geodesic neighborhoods of a surface. In comparison to alternatives, such as PointNet based methods which lack a notion of orientation, the coherent structure given by these neighborhoods results in significantly stronger features. As an example application, we demonstrate the benefits of our architecture for 3D semantic segmentation of textured 3D meshes. The results show that our method outperforms all existing methods on the basis of mean IoU by a significant margin in both geometry-only (6.4%) and RGB+Geometry (6.9-8.2%) settings