Analysis of tourist classification from cellular network data

We present and evaluate a classification method to estimate tourist presence in an area from cellular network data. Our approach is based on setting up a classifier to label users according to five main classes: residents, commuters, people in-transit, tourists and excursionists. We experiment the approach in some important tourist cities in Italy: Venice, Florence, Turin and Lecce. In the lack of sound groundtruth data, we analysed the composition of different classes obtaining results in line with domain knowledge. Moreover, these results are also supported by an analysis of the locations frequented by the tourists that well conforms with expectations. Finally, the number of users classified as tourists is strongly correlated with official statistics on tourist presence in the area.     

Resilient BBU placement in 5G C-RAN over optical aggregation networks

Photonic Network Communications - The huge data demand envisioned for the 5G requires radical changes in the mobile network architecture and technology. Centralized radio access network (C-RAN) is...     

Quantifying the higher-order influence of scientific publications

Scientometrics - Citation impact is commonly assessed using direct, first-order citation relations. We consider here instead the indirect influence of publications on new publications via...     

Optimization of Digital Growth of Thick N-Polar InGaN by MOCVD

Smooth 200 nm thick N-polar InGaN films were grown by metal–organic chemical vapor deposition (MOCVD) on sapphire using a digital approach consisting of a constant In, Ga, and N precursor flow with pulsed injection of H2 into the N2 carrier gas. Using this growth scheme, the H2 injection time was altered and the effect on the morphology and indium incorporation in the films observed. The effect of periodic insertion of additional GaN inter-layers on the surface morphology of the InGaN layers was also studied.     

The ANNS approach to DEM reconstruction

This research has 6 fundamental aims: (i) to present a modified version of Taylor's interpolation, one that is more effective and faster than the original; (ii) outline the capability of artificial neural networks (ANNs) to perform an optimal functional approximation of the digital elevation model reconstruction from a satellite map, using a small and independent sample of Global Positioning System observations; (iii) demonstrate experimentally how ANNs outperform the traditional and most used algorithm for the height interpolation (Taylor's interpolation); (iv) introduce a new ANN, the Conic Net, able to outperform the results of the classic and more known multilayer perceptron; (v) determine that Conic Nets, even when using Taylor's modified interpolation as input features, are able to optimally approximate the heights with one order of magnitude more than the original satellite map; and (vi) make evident the possibility to interpolate the DEM heights through an ANN, which learns a data set of known points.     

Numerical Preservation of Velocity Induced Invariant Regions for Reaction–Diffusion Systems on Evolving Surfaces

We propose and analyse a finite element method with mass lumping (LESFEM) for the numerical approximation of reaction–diffusion systems (RDSs) on surfaces in \({\mathbb {R}}^3\) that evolve under a given velocity field. A fully-discrete method based on the implicit–explicit (IMEX) Euler time-discretisation is formulated and dilation rates which act as indicators of the surface evolution are introduced. Under the assumption that the mesh preserves the Delaunay regularity under evolution, we prove a sufficient condition, that depends on the dilation rates, for the existence of invariant regions (i) at the spatially discrete level with no restriction on the mesh size and (ii) at the fully-discrete level under a timestep restriction that depends on the kinetics, only. In the specific case of the linear heat equation, we prove a semi- and a fully-discrete maximum principle. For the well-known activator-depleted and Thomas reaction–diffusion models we prove the existence of a family of rectangles in the phase space that are invariant only under specific growth laws. Two numerical examples are provided to computationally demonstrate (i) the discrete maximum principle and optimal convergence for the heat equation on a linearly growing sphere and (ii) the existence of an invariant region for the LESFEM–IMEX Euler discretisation of a RDS on a logistically growing surface.     

Onion under Microscope: An in-depth analysis of the Tor Web

World Wide Web - Tor is an open source software that allows accessing various kinds of resources, known as hidden services, while guaranteeing sender and receiver anonymity. Tor relies on a free,...     

Facilitating the migration to the microservice architecture via model-driven reverse engineering and reinforcement learning

The microservice architecture has gained remarkable attention in recent years. Microservices allow developers to implement and deploy independent services, so they are a naturally effective architecture for continuously deployed systems. Because of this, several organizations are undertaking the costly process of manually migrating their traditional software architectures to microservices. The research in this paper aims at facilitating the migration from monolithic software architectures to microservices. We propose a framework which enables software developers/architects to migrate their software systems more efficiently by helping them remodularize the source code of their systems. The framework leverages model-driven reverse engineering to obtain a model of the legacy system and reinforcement learning to propose a mapping of this model toward a set of microservices.

     

Formulation of muds for pelotherapy: effects of “maturation” by different mineral waters

Spa centres in northern Italy use clayey admixtures for the formulation of muds to be used in pelotherapy. The basic ingredient (“virgin” clay) is a dressed bentonitic geomaterial with mineralogical composition: smectite 60–70%, illite 5–10%, kaolinite 10–15%, quartz 5–10%, calcite 5–10% and feldspars 2–3%.The peloid muds are obtained by “maturation” of the virgin clay with mineral waters gushing out in situ which have different geochemistry: sulphureous, Ca-sulphate, Ca–Mg-sulphate and Br–I-salty (after the Italian regulation DPR 105/92). The maturation treatment is varying with respect to the mixing procedure and lasting time.Peculiar parameters have been tested to verify the effects of various maturation treatments, i.e., changes with respect to virgin clay.Formation of organic matter is due to the presence of microorganisms and algae in the maturation habitat. The <2 μm fraction is generally decreased due to clay particles agglomeration. Mineralogical changes are mainly concerning the degradation of clay minerals, as smectite and illite, and subordinately to the dissolution of calcite. Cation exchange capacity (CEC), soluble salts, water retention, swelling index, activity, consistency parameters (WL, WP and PI), thermal behaviour and cooling kinetics are influenced by the geochemistry of mineral waters used for the maturation treatments but with some opposite trends for Br–I-salty water, and for sulphureous and Ca-sulphate waters, respectively.Noteworthy was the influence of high-pH value of the virgin clay on the pH of peloid muds (in fact, the pH of the used mineral waters is ranging around the natural value). Furthermore, the temperature reached by the peloid muds after 20 min of application (calculated after an innovative mathematical model) is influenced by water retention. An increase in plasticity index and a slower cooling are considered to improve the quality of the obtained peloid muds for pelotherapy.The observed different cation exchange behaviour and soluble salt content could be discriminant for either dermatological masks or thermal body cataplasms.A need of regulation (standard procedures) is suggested to certificate the clay geomaterials suitable for pelotherapy and also for drugs formulation.     

Nanostructured Silicon Oxide–Nickel Oxide Sol–Gel Films with Enhanced Optical Carbon Monoxide Gas Sensitivity

Sol–gel derived silica (SiO₂) films doped with nickel oxide (NiO) nanocrystals were fabricated. A bifunctional ligand was used, bearing amine groups capable of coordinating the nickel ions and hydrolysable siloxane groups for anchoring the metal complex moiety to the silicate matrix. Nickel oxide nanocrystals precipitated at 500°C while the film was still porous. The nanocomposite films showed a reversible change in the optical transmittance in the VIS-NIR range when exposed to carbon monoxide gas. The effects of residual porosity, testing temperature, and carbon monoxide gas concentration on optical transmittance were studied.