A formal support to business and architectural design for service-oriented systems

Architectural Design Rewriting (ADR) is an approach for the design of software architectures developed within Sensoria by reconciling graph transformation and process calculi techniques. The key feature that makes ADR a suitable and expressive framework is the algebraic handling of structured graphs, which improves the support for specification, analysis and verification of service-oriented architectures and applications. We show how ADR is used as a formal ground for high-level modelling languages and approaches developed within Sensoria

A molecular dynamics simulation of water confined in a cylindrical SiO2 pore

A molecular dynamics simulation of water confined in a silica pore is performed in order to compare it with recent experimental results on water confined in porous Vycor glass at room temperature. A cylindrical pore of 40 A is created inside a vitreous SiO2 cell, obtained by computer simulation. The resulting cavity offers to water a rough hydrophilic surface and its geometry and size are similar to those of a typical pore in porous Vycor glass. The site-site distribution functions of water inside the pore are evaluated and compared with bulk water results. We find that the modifications of the site-site distribution functions, induced by confinement, are in qualitative agreement with the recent neutron diffraction experiment, confirming that the disturbance to the microscopic structure of water mainly concerns orientational arrangement of neighbouring molecules. A layer analysis of MD results indicates that, while the geometrical constraint gives an almost constant density profile up to the layers closest to the interface, with an uniform average number of hydrogen bonds (HB), the hydrophilic interaction produces the wetting of the pore surface at the expenses of the adjacent water layers. Moreover the orientational disorder togheter with a reduction of the average number of HB persists in the layers close to the interface, while water molecules cluster in the middle of the pore at a density and with a coordination similar to bulk water.Comment: RevTex, 11 pages, 12 figures; to appear in June 15 issue of J. Chem. Phy

An adaptive perception-based image preprocessing method

The aim of this paper is to introduce an adaptive preprocessing procedure based on human perception in order to increase the performance of some standard image processing techniques. Specifically, image frequency content has been weighted by the corresponding value of the contrast sensitivity function, in agreement with the sensitiveness of human eye to the different image frequencies and contrasts. The 2D Rational dilation wavelet transform has been employed for representing image frequencies. In fact, it provides an adaptive and flexible multiresolution framework, enabling an easy and straightforward adaptation to the image frequency content. Preliminary experimental results show that the proposed preprocessing allows us to increase the performance of some standard image enhancement algorithms in terms of visual quality and often also in terms of PSNR

Chaotic dynamics in a storage-ring Free Electron Laser

The temporal dynamics of a storage-ring Free Electron Laser is here investigated with particular attention to the case in which an external modulation is applied to the laser-electron beam detuning. The system is shown to produce bifurcations, multi-furcations as well as chaotic regimes. The peculiarities of this phenomenon with respect to the analogous behavior displayed by conventional laser sources are pointed out. Theoretical results, obtained by means of a phenomenological model reproducing the evolution of the main statistical parameters of the system, are shown to be in a good agreement with experiments carried out on the Super-ACO Free Electron Laser.Comment: submitted to Europ Phys. Journ.

The central structure of Broad Absorption Line QSOs: observational characteristics in the cm-mm wavelength domain

Accounting for ~20% of the total QSO population, Broad Absorption Line QSOs are still an unsolved problem in the AGN context. They present wide troughs in the UV spectrum, due to material with velocities up to 0.2 c toward the observer. The two models proposed in literature try to explain them as a particular phase of the evolution of QSOs or as normal QSOs, but seen from a particular line of sight. We built a statistically complete sample of Radio-Loud BAL QSOs, and carried out an observing campaign to piece together the whole spectrum in the cm wavelength domain, and highlight all the possible differences with respect to a comparison sample of Radio-Loud non-BAL QSOs. VLBI observations at high angular resolution have been performed, to study the pc-scale morphology of these objects. Finally, we tried to detect a possible dust component with observations at mm-wavelengths. Results do not seem to indicate a young age for all BAL QSOs. Instead a variety of orientations and morphologies have been found, constraining the outflows foreseen by the orientation model to have different possible angles with respect to the jet axis

Cosmic no-hair: non-linear asymptotic stability of de Sitter universe

We study the asymptotic stability of de Sitter spacetime with respect to non-linear perturbations, by considering second order perturbations of a flat Robertson-Walker universe with dust and a positive cosmological constant. Using the synchronous comoving gauge we find that, as in the case of linear perturbations, the non-linear perturbations also tend to constants, asymptotically in time. Analysing curvature and other spacetime invariants we show, however, that these quantities asymptotically tend to their de Sitter values, thus demonstrating that the geometry is indeed locally asymptotically de Sitter, despite the fact that matter inhomogeneities tend to constants in time. Our results support the inflationary picture of frozen amplitude matter perturbations that are stretched outside the horizon, and demonstrate the validity of the cosmic no-hair conjecture in the nonlinear inhomogeneous settings considered here.Comment: 8 pages, REVTEX, submitted to Physical Review Lette

