Using Modularity Metrics to assist Move Method Refactoring of Large System

For large software systems, refactoring activities can be a challenging task, since for keeping component complexity under control the overall architecture as well as many details of each component have to be considered. Product metrics are therefore often used to quantify several parameters related to the modularity of a software system. This paper devises an approach for automatically suggesting refactoring opportunities on large software systems. We show that by assessing metrics for all components, move methods refactoring an be suggested in such a way to improve modularity of several components at once, without hindering any other. However, computing metrics for large software systems, comprising thousands of classes or more, can be a time consuming task when performed on a single CPU. For this, we propose a solution that computes metrics by resorting to GPU, hence greatly shortening computation time. Thanks to our approach precise knowledge on several properties of the system can be continuously gathered while the system evolves, hence assisting developers to quickly assess several solutions for reducing modularity issues

An agent-driven semantical identifier using radial basis neural networks and reinforcement learning

Due to the huge availability of documents in digital form, and the deception possibility raise bound to the essence of digital documents and the way they are spread, the authorship attribution problem has constantly increased its relevance. Nowadays, authorship attribution,for both information retrieval and analysis, has gained great importance in the context of security, trust and copyright preservation. This work proposes an innovative multi-agent driven machine learning technique that has been developed for authorship attribution. By means of a preprocessing for word-grouping and time-period related analysis of the common lexicon, we determine a bias reference level for the recurrence frequency of the words within analysed texts, and then train a Radial Basis Neural Networks (RBPNN)-based classifier to identify the correct author. The main advantage of the proposed approach lies in the generality of the semantic analysis, which can be applied to different contexts and lexical domains, without requiring any modification. Moreover, the proposed system is able to incorporate an external input, meant to tune the classifier, and then self-adjust by means of continuous learning reinforcement.Comment: Published on: Proceedings of the XV Workshop "Dagli Oggetti agli Agenti" (WOA 2014), Catania, Italy, Sepember. 25-26, 201

Efficient generation of NN-photon generalized binomial states in a cavity

Extending a previous result on the generation of two-photon generalized binomial field states, here we propose an efficient scheme to generate with high-fidelity, in a single-mode high-Q cavity, N-photon generalized binomial states with a maximum number of photons N>2. Besides their interest for classical-quantum border investigations, we discuss the applicative usage of these states in realizing universal quantum computation, describing in particular a scheme that performs a controlled-NOT gate by dispersive interaction with a control atom. We finally analyze the feasibility of the proposed schemes, showing that they appear to be within the current experimental capabilities.Comment: 8 pages, 2 figure

MRI-guided focused ultrasound surgery in musculoskeletal diseases: the hot topics

MRI-guided focused ultrasound surgery (MRgFUS) is a minimally invasive treatment guided by the most sophisticated imaging tool available in today's clinical practice. Both the imaging and therapeutic sides of the equipment are based on non-ionizing energy. This technique is a very promising option as potential treatment for several pathologies, including musculoskeletal (MSK) disorders. Apart from clinical applications, MRgFUS technology is the result of long, heavy and cumulative efforts exploring the effects of ultrasound on biological tissues and function, the generation of focused ultrasound and treatment monitoring by MRI. The aim of this article is to give an updated overview on a "new" interventional technique and on its applications for MSK and allied sciences

Wind- and tide-induced currents in the Stagnone Lagoon (Sicily)

The hydrodynamic circulation is analyzed in the coastal lagoon of Stagnone di Marsala, a natural reserve located in the north-western part of Sicily, using both experimental measurements and numerical simulations. Field measurements of velocities and water levels, carried out using an ultrasound sensor (3D), are used to validate the numerical model. A 3D finite-volume model is used to solve the Reynolds-averaged momentum and mass balance differential equations on a curvilinear structured grid, employing the k–ε turbulence model for the Reynolds stresses. The numerical analysis allows to identify the relative contribution of the forces affecting the hydrodynamic circulation inside the lagoon. In the simulations only wind and tide forces are considered, neglecting the effects of water density changes. Two different conditions are considered. In the first both the wind stress over the free-surface and the tidal motion are imposed. In the second the wind action is neglected, to separately analyze the tide-induced circulation. The comparison between the two test cases highlights the fundamental role of the wind on the hydrodynamics of the Stagnone lagoon, producing a strong vertical recirculation pattern that is not observed when the flow is driven by tides only

Tectonic evolution of the Sicilian Thrust System (central Mediterranean)

The Sicilian Thrust System (STS) is a south-verging (Africa-verging) fold-and-thrust belt including a Mesozoic-Paleogene sedimentary sequence. This thrust stack owes its origin to the deformation of pre-orogenic strata deposited in different palaeogeographic domains belonging to passive margins of the African plate. The STS was deformed during the Neogene, following the closure of the Tethys Ocean and the continental collision between the Sardo-Corso Block and the North Africa margins. The thrust pile was detached from the underlying basement during the Miocene-Pleistocene. The regional-scale structural setting recognized allows us to reconstruct the tectonic evolution of the STS as follows: I - piggy-back thrusting from the Late Oligocene to the Langhian, inducing the building of the Inner Sicilian Chain (ISC); II - piggy-back thrusting from the Langhian to the Tortonian, inducing the formation of the Middle Sicilian Chain (MSC); III - generalized extensional deformation in the chain-foredeep-foreland system from the Tortonian to the Early Pliocene; IV - a new onset of piggy-back thrusting after the Early Pliocene allowed the building of the Outer Sicilian Chain and out-of sequence thrusting in the previously developed ISC and MSC

Validation of Geant4 nuclear reaction models for hadrontherapy and preliminary results with SMF and BLOB

Reliable nuclear fragmentation models are of utmost importance in hadrontherapy, where Monte Carlo (MC) simulations are used to compute the input parameters of the treatment planning software, to validate the deposited dose calculation, to evaluate the biological effectiveness of the radiation, to correlate the bþ emitters production in the patient body with the delivered dose, and to allow a non- invasive treatment verification. Despite of its large use, the models implemented in Geant4 have shown severe limitations in reproducing the measured secondaries yields in ions interaction below 100 MeV/A, in term of production rates, angular and energy distributions [1–3]. We will present a benchmark of the Geant4 models with double-differential cross sec- tion and angular distributions of the secondary fragments produced in the 12C fragmentation at 62 MeV/A on thin carbon target, such a benchmark includes the recently implemented model INCL++ [4,5]. Moreover, we will present the preliminary results, obtained in simulating the same interaction, with SMF [6] and BLOB [7]. Both, SMF and BLOB are semiclassical one-body approaches to solve the Boltzmann-Langevin equation. They include an identical treatment of the mean-field propagation, on the basis of the same effective interaction, but they differ in the way fluctuations are included. In particular, while SMF employs a Uehling-Uhlenbeck collision term and introduces fluctuations as projected on the density space, BLOB introduces fluctuations in full phase space through a modified collision term where nucleon-nucleon correlations are explicitly involved. Both of them, SMF and BLOB, have been developed to sim- ulate the heavy ion interactions in the Fermi-energy regime. We will show their capabilities in describing 12C fragmentation foreseen their implementation in Geant4

Mapping combined wildfire and heat stress hazards to improve evidence-based decision making

Heat stress and forest fires are often considered highly correlated hazards as extreme temperatures play a key role in both occurrences. This commonality can influence how civil protection and local responders deploy resources on the ground and could lead to an underestimation of potential impacts, as people could be less resilient when exposed to multiple hazards. In this work, we provide a simple methodology to identify areas prone to concurrent hazards, exemplified with, but not limited to, heat stress and fire danger. We use the combined heat and forest fire event that affected Europe in June 2017 to demonstrate that the methodology can be used for analysing past events as well as making predictions, by using reanalysis and medium-range weather forecasts, respectively. We present new spatial layers that map the combined danger and make suggestions on how these could be used in the context of a Multi-Hazard Early Warning System. These products could be particularly valuable in disaster risk reduction and emergency response management, particularly for civil protection, humanitarian agencies and other first responders whose role is to identify priorities during pre-interventions and emergencies

Integration of HVSR measures and stratigraphic constraints for seismic microzonation studies: the case of Oliveri (ME)

Because of its high seismic hazard the urban area of Oliveri has been subject of first level seismic microzonation. The town develops on a large coastal plain made of mixed fluvial/marine sediments, overlapping a complexly deformed substrate. In order to identify points on the area probably suffering relevant site effects and define a preliminary Vs subsurface model for the first level of microzonation, we performed 23 HVSR measurements. A clustering technique of continuous signals has been used to optimize the calculation of the HVSR curves. 42 reliable peaks of the H/V spectra in the frequency range 0.6–10 Hz have been identified. A second clustering technique has been applied to the set of 42 vectors, containing Cartesian coordinates, central frequency and amplitude of each peak to identify subsets which can be attributed to continuous spatial phenomena. The algorithm has identified three main clusters that cover significant parts of the territory of Oliveri. The HVSR data inversion has been constrained by stratigraphic data of a borehole. To map the trend of the roof of the seismic bedrock, from the complete set of model parameters only the depth of the seismic interface that generates peaks fitting those belonging to two clusters characterized by lower frequency has been extracted