Implementing Session Centered Calculi

Recently, specific attention has been devoted to the development of service oriented process calculi. Besides the foundational aspects, it is also interesting to have prototype implementations for them in order to assess usability and to minimize the gap between theory and practice. Typically, these implementations are done in Java taking advantage of its mechanisms supporting network applications. However, most of the recurrent features of service oriented applications are re-implemented from scratch. In this paper we show how to implement a service oriented calculus, CaSPiS (Calculus of Services with Pipelines and Sessions) using the Java framework IMC, where recurrent mechanisms for network applications are already provided. By using the session oriented and pattern matching communication mechanisms provided by IMC, it is relatively simple to implement in Java all CaSPiS abstractions and thus to easily write the implementation in Java of a CaSPiS process

Coherence of PRNU weighted estimations for improved source camera identification

This paper presents a method for Photo Response Non Uniformity (PRNU) pattern noise based camera identification. It takes advantage of the coherence between different PRNU estimations restricted to specific image regions. The main idea is based on the following observations: different methods can be used for estimating PRNU contribution in a given image; the estimation has not the same accuracy in the whole image as a more faithful estimation is expected from flat regions. Hence, two different estimations of the reference PRNU have been considered in the classification procedure, and the coherence of the similarity metric between them, when evaluated in three different image regions, is used as classification feature. More coherence is expected in case of matching, i.e. the image has been acquired by the analysed device, than in the opposite case, where similarity metric is almost noisy and then unpredictable. Presented results show that the proposed approach provides comparable and often better classification results of some state of the art methods, showing to be robust to lack of flat field (FF) images availability, devices of the same brand or model, uploading/downloading from social networks

Optimization methods for the imputation of missing values in Educational Institutions Data

The imputation of missing values in the detail data of Educational Institutions is a difficult task. These data contain multivariate time series, which cannot be satisfactory imputed by many existing imputation techniques. Moreover, almost all the data of an Institution are interconnected: the number of graduates is not independent from the number of students, the expenditure is not independent from the staff, etc. In other words, each imputed value has an impact on the whole set of data of the institution. Therefore, imputation techniques for this specific case should be designed very carefully. We describe here the methods and the codes of the imputation methodology developed to impute the various patterns of missing values which appear in similar interconnected data. In particular, a first part of the proposed methodology, called ``trend smoothing imputation'', is designed to impute missing values in time series by respecting the trend and the other features of an Institution. The second part of the proposed methodology, called ``donor imputation'', is designed to impute larger chunks of missing data by using values taken form similar Institutions in order to respect again their size and trend. • Trend smoothing imputation can handle missing subsequences in time series, and is given by a weighted combination of: (a) weighed average of the other available values of the sequence, and (b) linear regression. • Donor imputation can handle full sequence missing in time series. It imputes the Recipient Institution using the values taken from a similar institution, called Donor, selected using optimization criteria. • The values imputed by our techniques should respect the trend, the size and the ratios of each Institution

Fractal properties of 4-point interpolatory subdivision schemes and wavelet scattering transform for signal classification

Wavelet scattering is a recent time-frequency transform that shares the convolutional architecture with convolutional neural networks, but it allows for a faster training and it often requires smaller training sets. It consists of a multistage non-linear transform that allows us to compute the deep spectrum of a signal by cascading convolution, non-linear operator and pooling at each stage, resulting a powerful tool for signal classification when embedded in machine learning architectures. One of the most delicate parameters in convolutional architectures is the temporal sampling that strongly affects the computational load as well as the classification rate. In this paper the role of sampling in the wavelet scattering transform is studied for signal classification purposes. In particular, the role of subdivision schemes in properly compensating the information lost when using sampling at each stage of the transform is investigated. Preliminary experimental results show that, starting from coarse grids, interpolatory subdivision schemes reproduce copies of the original scattering coefficients at a fixed full grid that still represent distinctive features for signal classes. In fact, thanks to the ability of the scheme in reproducing similar fractal properties of the transform through an efficient iterative refinement procedure, the reproduced coefficients enable to obtain classification rates similar to those provided by the native wavelet scattering transform. The relationships between the tension parameter of the scheme and the fractal dimension of its limit curve are also investigated